Background: Immune checkpoint inhibitors (ICIs) have significantly improved the therapeutic efficacy and extended the survival of patients with advanced nonsmall-cell lung cancer (NSCLC); however, the benefits were confined to certain populations. How to optimally select eligible patients for ICI therapy needs to be solved. Materials and Methods: A total of 100 NSCLC patients treated with ICIs from two independent studies were included and then were randomly assigned to the train dataset and the validation dataset. A logistic regression model and a decision tree model were developed to predict the objective response outcome. The area under the receiver operating characteristic curves (AUC) of the two models was evaluated. The confusion matrix for decision tree model was also calculated. Results: The comparison of baseline clinical features between the train and validation datasets showed no significant difference. The multivariable logistic regression identified three variables associated with objective response, i.e, age, tumor mutational burden (TMB), and programmed cell death ligand 1. Moreover, a logistic regression model was developed based on these variables. A decision tree, including age and TMB, was also developed. The AUCs of the two models were both 0.85 in the train dataset. And, that was better than each single variable. The AUC of the decision tree in the validation dataset was inferior to that of the logistic regression model. The performance showed that the decision tree could not effectively identify responders. Conclusion: The performance of the decision tree developed in this study was dismal. Its predictive ability was inferior to the logistic regression model.

Objective: To investigate the effect of zoledronic acid on the remission of bone pain in patients with non-small cell lung cancer (NSCLC) during and after radiotherapy. Materials and Methods: A total of 197 NSCLC patients who received radiotherapy for osteopathy with complete recorded visual analog scale (VAS) scores were enrolled. Of these, 79 patients were treated with radiotherapy alone (radiotherapy group), and 118 patients were treated with radiotherapy combined with zoledronic acid (zoledronic acid group). The differences in VAS scores between the two groups were compared. Logistic regression was used to determine the odds ratio (OR) of the complete response rate for osteodynia between the zoledronic acid group and the radiotherapy group. Univariate and multivariate Cox regression analyses were used to evaluate the independent prognostic factors for overall survival (OS). Results: The complete response rate in patients in the zoledronic acid group was significantly higher than that in patients in the radiotherapy group (odds ratio [OR] = 3.201, 95% confidence interval [CI]: 1.559–6.575, P = 0.002). Except for the baseline VAS score, all VAS scores in the zoledronic acid group at different time points during radiotherapy, at the end of radiotherapy, and 1 month after radiotherapy were significantly lower than those in the radiotherapy group (all P < 0.01). Grade 3 constipation was observed in only one patient in the zoledronic acid group. There were no other Grade 3 adverse events. Multivariate Cox regression analysis showed that only the treatment group (zoledronic acid group vs. radiotherapy group, hazard ratio [HR] = 0.720, 95% CI: 0.530–0.978, P = 0.036) and manner of bone destruction (mixture vs. osteolytic, HR = 0.596, 95% CI: 0.424–0.837, P = 0.003) were independent prognostic factors for OS. Conclusion: Zoledronic acid combined with radiotherapy can not only accelerate bone pain control but also prolong survival in NSCLC patients with bone metastases.

Objective: This study aimed to compare rehabilitation after lobectomy performed with a Da Vinci robot versus thoracoscopy. Materials and Methods: Patients who underwent lobectomy at the Changzhou First People's Hospital from November 2020 to May 2021 were analyzed retrospectively, including 182 patients in the Da Vinci robot group and 280 patients in the thoracoscopy group. Postoperative hospital stay and postoperative pain were compared between groups. Results: The hospitalization cost of the Da Vinci robot group was $ 10874.06 ± 1757.07, which was higher than that of the thoracoscopy group ($ 7500.96 ± 1704.83). The postoperative hospital stay was significantly shorter in the Da Vinci robot group (4.74 ± 2.104 days) than that in the thoracoscopy group (5.55 ± 2.669 days; t = −3.664, P < 0.001). No significant differences between groups were observed in postoperative intensive care unit admission time and postoperative chest tube indwelling time. The proportion of patients with no pain 2 h after the operation was significantly higher in the Da Vinci robot group than in the thoracoscopy group (26.9% vs. 11.8%; χ² = 17.639, P < 0.001). The proportion of patients with no pain during the first activity was significantly higher in the Da Vinci robot group than in the thoracoscopy group (54.9% vs. 39.6%; χ² = 12.109, P = 0.004). Conclusion: The total cost of Da Vinci robotic surgery was higher than that of thoracoscopy for lobectomy, but the postoperative recovery was better, and the pain was less severe.

Background and Purpose: Burnout syndrome (BOS), the popular phenomenon of our pandemic era, is examined in three dimensions: emotional exhaustion, depersonalization and cynicism, and personal inefficiency. One of the known and accepted ways of measuring BOS is Maslach Burnout Inventory (MBI), in which these three dimensions are measured by 22 items, using 5- or 7-point Likert scales. The aim of this study is to eliminate the loss of precision in BOS measurement and handle the subjectivity and uncertainty, as a result, to get rid of the bias caused by the classical way. Methods: To do this, fuzzy conjoint analysis (FCA) is used together with MBI. In the classical way, the calculations are made by assigning crisp values to the answers, which causes scientific bias and loss of precision because Likert scale type answers have subjectivity and uncertainty. Results: When the scores obtained with FCA are examined, all the scores and some BOS levels differ. When the position of the values according to the borders of the BOS levels is taken into account, it can be said that these tiny differences caused by the loss of precision make this difference. Conclusion: Findings show that the resulting scores changed significantly when calculations are made with FCA. Especially, when these scores are interpreted as intervals or grades, as in MBI, even tiny differences may result in significant scientific bias.

Background: The purpose of this study was to establish the newest trends in medical health-care systems. Methods: This is a theoretical reflection about next-generation medicine, which is the first step to begin with an exponential medical health care and break with past models. Results: In the past, the medical health care relied on an evidence-based practice to provide the best treatment options for patients, however, since 2010, a strong economic wave has shaped the perspective into a value-based medicine framework. We are facing new social dynamics and megatrends in our society. The emergence of 4.0 technologies is leading us to a pathway where a next-generation medicine will create an exponential value for the overall health-care ecosystem. Originality: Next-Generation Medicine (NGM) integrates health care into digital ecosystems linked by innovative interfaces, advanced analytics, centric customer models, and digital epidemiology surrounding a new concept of health and disease management. NGM is based on four core capabilities of physicians: creativity, collaboration, communication, and critical thinking added to advanced digital operations that create a systemic risk management. This integration is developed using bidirectional and integrative digital platforms operated by artificial intelligence/Machine Learning (ML) connected to the Internet of things and data collection in the cloud or in the edge computing. It is time for health-care visionaries to set prejudice aside and start contemplating the amazing landscape that next-generation medicine could offer.

Background and Purpose: Three-dimensional printing (3DP) selective laser melting (SLM) and electron beam melting (EBM) technique can construct porous Ti-6Aluminum-4Vanadium (Ti-6Al-4V) scaffolds with special microstructural and biomechanical properties. However, it is still needed to be tested for bone tissue engineering. Materials and Methods: To investigate the microstructure and surface modification of a porous titanium scaffold, 3DP-SLM technique was used, and the mechanical and biological performance of the scaffolds was compared with that fabricated by EBM technique. Ti-6Al-4V scaffolds were computer-designed and fabricated using low-power SLM (L-SLM). The microstructure morphologies of L-SLM Ti-6Al-4V (L-SLM-Ti) scaffolds were determined and compared with EBM-fabricated Ti-6Al-4V (EBM-Ti) scaffolds. Each scaffold was immersed with marrow clot for 1 h until fully combined with bone mesenchymal stem cells in clots. The biomechanical and cellular response of these two kinds of Ti-6Al-4V scaffolds were compared. Results: The L-SLM-Ti scaffolds showed a microstructure closer to the designed parameters than that of the EBM-Ti scaffolds. The L-SLM-Ti scaffold fibers had a rougher surface than the EBM-Ti scaffolds. Meanwhile, L-SLM-Ti scaffolds had a lower elasticity modulus and lower bearing force than EBM-Ti scaffold. Cell proliferation and the relative expression levels of OPN, COL1, and RUNX2 in L-SLM-Ti scaffolds was apparently higher than in the EBM-Ti scaffolds, with no significant difference found between the percentage of live cells found in L-SLM-Ti and EBM-Ti scaffolds. Conclusion: 3DP-Ti-6Al-4V scaffolds fabricated by L-SLM and designed with rougher surfaces and larger pore sizes may have more reasonable biomechanical properties and increased biological performance than traditional EBM-Ti scaffolds. These L-SLM-Ti scaffolds might be suitable candidates for bone defect repair.

Background: Low-resolution magnetic resonance imaging (MRI) has high imaging speed, but the image details cannot meet the needs of clinical diagnosis. More and more researchers are interested in neural network-based reconstruction methods. How to effectively process the super-resolution reconstruction of the low-resolution images has become highly valuable in clinical applications. Methods: We introduced Super-Resolution Convolution Neural Network (SRCNN) into the reconstruction of magnetic resonance images. The SRCNN consists of three layers, the image feature extraction layer, the nonlinear mapping layer, and the reconstruction layer. For the feature extraction layer, a multi-scale feature extraction (MFE) method was used to extract the features in different scales by involving three different levels of views, which is superior to the original feature extraction in views with fixed size. Compared with the original feature extraction only in fixed size views, we used three different levels of views to extract the features of different scales. This MFE could also be combined with residual learning to improve the performance of MRI super-resolution reconstruction. The proposed network is an end-to-end architecture. Therefore, no manual intervention or multi-stage calculation is required in practical applications. The structure of the network is extremely simple by omitting the fully connected layers and the pooling layers from traditional Convolution Neural Network. Results and Conclusions: After comparative experiments,the effectiveness of the MFE SRCNN-based network in super-resolution reconstruction of MR images has been greatly improved. The performance is significantly improved in terms of evaluation indexes peak signal-to-noise ratio and structural similarity index measure, and the detail recovery of images is also improved.

Background and Purpose: To characterize the global physician community's opinions on the use of digital tools for COVID-19 public health surveillance and self-surveillance. Materials and Methods: Cross-sectional, random, stratified survey done on Sermo, a physician networking platform, between September 9 and 15, 2020. We aimed to sample 1000 physicians divided among the USA, EU, and rest of the world. The survey questioned physicians on the risk-benefit ratio of digital tools, as well as matters of data privacy and trust. Statistical Analysis Used: Descriptive statistics examined physicians' characteristics and opinions by age group, gender, frontline status, and geographic region. ANOVA, t-test, and Chi-square tests with P < 0.05 were viewed as qualitatively different. As this was an exploratory study, we did not adjust for small cell sizes or multiplicity. We used JMP Pro 15 (SAS), as well as Protobi. Results: The survey was completed by 1004 physicians with a mean (standard deviation) age of 49.14 (12) years. Enthusiasm was highest for self-monitoring smartwatches (66%) and contact tracing apps (66%) and slightly lower (48–56%) for other tools. Trust was highest for health providers (68%) and lowest for technology companies (30%). Most respondents (69.8%) felt that loosening privacy standards to fight the pandemic would lead to misuse of privacy in the future. Conclusion: The survey provides foundational insights into how physicians think of surveillance.

Background: Telerehabilitation has been recommended as a potential solution to bridge service delivery gap, especially in geographically remote areas with shortage of healthcare personnel and lack of access to physical therapy. This study was aimed to develop and test the feasibility of a smartphone video-based exercise program (VBEP) for patients with knee osteoarthritis (OA). Methods: This two-phase study involved the development and feasibility testing stages. A three-round modified Delphi approach was employed in the development phase involving a panel of four experts and a patient with knee OA. Based on consensus, five types of exercises comprising seated knee flexion and extension, quadriceps isometric setting, quadriceps strengthening exercise, hamstring clenches, and wall squats were developed into a video-program for knee OA. 15 consenting patients with knee OA participated in the feasibility testing of the program after 2 weeks of utilization. Feasibility of the VBEP was assessed using system usability scale and user experience questionnaire, respectively. The quadruple visual analog scale was used to assess the pain intensity. Results: The mean age and pain intensity of the participants were 67.3 ± 6.4 years and 61.1 ± 10.6, respectively. User perceived usability of the VBEP was 77.1 ± 13.1 (out of 100) with a high usability rating of 86.7%. Pragmatic quality score, hedonic quality rating, attractiveness, and perspicuity were 2.2 (out of 3.0), 1.6 (out of 3.0), 2.4 (out of 3.0), and 3.0 (out of 3.0), respectively. Efficiency, dependability, stimulation, and novelty scores were 2.3 (out of 3.0), 1.8 (out of 3.0), 2.3 (out of 3.0), and 1.0 (out of 3.0), respectively. Conclusions: The VBEP for knee OA has high usability and quality rating, as well as good user experience, and it may be a feasible alternative platform for rehabilitation of patients with knee OA.

In view of the shortage of equipment resources and the inability for on-site disassembly and assembly training in the current teaching of positron emission tomography/computed tomography (PET/CT), a simulation training system for PET/CT based on Unity 3D engine and C# language is designed by 3ds Max and Cinema 4D. The system realizes the simulation interaction of the equipment, thus providing a simulation environment for the operation training of equipment disassembly and maintenance. Through practical application, more users have a great interest in learning, and the comprehensive quality of operation and maintenance ability has been significantly improved, which shows that the system effectively improves teaching quality and reduces teaching costs. Taken together, we can see that it is worth rolling out.

Background: Digital physiotherapy in line with global health coverage has become a salient field of physiotherapy practice where routine and innovative forms of information and communications technology are employed with the aim of facilitating effective delivery and access to physiotherapeutic services and resources. This study evaluated and determined the socio-demographic correlates of awareness, acceptability, and willingness-to-pay (WTP) for digital physiotherapy among patients. Materials and Methods: A total of 92 consenting patients who were 18 years and older responded in this cross-sectional study. An adapted tool on awareness, acceptability, and WTP for telemedicine services was adapted for use in this study. Data were analyzed using descriptive statistics of mean, standard deviation, and percentages; inferential statistics of Chi-square was used for test of association. Alpha level was set at P < 0.05. Results: The mean age of the respondents was 52.40 ± 15.62 years. There was a high rate of unawareness (91.3%), moderate-to-high acceptability (87.0%) and high WTP (88.0%) for digital physiotherapy, respectively. There was no significant association between the socio-demographic factors and each of acceptability and WTP for digital physiotherapy (P > 0.05). Conclusion: In spite of low awareness of digital physiotherapy, Nigerian patients attending physiotherapy clinics are willing to accept and pay for its use irrespective of socio-demographic variations.

Objective: Biomedical data processing generally requires the secure stepwise transfer of sensitive personal information across multiple parties. Mediating such operations using distributed secure digital ledgers, i.e., blockchains, is investigated in this article. Materials and Methods: The bitmark property rights blockchain was used to simulate the process of assessing individuals for enrollment to specific clinical trials. In the scenario presented, a sponsor publishes a recruitment call for a clinical trial and patients signal their willingness to participate in the trial through blockchain transactions. The blockchain creates and maintains digital references of the medical data assets of prospective study participants as well as digital property certificates for assigning access rights to corresponding medical data assets. Trial matching services review the patient blockchain records and recommend study participants that are likely to meet the enrollment criteria of recruiting clinical trials. Digital certificates assign transient access rights to the data assets of the prospective study participants. These certificates are transferred to pertinent matching services and sponsors, allowing these organizations to examine the candidacy of each prospective study participant. Results: The trial matching simulation demonstrates that property rights blockchains can implement complicated multiparty interactions, such as those associated with medical data exchange, without supplemental peer-to-peer communications. Conclusions: Blockchain-based data marketplaces of the type described, when coupled with data-controlled virtual infrastructure environments (i.e., Medical Data Trusts), provide a viable model for managing the transfer, provenance, and processing of individual health information.

Background: A magnetic resonance image (MRI)-guided robotic system dedicated for prostate cancer (PC) was produced that carries a small spherically focused, single-element, ultrasonic transducer which can be potentially utilized endorectally. Materials and Methods: The developed robotic device utilizes four computer-controlled axes. An agar-based phantom was developed, which included a cavity that mimics the rectum geometry. Experiments with the system were performed in a 1.5T MRI system using the gel phantom. The transducer has a diameter of 18 mm, operates with 3 MHz, and focuses energy at 40 mm. Results: The functionality of the robot was assessed by means of magnetic resonance thermometry, demonstrating sufficient heating in both axes of operation (linear and angular). Conclusions: A functional MRI-guided robotic system was produced, which can create significant and controlled thermal exposures. The intention is to use the proposed device endorectally in the future for the focal treatment of PC.

Background: In this article, a medical robotic system that performs magnetic resonance imaging-guided focused ultrasound surgery ablation is presented. The main innovation of this robotic system is that all the actuators are placed outside the water container. The transducer is immersed in water through an arm which is attached to the angular stage. Materials and Methods: The system includes three linear and one angular stage. The device uses piezoelectric motors for each motion stage. The accuracy was achieved with optical encoders. A focused transducer operated at 1 MHz with a radius of curvature of 10 cm and a diameter of 4 cm was used. A polyacrylamide gel was used to assess the ultrasound protocol. Results: The system was tested in the magnetic resonance imaging (MRI) environment and was proved to be a magnetic resonance compatible. The accuracy of the system was tested, and it was found that spatial steps of 0.2 mm can be safely and reliably achieved. With this robotic system, it is possible to access many organs that ultrasound penetrates with the patient placed in a prone position. Conclusion: The proposed robotic system can be modified so that it can be used for other applications. One example of an alternative application is MRI-guided biopsy. Another application is to replace the transducer arm with a radio frequency (RF) device to perform MRI guided RF ablation. Finally, the maneuverability of the robotic system can be enhanced further by attaching another angular stage to the system.

Background and Objectives: Precision medicine and drug repurposing provide an opportunity to ameliorate the challenges of declining pharmaceutical R&D productivity, rising costs of new drugs, and poor patient response rates to existing medications. Multifactorial “disease signatures” provide unique insights into the architecture of complex disease populations that can be used to better stratify patient groups, aiding the delivery of precision medicine. Methods: Analysis of a complex disease (breast cancer) population was undertaken to identify the combinations of single-nucleotide polymorphisms that are associated with different disease subgroups. Target genes associated with the disease risk of these subgroups were examined, followed by identification and evaluation of existing active chemical leads as drug repurposing candidates. Results: One hundred and seventy-five disease-associated gene targets relevant to different subpopulations of breast cancer patients were identified. Twenty-three of these genes were prioritized as both promising novel drug targets and repurposing candidates. Two targets, P4HA2 and TGM2, have high repurposing potential and a strong mechanistic link to breast cancer. Conclusions: This study showed that detailed analysis of combinatorial genomic (and other) features can be used to accurately stratify patient populations and identify highly plausible drug repurposing candidates systematically across all disease-associated targets.

Background: A decline in physical activity (PA) during pregnancy, despite its benefits to the mother and fetus, invites concerns for innovative platforms for its implementation. This cross-sectional study assessed knowledge, attitude, and “willingness to use” and “willingness to pay” for smartphone applications (apps) for PA. Materials and Methods: A total of 196 consenting pregnant women participated in this study. Eligible respondents were pregnant women who were 18 years and older, on at least a second antenatal visit and uses a mobile phone. Three purposively selected antenatal care facilities were surveyed. A self-developed questionnaire pilot tested for face and content validity was used as the research tool. Results: The mean age of the respondents was 27.5 ± 3.42 years, and 52% of them were occasionally engaged in PA. The point prevalence for smartphone use for general purpose and the usability rate of smartphone app were 72.4% and 84.2%, respectively. The rates for willingness to use PA apps for pregnancy and willingness to pay for the apps were 64.3% and 63.8%, respectively. There was a significant association between the attitude of respondents toward smartphone apps use for PA and number of parity (χ² = 7.119; P = 0.028). There was no significant association between knowledge of the use of smartphone apps for PA in pregnancy and each of the educational qualification (χ² = 13.046; P = 0.523), income (χ² = 11.086; P = 0.679), age (χ² = 4.552; P = 0.804), gravidity status (χ² = 5.302; P = 0.506), and number of parity (χ² = 1.878; P = 0.758). Conclusion: Nigerian pregnant women have good knowledge, positive attitude, and willingness to use smartphone apps for PA in pregnancy. There was a significant association between the number of parity and each of the attitude and knowledge of the use of smartphone apps for PA.

Background and Objectives: Nonintrusive heart rate (HR) monitoring can be a useful tool for health monitoring. By creating capacitively coupled textile electrodes, a comfortable monitoring system can be integrated into seating or bedding that can monitor HR through clothing. This work empirically studied two factors for a system of this type: the electrode size and the material worn by the subject. Materials and Methods: HR measurements were taken using six different sizes of the rectangular textile electrode with four subjects and the signal-to-noise ratio (SNR) of the signals were analyzed. A further set of experiments were conducted with a single subject and a fixed electrode size where different materials were worn. Results: Electrode size was seen to have a statistically insignificant effect on the collected signal quality. The SNR was also largely unaffected by the worn material type. Conclusion: This study provided empirical data relating to two important factors for nonintrusive, textile, and HR monitoring systems. This data will be helpful for designing a seat-based HR monitoring system or to understand the operational limitations of a system of this type.

Purpose: Online adaptive correction in image-guided intensity-modulated radiotherapy appears to be a promising approach for precision radiation treatment in head-and-neck tumors. This research is designed to evaluate the setup uncertainties in the left-right (L-R), superior-inferior (S-I), and anterior-posterior (A-P) directions and rotational variations: pitch, roll, and yaw for head-and-neck cancer (HNC) patients with the ExacTrac 6 degree-of-freedom (6D) image-guided radiotherapy (IGRT) system. Materials and Methods: The setup errors measured by ExacTrac 6D IGRT system at the treatment unit with respect to the planning computed tomography were recorded for 40 patients with head-and-neck tumors. The residual setup errors were computed and quantitatively analyzed. Results: The results indicated that the setup errors measured in the S-I direction were larger than the other two directions. For the three rotational angles, the results were very close. The verifications showed that after the first correction, the overall setup errors were generally <0.32 mm in the L-R, S-I, and A-P directions and <0.2° in the three rotational variations: pitch, roll, and yaw. According to the results of verifications, we know that ExacTrac 6D IGRT system was accurate and clinical feasibility. Conclusion: The results of our study have shown that daily image guidance with ExacTrac 6D image-guided system for HNC patients is effective. These data suggest it allows a high accurate of setup errors.

Background and Objective: Portable and readily accessible wellness devices can aid vital sign measuring for those interested in tracking their health. In this diagnostic accuracy study, we evaluated the performance of the VitalWellness device (VW), a wireless, compact, noninvasive device that measures four vital signs (VS) – blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature (BT) – using the index finger and forehead. Methods: Adult volunteers with VS that fell both within and outside of the normal physiological range were enrolled to provide BP, HR, RR, and BT measurements using both the VW and Food and Drug Administration-approved reference devices. A subgroup of participants underwent an additional test to analyze the VW's performance on HR and RR outside of normal physiological ranges. Statistical measurements were plotted on scatter and Bland–Altman plots. Sensitivity analyses to evaluate the VW's performance by gender, skin color, finger size, and auxiliary activities were performed. Results: A total of 263 participants completed the study. On an average, systolic BP measured using the VW was 10 mmHg lower than that of the reference device (correlation coefficient r = 0.7), whereas diastolic BP was 3 mmHg lower (r = 0.6), and RR was 2 bpm lower (r = 0.7). VW HR and BT measurements were, on average, 1 bpm and 0.3°F higher than the corresponding reference measurements (r = 0.9 and r = 0.3), respectively. Conclusion: The VW device is well-suited for home-based, nonmedical monitoring of HR, RR, and BP. Further improvement in measurement accuracy is required to enable applications for medical use.

Background and Objectives: Image segmentation is the basic problem in computer vision and pattern recognition. This study mainly focuses on the segmentation of medical sequence images. Materials and Methods: In this article, we considered the spatial similarity of the medical sequence image in active contour model (ACM) for segmentation. First, by utilizing the similarity of object contour between adjacent slices of medical images, and then using the segment result of the former slice as the initial contour of the next image to segmentation. The proposed model can automatically obtain a better initial contour location and reduce the computing cost for segment processing. Second, to improve the accuracy of image segmentation, we considered the similarity of the object contour between adjacent slices, and introduce a punishment term in localized ACM. Results: We compared our model and other methods for segmenting medical brain magnetic resonance slices, and the experimental results on synthetic medical sequence images validate the effectiveness of the proposed method. Conclusions: By utilizing the similarity of object contour between adjacent slices of medical images, and using the segment result of former slice as the initial contour of the next image to segment, the proposed model can obtain better initial contour location for segmentation sequence images and reduce the computing cost for whole medical sequence image segmentation process.

Background and Objectives: Point set registration is a very fundamental problem in computer vision. The registration problem can be divided into rigid and nonrigid registration. The transformation function modeling of rigid registration is simpler, whereas the nonrigid registration is better to solve the practical problems. Materials and Methods: We proposed a robust point set registration method using both global and local structures. Here, we use a popular probability model, Gaussian mixture model, to preserve the global structure of point set. Then, we designed a local constraint provided by some neighboring points to maintain the local structure of the point set. Finally, expectation–maximization algorithm is used to update model parameters in our method. Results: First of all, we carried out experiments on the synthesized data, which included four degradation cases: deformation, noise, outlier, and rotation. By comparing the mean and standard deviation of registration errors with the several state-of-the-art methods, our method was proved to have stronger robustness. Then, we conducted experiments on real retinal fundus images, aiming to establish reliable feature point correspondence between the two images. The experimental results show that we perform better when the two images have larger shooting angles and more noises. Conclusions: The Gaussian mixture protects the global structure of the point set, and the local constraints make full use of the local structure, which makes our method more robust. Experiments on synthetic data prove that our method obtains superior results to those of the state-of-the-art methods. Experiments on retinal image data show that our method also performs very well in practical applications.

Background and Objectives: In magnetic resonance (MR) images' quantitative analysis, there are often considerable difficulties due to factors, such as intensity inhomogeneities and low contrast. Here, we construct a new image segmentation method to solve the MR image segmentation problem caused by internal and external factors. Materials and Methods: We downloaded a series of MR images as research objects through the BrainWeb (http://www.bic.mni.mcgill.ca/brainweb/). There is low contrast information between different components in these images. In addition, we randomly added a certain degree of bias field information to the images. We proposed a model that can simultaneously perform bias field estimation and image segmentation. Our idea is to make use of the property that observed image can be decomposed into multiplicative components. First, the bias field representation is given by a series of smooth basic functions; the required true image is represented as the function of observed image and bias field. Then, the segmentation model of Gaussian probability distribution with different means and variances is constructed by local information. Results: Qualitative experiments (intensity inhomogeneity images) show that our model achieves satisfactory segmentation results with very few (<10) iterations for severe intensity inhomogeneities image segmentation, while quantitative experiments (20 brain MR images) show that the proposed model can achieve higher accuracy in segmentation. Conclusions: Different from the existing model, our model is constructed based on the local information of the true image, and the influence of above-mentioned factors is better avoided and obtain satisfactory results.

Background and Objectives: Stroke is a leading cause of long-term disability. Rehabilitation involving repetitive, high-intensity, and task-specific exercise is the pathway to restore motor skills. Robotic assistive devices such as Gloreha are increasingly being used in upper limb rehabilitation. The aim of this study is to explore the efficacy of robotic therapy for upper limb rehabilitation using robotic glove (Gloreha) in patients with stroke. Materials and Methods: The patients affected by stroke who were admitted to our rehabilitation unit were studied. Patients were exposed to Gloreha device rehabilitation (30 min/die), physiotherapy (1,5 hours/die), and occupational therapy (30 min/die). We measured the impairment in motor function and muscle tone using the modified Ashworth scale (MAS), the activities of daily living functional independence measure (FIM), and the finger dexterity Nine-Hole Peg test (NHPT). Results: Twelve patients (mean age = 64.5 years; male/female: 8:4) were admitted at the rehabilitation training. We found statistically significant differences between admission and discharged in terms of functional recovery using the FIM scale (pre/M = 88.33; post/M = 117.25,P = 0.01); hand training showed a better outcome using the NHPT (pre/M = 51.8; post/M = 36.33, P = 0.01). No significant changes were observed in terms of spasticity with the MAS (pre/M = 1.25; post/M = 1.08;P > 0.05). Conclusions: Rehabilitation with robotic glove (Gloreha) can positively promote functional recovery of arm function in a patient with stroke.

Background and Objective: Oral cancer is a major public health problem which carries significant morbidity and mortality. A shift from treatment to prevention by screening is the key to reduce oral cancer lesion among population. Searching for an affordable and viable alternative to face-to-face screening that can expedite diagnosis of oral diseases among rural population with good accuracy is mandatory. One of the most realistic solutions to acknowledge this hurdle and the unavailability of dental professionals, is mobile teledentistry. Materials and Methods: Secondary data analysis was conducted, in which the data were derived from the project of “Oral Cancer Screening Program in Rural population” conducted by Thirumalai Mission Hospital, Ranipet. Ninety-six biopsies were taken for the patients who had visible oral lesions which had been provisionally diagnosed on clinical examination. Oral screening was carried out by unaided face-to-face screening method by a trained and calibrated dentist. In a separate subsequent visit, a trained teledental assistant took photographs of each participant's mouth by using a smartphone camera; the charting of the photographs was conducted independently by two dentists. Results: Intra-examiner reliability of Examiner 1 and Examiner 2 was 0.943 and 0.921, respectively. Inter examiner reliability score of 0.879 was obtained between both the examiners by the photographic method of diagnosis. Intraclass correlation coefficient between two methods of examination was 0.812. Agreement between the photographic examination (Examiner 1, Examiner 2) with the gold standard biopsy report was 0.791 and 0.855, respectively. Conclusion: Smartphone camera use offers a valid and reliable means of remote screening for oral lesions. Photographs of the oral lesions taken from the smart-phone camera with an acceptable diagnostic validity and reliability.

Background and Objectives: Multiple sclerosis (MS) lesion segmentation is important in estimating the progress of the disease and measuring the impact of new clinical treatments. Manual lesion delineation for the segmentation of lesions is time-consuming and suffers from observer variability. Therefore, a fully automated MS lesion segmentation method is considerable important in clinical practice. Subjects and Methods: In this study, we present a multilabel fusion embedded level set method for white matter lesion segmentation from MS patient images. Specifically, we focus on the validation of the variational level set method. Lesion segmentation is achieved by extending the level set contour which consists of an intensity-constrained term, an image data term, and a regularization term. Results: To compare the performance of our method with other state-of-the-art methods, we evaluated the methods with 25 magnetic resonance imaging datasets of MS patients. The dice score reaches an average of 0.55 for the proposed method. The sensitivity value and specificity value reach an average of 0.89 and 0.14, respectively. Conclusions: Experimental results demonstrate that our method is robust to parameter setting and outperforms other methods. The intensity-constrained term plays a key role in improving the segmentation accuracy. The experimental results show that our approach is effective and robust for lesion segmentation, which might simplify the quantification of lesions in basic research and even clinical trials.

Background and Objectives: Developing serious games (SGs) for children is challenging, especially when dealing with complex medical diagnosis. Enhancing children's compliance for the treatment of chronic conditions is a crucial challenge that requires caring about the engagement of users in the game experience already from the initial stages of the development. Materials and Methods: Participatory design is the methodological key to trace the right path toward an effective and easy-to-use game; specific methodological settings are necessary to collect meaningful feedback and guide the creation of the game. Our article reports the involvement of 14 young users in two different stages of the design and development of two SGs for chronic clinical conditions (Crohn's disease and cystic fibrosis). Results: Specific feedbacks were reported about game contents (e.g., the preference for anthropomorphic avatars) and technological issues (e.g., the need of a graphical tutorial). Conclusions: Using the same methodological approach in two different phases of the development allows to highlight children's perspective toward a technological solution addressing clinical compliance.

Background and Objectives: This study investigates a novel type of textile pressure sensor fabricated in a single production step. The work characterizes two designs of electronic textile pressure sensor creating new knowledge into the operation of these types of textile sensors. Interest in electronic flexible film and electronic textile pressure sensing has grown in recent years given their potential in medical applications, principally in developing monitoring solutions for wheelchair users and hospital patients to help prevent the formation of pressure ulcers. Materials and Methods: Two designs of textile pressure sensor were produced using computerized flat-bed knitting. One design was produced in a single step, where the conductive tracks were incorporated into the top and bottom surfaces of a knitted spacer structure (knitted spacer pressure sensor). The other sensor was comprised of separate knitted layers. The response of the sensors was tested by changing the applied pressure in two ways: By altering the applied force or changing the area of the applied force. Sensor hysteresis and how the sensor thickness affected its response were also examined. Results: The two sensor designs behaved differently under the tested conditions. The knitted spacer pressure sensor was pressure sensitive up to 25 kPa and showed no hysteretic effects over the pressure range of interest. Conclusions: This study presents a fully textile pressure sensor that was produced with a single production step and demonstrates its functionality over the pressure range of interest for monitoring wheelchair users.

Background and Objectives: Nowadays, more and more open source medical imaging databases are published on the Internet for medical teaching, algorithm development, and medical research. However, a statistical survey of these databases is still lacking. In this survey, we summarize the current status of open source medical image databases on the Internet. The aim is to make it easier for everyone to find and use open source medical image data. Methods: Information about publicly available medical image databases was collected by searching for scientific papers and Internet search engines. Based on the collected information, the number of databases and the number of images were counted for different diseases, body parts, imaging modalities, and countries. Results: Cancer, particularly breast cancer and lung cancer, ranked top in database numbers among all diseases. The breast, brain, lung, and chest are the top four body parts in terms of database numbers. Computed tomography, magnetic resonance imaging, and X-ray are the most common imaging modalities in the open source datasets. The USA and the Netherlands are the top two countries who own the most databases. Conclusions: The rankings for diseases and body parts were closely related to the diseases morbidity and the health-care expenditure of a country. The number of open sources of medical imaging databases is still growing; there is a need for continuous statistical research on their existence status in the coming years. The list of all the collected databases is opened on the Internet (https://docs.qq.com/sheet/DQWF0QlZKVHpHU1Za).

Objective: The objective of the study is to investigate the regional capacity and implementation of radiotherapy for nasopharyngeal carcinoma (NPC) in Chongqing city. Materials and Methods: The questionnaires, self-designed electronic forms in a uniform format, were distributed to 37 radiotherapy institutions, which covered all the medical units equipped with radiotherapy equipment in this city. Results: Of the 37 radiotherapy units in Chongqing, 27 could deliver radiotherapy for NPC, but the remaining 10 institutions could not due to equipment limitations. From January to December 2017, a total of 2904 patients with NPC were treated with radiotherapy. Patients from the five teaching hospitals in the main districts of the city accounted for 86% of the participants. There were four representative types of radiotherapy plan based on radiation technology among these units. Of the 37 units, 18 used intensity-modulated radiotherapy, 6 adopted three-dimensional conformal radiotherapy, 2 chose volumetric modulated arc therapy, and 1 delivered two-dimensional traditional radiotherapy; only 10 units applied magnetic resonance imaging (MRI)-computed tomography registration and fusion for gross tumor volume delineation in NPC treatment, and only 3 units routinely acquired nasopharyngeal and neck MRI scans to evaluate tumor shrinkage during treatment. Conclusion: Obvious distinctions exist between various units in Chongqing city in radiotherapeutic strategy, radiotherapy plan, frequency of image-guided radiation therapy, and mid-treatment evaluation for NPC radiotherapy. We need to learn and apply NPC guideline and consensus to improve NPC radiotherapy in Chongqing and to construct a rule with regional characteristics.

Background and Objectives: In neurorehabilitation, exoskeleton plays a key role among the numerous innovative and advanced frontiers in technology. The exoskeleton is intended for rehabilitation and mobility in patients with neurological motor diseases. The aim of this study is to evaluate the impact of robotic training in body perception and mood. Methods: Two patients, one affected by stroke and another affected by spinal cord injury admitted to our rehabilitation unit, have been studied. We used two exoskeletons (Ekso and Indego). Training occurred 3 days a week for a total of forty sessions, with a duration of 50–60 min each session. Psychological tests focused on depression (Beck Depression Inventory), self-perception (body uneasiness test A), and the workload (NASA-Task Load Index) were used. Results: After the treatment, we found a great improvement in mood disorders and body perception in the patients. Conclusions: Patients with neurological motor diseases can increase motor and psychological skills using an active powered exoskeleton.

Background and Objectives: The utility of postdischarge remote monitoring with patient self-measurement of physiological parameters has not been utilized in the elective colorectal surgical setting till date. Before full application of this utility, patient-acquired measurements' accuracy, and ability to detect deviation from normal physiological must be assessed. This study aims to ascertain the congruency of patient-measured and nurse-measured readings in the postoperative in-hospital setting, before future application in the home setting. Methods: This is a prospective single-institution study comparing patient and nurse measured readings of blood pressure, heart rate, oxygen saturation, and temperature, in ambulatory patients in the postoperative setting. Patients were provided with and trained on the usage of a handheld computing device with bluetooth-enabled measuring adjuncts preoperatively. Patients were instructed to acquire two sets of readings per day for 2 days. These were compared with nurse-acquired measurements and extrapolated to the modified “National Early Warning Score” system. Inter-rater concordance was analyzed using the Bland–Altman method for raw physiological measurements and for modified-National Early Warning Score (NEWS) risk and response categories. Results: A total of 40 elective colorectal patients were prospectively approached. Twenty-seven completed the study with 25 patients (15 males, age range 18–79, undergoing a variety of colorectal procedures) accruing a total of 98 datasets of physiological parameter readings. There were no significant differences/bias between blood pressure (P = 0.572), heart rate (0.122), and oxygen saturation (P = 0.308) readings. Patient and linked nurse measurements for all patients elicited the same modified NEWS clinical risk and required response in all instances. Conclusion: Patient self-measurement of physiological parameters and subsequent derived modified NEWS categories using a remote monitoring system are comparable to nurse-acquired measurements. Remote monitoring is technically feasible, and the next steps would be to trial this technology in the home setting.

Background and Objectives: Diet plays a huge role in health, both by increasing metabolic disease risks and acutely through adverse interactions with diseases and medications. Multimorbid and polypharmaceutical patients are at a particularly high risk of such interactions due to the number of drugs they take. This leads to avoidable hospitalizations and poor compliance. This study built and demonstrated a tool that provides personalized dietary advice that accounts for a patient's combination of disease and drugs in real-time on their mobile device. Methods: A comprehensive list of validated drug-disease-food interactions from several reputable sources was constructed. This was compiled into a knowledge graph using the RACE array logic platform. This interactions knowledge graph was used to power a personalized dietary advisor application on a mobile device. Results: Data from over 500,000 drug-disease-food interactions including 1,699 food ingredients and 9,526 disease interactions were compiled into a highly compressed knowledge model. This was used to inform recommendations for individual complex patients. It was also tested on virtual population of 10,000 multimorbid and polypharmaceutical patients. Conclusions: This study showed that digital health tools can provide highly contextual and adaptive responses from a single knowledge graph. The study showed it is possible to provide highly personalized health advice to complex patients in real-time on their own mobile device without having to hold such private information on a server. This enables highly secure, private and personalized digital health tools to be built.

Background and Objectives: The Singapore population is aging rapidly, with increased prevalence of chronic diseases and healthcare demand. Telemonitoring of vital signs will enable better care of the patient. However, daily monitoring requires a change in lifestyle and compliance may be an issue. Materials and Methods: A total of 18 patients in 4 demographics were identified. Telemonitoring equipment was deployed to them for 3 months. Results: After 3 months, the well individual did not use the monitoring devices. 50% of the patients with chronic medical disease <65 years old continued the use of the devices. 2 out of 7 activities of daily living (ADL) independent individuals >65 years old continued the daily monitoring and almost all (5 out of 6) ADL dependent patients continued daily routine monitoring. The dropout may be due to technical issues, user fatigue, change in caregiver or resistance to technology. Conclusions: Remote monitoring will be more successful if the individual already is doing routine self-monitoring or has a life-threatening health-related event. Technical support is also important to help retrain the person in using the devices and for troubleshooting.

Background and Objectives: In this study, the spatial courses of the connecting tubule (CNT) of nephron from different depth of cortex and the collecting duct (CD) in mouse kidney was established with the aid of three-dimensional visualization technology. Subjects and Methods: Kidneys from three C57/BL/6J mice were removed after perfusion fixation. The tissue blocks were cut perpendicular to the longitudinal axis of the kidney and embedded in Epon-812. A total of 2000, 2.5-μm-thick consecutive sections were obtained from the renal capsule to papilla. After acquiring the digitalized images and alignment, the CNT from 137 nephrons were traced with the custom-made programs. The spatial arrangement of the CNT was visualized, and the length was measured. Results: Each CD received CNT from 5 to 7 nephrons. The CNT from different level of cortex all drained into the CD at superficial cortex but took different path. The CNT from superficial cortical nephron joined CD directly, while the CNT from middle and juxtamedullary cortical nephron joined each other to form an arcade, and the latter drained into CD at superficial cortex. The length of the arcade ranged 400–800 μm. Conclusions: The CNT joined CD at superficial cortex, which means the fluid along the CD from the cortex would not be added from outside, contributing to stabilization of the hormone regulation in the transportation of solutes and water along the CD from cortex to medulla.

Background and Objectives: Current developments in electroencephalography (EEG) foster medical and nonmedical applications outside the hospitals. For example, continuous monitoring of mental and cognitive states can contribute to avoid critical and potentially dangerous situations in daily life. An important prerequisite for successful EEG at home is a real-time classification of mental states. In this article, we compare different machine learning algorithms for the classification of eye states based on EEG recordings. Materials and Methods: We tested 23 machine learning algorithms from the Waikato Environment for Knowledge Analysis toolkit. Each classifier was analyzed on four different datasets, since two separate approaches – called sample-wise and segment-wise – in combination with raw and filtered data were applied. These datasets were recorded for 27 volunteers. The different approaches are compared in terms of accuracy, complexity, training time, and classification time. Results: Ten out of 23 classifiers fulfilled the determined requirements of high classification accuracy and short time of classification and can be denoted as applicable for real-time EEG eye state classification. Conclusions: We found that it is possible to predict eye states using EEG recordings with an accuracy from about 96% to over 99% in a real-time system. On the other hand, we found no best, universal method of classifying EEG eye states in all volunteers. Therefore, we conclude that the best algorithm should be chosen individually, using the optimal classification accuracy in combination with time of classification as the criterion.

Background: In this research, the pulse wave data of 274 subjects from both the patient and control groups are evaluated and analyzed. Based on the pulse wave analysis of those subjects, a study of diagnosing cardiovascular diseases is conducted. Methods and Results: By investigating the correlation between the cardiac indices Reverse Shoulder Index (RSI) and Ratio of Distance for patients with cardiovascular diseases from different age and gender groups, several common and important observations are reported. By carrying out case studies, we have verified some of our findings with several patient cases. Conclusion: In this research, pulse wave analysis is applied for the study of cardiovascular diseases with some important observations. We expect that our discoveries in this research can eventually help the end-users in cardiovascular diseases diagnosis.

Background and Objectives: Cervical total disc replacement (TDR) is a novel dynamically stabilizing technique for the symptomatic cervical intervertebral segment. While the long-term effect of mainstream cervical nonconstrained artificial disc group (CNAD) does not match the theoretical effects of mobility preserving and neural decompression. The cervical semiconstrained elastic integrated artificial disc (CSID) may be a more reasonable design. However, beneficial or adverse effects of this design have not been measured and data for biomechanical effect are unavailable. The aim of this study is to assess the biomechanical effect of CSID on the segmental motion at implanted and adjacent levels. Methods: This study was supported by medical science developmental funding of Nanjing (20,000 dollars). Eight cadaveric C3–T1 specimens were loaded in flexion/extension (F/E), axial rotation (AR), and lateral bending (LB) with CSID, CNAD, and anterior fusion (AF) implanted at C5–C6 level alternatively. The range of motion (ROM), neutral zone (NZ), and elastic zone (EZ) at implanted and adjacent levels were measured. The mean values of parameters in the intact specimen group (INT), CSID group, CNAD group, and AF group were compared statistically (n = 8). Results: There was no significant difference of ROM, NZ, and EZ at implanted and adjacent levels between CSID and INT in F/E, AR, and LB (P > 0.05). CNAD caused a significant change of EZ in F/E and LB and ROM in LB at implanted level. Meantime, CNAD caused ROM increasing at adjacent levels (P < 0.05). AF caused the most significant changes of ROM, NZ, and EZ in F/E, AR and LB, compared to CSID and CNAD (P < 0.05). Conclusions: The semiconstrained elastic integrated design of cervical artificial disc may mimic of physiological disc's biomechanical effects on segmental kinematics at implanted and adjacent levels more closely, compared to nonconstrained discs and AF. CSID disc may reduce the acceleration of postTDR degeneration at the implanted and adjacent levels due to this promoted biomechanical performance. CSID disc could be a potential candidate for future cervical artificial intervertebral prosthesis studies.

Objectives: This article describes novel magnetic resonance imaging (MRI)-compatible focused ultrasound robotic systems and agar-based MRI-compatible ultrasonic phantoms mimicking bone. Materials and Methods: All the robotic systems and phantoms were developed using three-dimensional (3D) printing technology using plastic material. The tissue surrounding the bone in the phantoms was mimicked using agar-based solutions. Results: The article presents MRI-guided focused ultrasound robotic systems for brain, prostate, and gynecological targets. It also reports on MRI-compatible ultrasonic phantoms for brain, breast, bone, and motion. Conclusions: The popular 3D printing technology serves a major role in MRI-guided focused ultrasound surgery because MRI-guided focused ultrasound robotic systems can be developed. In addition, 3D printing can be used to develop MR-compatible phantoms that include bone structures for testing the safety and efficacy of focused ultrasound applications. All the developed structures have been evaluated in MRI environment using either mimicking materials or animals.

Background and Objectives: The diagnosis of cancer is concerned, and the prediction of cell carcinoma is of great importance for the treatment. Materials and Methods: First, we obtain a series of slices of tumor cell pathology in clinical data, with being followed training sets and test sets gained by adding data model. Then, we design a convolutional neural network training and prediction model. After that, we optimize parameters for training and prediction model, combining experience. Results: In experiment, the accuracy of the model predicting for cell carcinoma is 87.38%. Conclusions: This study provides a reference that predicts the extent of cell carcinoma progression by using deep learning model.

Background and Objectives: In this article, we propose an image segmentation model based on Chan-Vese (CV) for image segmentation. By taking into account the local features of the image, the new proposed model can successfully segment images with intensity nonuniformity. Materials and Methods: We quantitatively compare our method with other two state-of-the-art algorithms, namely, CV model and local binary fitting (LBF) model in segmenting synthetic MR images with the ground truth from BrainWeb; the data can be available at: https://www.mni/mcgill.ca/brainweb/. For segmenting the missing and weak boundaries, to deal with the intensity inhomogeneity, based on the LBF model, we introduced the convex total variation regularization term, for explicit smoothing of the level set function ø. The evolution equation will be solved through the level set method of calculus of variations. Results: In the experimental processing, we use some real images and magnetic resonance imaging brain images as the experimental images, to validate the stabilization of algorithm. The experimental results on comprehensive and sincerity images show the outstanding of our proposed model with reference to stabilization and availability. Conclusions: We propose a new segmentation local information of an image and introduce a new regularization functional is to keep the level set function smooth. Finally, various experimental results on real and low-contrast image, showing which is a powerful type of images, including some that would be difficult to segment with gradient-based methods. In addition, the advantages of the proposed model are better than CV model and the LBF model. Our new model can effectively segment a real image.

Background and Objectives: The increasing clinical use of torso positron emission tomography/computed tomography (PET/CT) demands automated segmentation of torso organs from PET/CT images. We attempt to use the multi-atlas segmentation approach for trunk organ segmentation from the low-dose CT images of PET/CT. Since atlas selection is a prerequisite step for multi-atlas segmentation, this study focuses on evaluating the performance of different atlas selection strategies for torso organ segmentation. Methods: We evaluated two criteria for atlas selection, including image similarity and body mass index (BMI) difference between the atlas and the target image. Based on the two criteria, ten atlases are selected and registered to the target image, followed by the label fusion step to achieve final segmentation. Results: The BMI criterion yields comparable segmentation accuracy to the image similarity criterion but with much less computation time. All the evaluated atlas selection methods have Dice >0.9 for the lungs, heart, and liver and Dice < 0.85 for the skeleton, spleen, and kidneys. The inter-method differences are not significant for the high-contrast and big-sized organs such as skeleton, lungs, heart, and liver. For the low-contrast and smaller-sized organs such as spleen and kidneys, none of the atlas selection methods significantly outperforms random atlas selection. Conclusions: BMI is an effective and efficient atlas selection criterion for low-dose torso CT images. The spleen and kidneys are difficult to get good segmentation, no matter which atlas selection method is used. It is important to develop more effective atlas selection methods for the spleen and kidneys.

Background and Objectives: Multimodal image registration is a crucial step in prostate cancer radiation therapy scheme. However, it can be challenging due to the obvious appearance difference between computed tomography (CT) and magnetic resonance imaging (MRI) and unavoidable organ motion. Accordingly, a nonrigid registration framework for precisely registering multimodal prostate images is proposed in this paper. Materials and Methods: In this work, multimodal prostate image registration between CT and MRI is achieved using a hybrid model that integrates multiresolution strategy and Demons algorithm. Furthermore, to precisely describe the deformation of prostate, B-spline-based registration is utilized to refine the initial registration result of multiresolution Demons algorithm. Results: To evaluate our method, experiments on clinical prostate data sets of nine participants and comparison with the conventional Demons algorithm are conducted. Experimental results demonstrate that the proposed registration method outperforms the Demons algorithm by a large margin in terms of mutual information and correlation coefficient. Conclusions: These results show that our method outperforms the Demons algorithm and can achieve excellent performance on multimodal prostate images even the appearances of prostate change significantly. In addition, the results demonstrate that the proposed method can help to localize the prostate accurately, which is feasible in clinical.

Background and Objectives: Three-dimensional (3D) printing has potential value in medical applications with increasing reports in the diagnostic assessment of cardiovascular diseases. The use of 3D printing in replicating pulmonary artery anatomy and diagnosing pulmonary embolism is very limited. The purpose of this study was to develop a 3D printed pulmonary artery model and test different computed tomography (CT) scanning protocols for determination of an optimal protocol with acceptable image quality but low radiation dose. Materials and Methods: A patient-specific 3D printed pulmonary artery model was created based on contrast-enhanced CT images in a patient with suspected pulmonary embolism. Different CT pulmonary angiography protocols consisting of 80, 100, and 120 kVp, pitch 0.7, 0.9, and 1.2 with 1 mm slice thickness, and 0.6 mm reconstruction interval were tested on the phantom. Quantitative assessment of image quality in terms of signal-to-noise ratio (SNR) was measured in the images acquired with different protocols. Measurements in pulmonary artery diameters were conducted and compared between pre- and post-3D printed images and 3D printed model. Results: The 3D printed model was found to replicate normal pulmonary artery with high accuracy. The mean difference in diameter measurements was <0.8 mm (<0.5% deviation in diameter). There was no significant difference in SNR measured between these CT protocols (P = 0.96–0.99). Radiation dose was reduced by 55% and 75% when lowering kVp from 120 to 100 and 80 kVp, without affecting image quality. Conclusions: It is feasible to produce a 3D printed pulmonary artery model with high accuracy in replicating normal anatomy. Different CT scanning protocols are successfully tested on the model with 80 kVp and pitch 0.9 being the optimal one with resultant diagnostic images but at much lower radiation dose.

Background and Objectives: The aim of this study is to investigate the application of three-dimensional (3D) visualization technique in the surgical treatment of malignant tumors of the hilar and common bile ducts. Materials and Methods: A total of 23 patients admitted from January 2015 to April 2017 for surgical treatment were analyzed, of whom 13 patients underwent medical image 3D visualization system (treatment group) while 10 underwent surgery alone (control group). Indicators to the treatment effects were recorded and compared between the two groups, including the operation time, intraoperative bleeding volume, postoperative hospitalization time, the number of dissected lymph nodes, the incidence of all postoperative complications, and the alanine transaminase (ALT), albumin (ALB), and total bilirubin (TBIL) monitored on days 1, 3, 5, and 7 after the operation. Results: In the treatment group and control group, the operation time was 194.66 ± 13.79 and 230.81 ± 27.07 min (t = 3.857, P = 0.002), the intraoperative bleeding volume was 274.28 ± 44.57 and 320.69 ± 35.90 mL (t = 2.686, P = 0.014), the postoperative hospitalization time was 11.15 ± 1.25 and 15.25 ± 1.75d (t = 6.557, P = 0.000), the number of dissected lymph nodes 10.46 ± 1.71 and 7.40 ± 0.97 (t = 5.050, P = 0.000), and the incidence of all postoperative complications 7.69% and 60% (χ² = 7.304, P = 0.019), respectively. The level of ALT and TBIL was significantly higher in the treatment group than in the control group, whereas the level of ALB was significantly lower in the treatment group than in the control group on days 3, 5, and 7 (P < 0.05). The recovery of liver function was better in the treatment group than in the control group. In addition, no perioperative deaths were found in either group. Conclusions: In the surgical treatment of malignant tumors occurring in the hilar to the common bile duct, 3D visualization technology can reduce the operation injury and intraoperative bleeding, decrease the incidence of postoperative complications, improve the safety and effectiveness of the operation, and promote the recovery of liver function, thus demonstrating promising short-term efficacy.

Background and Objectives: An magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) positioning device was developed with 3 identical Cartesian stages. The robotic system can be utilized to move a focused ultrasound transducer for performing various MR-guided applications. Materials and Methods: A single element spherically focused transducer of 4 cm diameter, focusing at 10 cm, and operating at 1.14 MHz was used during the evaluation of the robotic system. The propagation of ultrasound was either lateral or superior to inferior. MRI thermometry algorithms were developed to assess the thermal effects of MRgFUS. The proposed robotic system was developed using a three-dimensional printer. Results: The system was tested successfully in a gel phantom for various tasks (robot motion, functionality, and MR compatibility). Controlled thermal lesions were created in the gel phantom. The lesion creation was monitored successfully using MRI thermometry. Conclusions: The system was tested successfully for its functionality and its MR compatibility. This system has the potential to be used for focused ultrasound applications in the brain, breast, abdominal, and thyroid.

Background and Objectives: This study examined the learning effect of surface models made from the sectioned images of a male cadaver. Materials and Methods: The first author guided 46 medical students to study with a portable document format (PDF) file containing hundreds of surface models of a whole body. Their level of anatomy knowledge gained was evaluated by a digital examination on the tablet computers using the captured movies of PDF file. Results: The medical students' grades on the surface models were positively correlated with those on the remainder of the anatomy quiz. More than half of the students reported that the PDF file was helpful in anatomy learning and cadaver dissection. Conclusions: Digital anatomy learning is under continuous development in many ways. This report shows that surface models of the human body can be effective for self-learning and in the evaluation of anatomy knowledge.

Background and Objectives: This study describes a software application for controlling a focused ultrasound system that was guided by magnetic resonance imaging (MRI). Materials and Methods: The software's functionalities were tested using a custom-made electronic system, MRI compatible robotic systems, and a high-intensity focused ultrasound (HIFU) system. The experiments were conducted in gel phantoms to test the motion accuracy and functionality of the system. Results: The software includes the following functionalities: (a) patient database (patient identification number, age, weight, gender, etc.); (b) acquisition of MRI images; (c) transducer movement; (d) transducer coordinates; (e) ultrasound control; (f) MRI thermometry; (h) temperature measurement with thermocouple; (i) command history (command name, starting time, and remaining time); and (j) MRI compatible camera. Evaluation experiments were conducted to test the software for accuracy, functionality, and communication with MRI. Conclusions: User-friendly software was developed to control an MRI-guided HIFU system. The software was evaluated in phantom experiments and it was found to accomplish all the intended functions.

Background and Objectives: Three-dimensional (3D) printing has been increasingly used in medicine with applications in the diagnostic assessment of disease extent, medical education and training, preoperative planning, and surgical simulation. The use of 3D printing in brain tumors is very limited. In this study, we presented our preliminary experience of creating patient-specific 3D printed model of a brain tumor in a pediatric patient and demonstrated the feasibility of using 3D printing in delineating brain anatomy and tumor. Materials and Methods: A life-size 3D printed brain model of a 6-year-old girl, who was diagnosed with pilocytic astrocytoma, was generated. The model was created using high-resolution magnetic resonance images which were postprocessed and segmented to demonstrate normal anatomical structures and the tumor. The tumor was confirmed to be Grade I pilocytic astrocytoma after neurosurgery. Results: 3D printed model was found to provide realistic visualization of brain anatomical structures and tumor, and enhance understanding of pathology in relation to the surrounding structures. The mean difference in diameter measurements of the brain tumor was 0.53 mm (0.98%) between the 3D printed model and computerized model. Conclusions: This study shows it is feasible to generate a 3D printed model of brain tumor with encouraging results achieved to replicate brain anatomy and tumor. 3D printed model of brain tumor could serve as an excellent tool for preoperative planning and simulation of surgical procedures, which deserve to be investigated in further studies.

Background and Objectives: This paper evaluates the performance of a variational level set method for performing label fusion through the use of a penalty term, label fusion term, and length regularization term, which automatically labels objects of interest in biomedical images. This paper is an extension of our preliminary work in the conference paper. We mainly focus on the validation of the variational level set method. Subjects and Methods: Label fusion is achieved by combining the three terms: label fusion term, image data term, and regularization term. The curve evolution derived from the energy minimization is impacted by the three terms simultaneously to achieve optimal label fusion. Each label obtained from the nonlinear registration method is represented by a level set function whose zero level contour encloses the labeled region. In Lu et al.’s paper, they employ the level set formulation only for hippocampus segmentation. Results: Our method is compared with majority voting (MV), local weighted voting (LWV), and Simultaneous Truth and Performance Level Estimation (STAPLE). The method is evaluated on MICCAI 2012 Multi-Atlas Labeling challenge and MICCAI 2012 ventricle segmentation challenge. The mean Dice metric is computed using different atlases and produces results with 0.85 for the hippocampus, 0.77 for the amygdala, 0.87 for the caudate, 0.78 for the pallidum, 0.89 for the putamen, 0.91 for the thalamus, and 0.78 for cardiac left ventricles. Conclusions: Experimental results demonstrate that our method is robust to parameter setting and outperforms MV, LWV, and STAPLE. The image data term plays a key role in improving the segmentation accuracy. Our method can obtain satisfactory results with fewer atlases.

Background and Objectives: Cloud-based mHealth services have the potential to make quality healthcare available in remote locations in the world. A practical deployment will involve medicolegal issues involving physicians and patients in different within and across countries. However, the first step is to evaluate such a cloud-based mHealth (MyOnlineClinic). This study aimed to understand and find out the factors that influence the end-user intention to use this new technology in Australia. Materials and Methods: We surveyed 167 end-users in 2015 and performed a Structural Equation Model analysis using Smart PLS to identify the intention to use the system among the participants. Results: The study revealed that the Unified Theory of Acceptance and Use of Technology construct, particularly facilitating condition (FC) (β = 0.355, P = 0.002), has yielded a significant influence on the behavioral intention to use MyOnlineClinic. However, the relationships between performance expectancy and behavioral intention (β = 0.162, P = 0.141), effort expectancy and behavioral intention (β = −0.004, P = 0.971), and social influences and behavioral intention (β = 0.164, P = 0.100) were insignificant. Further, age showed moderating effect on these variables. The majority of the respondents agreed or strongly agreed that technological issues such as sound (92.2%), video qualities (88.6%), and interaction with doctor (89.8%) are good. Conclusion: The end-users’ intentions to use MyOnlineClinic system were particularly influenced by FCs such as hardware, software, and the information technology knowledge/familiarity of users. These factors may get further accentuated when these systems are deployed across countries with different languages, technological infrastructures, and medicolegal environments. Therefore, cloud-based mHealth would help in removing some barriers, such as differences in software versions and interoperability problems of systems at physician and patient ends.

Background and Objectives: Owing to the scarcity of health-care financing and the pressure of aging with the associated increased incidence of chronic heart failure, new models of health-care delivery supported by technology solution require a social economic analysis. We aim to assess improvement of Kansas City Living with Cardiomyopathy Questionnaire (KCCQ) score with telehome monitoring in elderly patients affected with Chronic Heart Failure (CHF) and to estimate a probable cost saving for health-care provider and patient, by calculating a probability to reduce fatal events such as mortality and hospitalization associated with improved health status measured with the KCCQ questionnaire. Materials and Methods: An observational quasi-experimental trial was used. Eight patients affected with chronic heart failure aged 85-90 years of age who have been at least three times hospitalized within the last year were recruited for the study. These patients received an educational module to empower their self-management capacity and a medicine kit necessary for telehome monitoring. The KCCQ questionnaire was employed. The KCCQ questionnaire is an independent predictor of health-care resource utilization. The KCCQ score improvement is associated likely with rehospitalization and mortality reduction according to results from previous clinical trial, where KCCQ score has been demonstrated as a strong statistically independent predictor of mortality and rehospitalization after adjustment for other variables. Results: The KCCQ score improved for 15 points from baseline measurement, after 6 months of telehome monitoring. The improvement of KCCQ score of 15 points represents a reduction of probability of hospitalization and mortality for 18% and 16%, respectively. In addition, an individual's cost savings were calculated, using the individual's willingness to pay to avoid fatal event, individual's productivity gain by avoiding a travel to remote hospital facilities, and an improved probability of positive event with telehome monitoring. Conclusion: Analysis demonstrated a probability for an important economical saving with the use of telehome monitoring for the provider and patient. We can conclude that telehome monitoring represents an innovative service that provides clinical and economical value addition to the patient, health-care system, and society.

Background and Objectives: Realistically and efficiently simulating dynamic behavior of human organs under interactions is crucial for the immersive user experience of the surgical simulator. Conventional methods are time-consuming to simulate this phenomenon due to topological modifications. Materials and Methods: This paper proposes a robust and efficient point-based framework for surgical simulation, allowing realistically simulating mechanical response of human organs under interactions with visual and tactile feedback. Considering the inevitable topological modifications occurred in surgical simulation, we adopt sparse point cloud to model the mechanics of deformable bodies while employ surface mesh to represent morphological details of human organ, which can not only disconnect mechanical complexity from geometrical details, but also enable precise boundary conditions to be solved with surface mesh. Results: We validate our method on a variety of challenging surgical scenarios, and the results demonstrate that our method can realistically and efficiently provide the visuo-haptic feedback for surgical simulation. Conclusions: Our method can well tackle the inefficiency limitation of mesh-based methods related to topological modifications issue, and has great potential to be adopted in practical surgical simulators.

Background and Objectives: Spinal cord injury (SCI) is a severe disease where the patients lost the body function below the level of lesion. Neurorehabilitative exercise leads to improvements in physical functions such as strength, range of motion, transfers, wheelchair mobility, and gait. The aim of this study is to evaluate the impact of overground gait training using an active powered exoskeleton. Materials and Methods: Patients affected of SCI admitted to our rehabilitation unit have been studied. We used an active powered exoskeleton (Ekso). Training occurred each day for 5 days a week for a total of 4 weeks. Patients were trained for at least twenty sessions, with a duration of 45–60 min each session. Patients were scored with the 6 min walking test (6MWT) before and after treatment to evaluate the movement and Ashwort scale was used to test spasticity. Psychological tests were also performed to focus on depression (Beck Depression Inventory) and on self-perception (Body Uneasiness Test-A). Results: Thirteen patients were studied (mean age 31 ± 10.4; ten males and three females), who were affected by SCI with motor complete/incomplete lesions (seven complete, six incomplete), according to the American Spinal Injury Association guidelines. All patients completed the overground gait training for all 4 weeks without collateral effects. The motor recovery evaluated with the 6MWT in incomplete motor patients described a statistical significant recovery in terms of meters and absence of rest, especially in thoracic and lumbar level lesions (48/114 m [improvement 137.5%]; 98/214 m [improvement 118.37%], P < 0.05). We did not find any difference in terms of spasticity using the Ashworth Scale. After the treatment, we found in all patients a great improvement in mood disorders and body perception. Conclusions: The overground training with the exoskeleton is a promising therapeutical approach for SCI patients, which can increase both motor and psychological aspects.

Background and Objectives: Aging society is a social health issue that digital gaming solutions can address by enabling both infrastructures as advanced environments for care and patients as active people in their aging. Cost-effective patient management may be emphasized thanks to the communication protocols that allow remote monitoring and intervention by medical professionals. Services for elderly depend on their behavior and lifestyle toward personal health management. Digital games could increase seniors' engagement and motivation. However, a few studies have looked at the acceptance of digital games by the elderly. The study here presented aims to evaluate the feasibility of a gaming rehabilitation platform. Materials and Methods: In Singapore, fifty elderly practiced 30-min sessions and evaluated their experience with a new tool based on game scenarios for rehabilitation. Results: Results are discussed in the light of Davis' Technology Acceptance Model, highlighting mainly a good perceived usefulness of the service. Conclusions: This preliminary study is encouraging the spread of digital medical games for old patients.

Background: The development of telemedicine has become a solution to provide healthcare service to the elderly while they remain in their homes. The unit of cost of healthcare service provided at home is lower than the unit of cost of Institutional Healthcare Service. The healthcare users' attitude and motivation are a fundamental factor for the acceptance of technology and behavior change. Still, motivation and attitude toward telemedicine, especially among elderly and their caregivers is not satisfactory. Objectives: The object of this study is to investigate the utilization of Telehomecare and its effect on user's attitude and motivation among caregivers of elderly population who are affected by chronic heart failure. Materials and Methods: Observational trial and quasi-experimental design with duration of 6 months were adopted. Intervention with the telemedicine platform that supports multispecialty teleconsultation and questionnaire for evaluating the effect of intervention “Use and attitude of current technology” were used. Results: The results after 6 months showed that expectations and attitude were improved, and the user's opinion about barriers was positive. Conclusion: We evaluated readiness and responsiveness of naïve user before and after 6 months during observational trial. The trial has demonstrated a unified user's opinion that the barriers to telemedicine's use are not so high that they cannot be overcome.

Background and Objectives: Lung cancer is the commonest cancer killer in the western world. Many patients have lung cancers first identified on chest radiograph (CXR). Potentially curable cancers are often missed on CXR. This study quantified the incidence of cases of lung cancer which were initially overlooked and studied the causes of delayed diagnosis. Materials and Methods: All consecutive patients discussed during a 3-month period at the local lung cancer multidisciplinary meeting (MDM) were identified. All imaging within two years prior to diagnosis of lung cancer were reviewed with its report. Any CXR examination which failed to raise the potential for lung cancer was blindly reviewed by four consultant chest radiologists. Results: 189 patients were identified from the MDM over three months. 38,049 CXRs were carried out in the trust over the same period. Of the 189 patients, 58 had previous CXRs within 2 years reported as normal. On review 27 (47%) showed an abnormality in the region of the lung subsequently shown to have cancer. 70% of lesions were central, obscured by the heart, diaphragm, clavicles or mediastinum. Conclusions: This study shows that 1 in 1,409 CXRs reported as normal harbours a visible lung cancer on retrospective review. In this group 14% of patients with lung cancer could potentially have been diagnosed earlier. Of those that had previous CXRs, 47% had abnormal CXRs reported as normal. This study qualifies the rate of missed lung cancer on CXR in clinical practice and highlights where on CXR cancers are missed.

Background and Objectives: Pediatric femoral neck fracture is a serious and disabling injury that is prone to complications. This study examined the feasibility, accuracy, and efficiency of treating the fracture through a three-dimensional (3D)-printed navigation template that was used to guide placement of cannulated screws and locking compression-pediatric hip plates (LC-PHPs). Materials and Methods: Template-guided surgeries were carried out on nine children with femoral neck fracture from 1, 2012 to 12, 2014, and the resulting data were analyzed retrospectively. From preoperative computed tomography data, a 3D model of the proximal femur and a matching navigation template were created for guiding placement of cannulated screws or LC-PHP. Finally, the template-guided operation was performed, and the outcomes were compared to those from control patients undergoing the same surgery without navigation templates (n = 10). Results: The navigation templates were found to match the individual proximal femurs well. Two to three screws were accurately inserted in the femoral neck, and the end of the fracture was successfully stabilized. Implantation of the cannulated screws or LC-PHP took an average of 13.6 and 24.5 min, respectively, whereas intraoperative X-ray was used an average of 4.2 times for the former and 5.5 times for the latter. This was compared to 37.6 and 59.6 min, and 11.4 and 15.4 X-rays, for the controls. Postoperative X-ray showed a great reduction of the femoral neck fracture. Six- to twelve-month follow-ups indicated that the fracture had healed and the function of hip joint was excellent for seven of the children and good for two (Ratliff's criteria). Conclusions: Using 3D-printed guides, accurate and effective placement of cannulated screws and LC-PHPs is realized in the femoral neck. The method reduces operation time, intraoperative bleeding, radiation exposure, and iatrogenic damage to the vasculature, femoral neck, and epiphysis.

Objective: The objective of this study was to analyze the functional brain activation in acute stroke patients during motor execution (ME) and motor imagery (MI) and to discuss the association between damaged brain structure and impaired brain function in stroke patients. Methods: The functional magnetic resonance imaging technique was used to observe activation of the brain during ME/MI of the upper limbs in 12 acute stroke patients (with the left brain damage) and 12 healthy controls. Results: During ME, the stroke patients appeared to be activated more strongly than the healthy controls in the ipsilateral primary motor areas. The MI of the affected hand in the stroke patients was not significantly different from that of the healthy hand. The nonmotor areas, the angular gyrus, and the fusiform gyrus were also activated during ME/MI. Conclusion: Structural damage in the brain is associated with the activation of brain function in acute stroke patients. Ipsilateral inhibition is reduced in stroke patients during ME and the damaged brain needs to recruit more brain areas to complete the desired action due to motion difficulties resulting from brain damage. The participation of nonmotor brain areas in ME/MI indicates that cortical reorganization may contribute to the restoration of motor function following stroke. MI can be used to improve injured brain areas, helping with the rehabilitation of stroke patients.

Background and Objectives: Electronic devices such as laptops, tablets, and smartphones are commonly used in clinical clerkships, problem-based learning, and practicals. However, there is limited literature on electronic device usage in medical lectures. This study aimed to (1) assess preclinical medical students' pattern and reason for electronic device usage in lectures and (2) assess the effect of lecture content and student factors on device usage. Materials and Methods: This was a cross-sectional study from the year 1 to 3 medical students of the Li Ka Shing Faculty of Medicine, The University of Hong Kong. The data was collected through self-administrated questionnaires. The questionnaire was distributed twice to the same cohort of students, once after their basic medical science lectures, another after humanities lectures. Categorical variables were compared by Chi-squared test or Fisher's exact test; continuous variables were compared by Mann-Whitney U-test or Kruskal-Wallis H-test. Results: Five hundred and seventy-nine valid questionnaires were collected. Students spent more time on electronic devices for learning in science lectures when compared with humanities lectures (P < 0.001). In contrast, students spent more time for nonlearning purposes in humanities lectures (P < 0.001). In science lectures, the mode of admission to medical school (P < 0.05) and year of study (P < 0.001) were factors affecting the device usage. Conclusions: Lecture content, mode of admission, and year of study have a significant impact on the electronic device usage in preclinical medical lectures. Appropriate interventions are necessary to help the students make better use of their devices and decrease the time spent on nonlearning purposes, particularly in humanities lectures.

Objective: To determine the pattern and forecast visitor accession trend of two national academic journal website: Indian Journal of Community Medicine (IJCM) and Indian Journal of Public Health (IJPH) for the period 2015-2020. Materials and Methods: The visitor accession details (number of times journal issue accessed online) for the period 2000-2014 (15 years) were collected and recorded on Microsoft Excel sheet. Time series analysis was then applied on the dataset using different forecasting models to predict the future trend of accession and value of a real dataset using R software (version 3.1). Results: Both the Indian journals are managed by independent professional bodies, but IJCM journal website was made online in 2007, 3 years ahead of IJPH (2010), leading to a very high accession (a proxy indicator for volume of readership) of IJCM during this period ranging between 100,000 and 120,000 counts, and thereafter accession was noticed to be slightly higher for IJPH than IJCM. The time series sequence showed that both had similar pattern, i.e., first stage: they have initial slow rise; second stage: sudden increasing trend from 2007 to 2010 (IJCM); and 2010 to 2012 (IJPH), respectively; and third stage: Both have then a decreasing trend with superimposed seasonal fluctuations. Future predicted accession details of IJCM and IJPH for 2015-2020 by Holt-Winter fitting model suggest stagnation with online accession of journal issue ranging from 30,360 to 31,860 counts for IJPH and 20,997 to 25,581 counts for IJCM though the range of accession for IJCM (4584) was higher than IJPH (1500), thereby reflecting that IJPH will attain stagnation earlier then IJCM. Autoregressive integrated moving average model also reflected similar results. Ljung-Box test indicated that the model was found statistically correct (P = 0.825 for IJCM and P = 0.50 (IJPH), and there was no statistically significant difference between actual values and predicted values by model. For IJCM dataset, value of R² = 0.678 means that the model could explain 67.8% of the observed variation in the series, while it was able to explain 63.3% variations in IJPH series. Conclusion: To conclude within limitations, this study provides information on pattern and trend of visitor accession of public health journal website. The information unraveled from this study may further aids in planning, strengthening publication standards along with experimentation of innovative ideas to enhance visibility, global participation with a focus on retaining and enhancing journal user base.

Background and Objectives: Patient safety in hospital is an essential professional indicator that should be noticed. The thread of fires is of the most potentially dangerous risk that could harm patients and personnel. Hence, we studied operating room staff knowledge about fires, its prevention, and control, based on their specialty and their job tenure. Materials and Methods: This is a descriptive-analytical cross-sectional study. A cluster sampling method was applied, and a quota was considered for each hospital. In each cluster, samples were selected through census method. Data were collected using a three-part questionnaire and analyzed using SPSS version 17 (SPSS, Inc, Chicago, IL, USA). Results: The mean of their knowledge level about fires and its prevention was 2.71 (0.67), and control was 2.62 (0.71). In 66% of cases, the level of knowledge about fires and its prevention, and in 70% of cases, the level of knowledge about methods of fire control have been below the average (P < 0.05). As staff age increases, their level of knowledge increases as well. Hospital they are employed by, their job tenure, and their profession can affect the level of knowledge (P < 0.05). Discussion: This study shows that the staff knowledge about fires, its prevention, and control has been lower than the average limit. Due to the sensitivity of the issue, in terms of susceptibility of the environment and medical equipment for ignition, and also the safety of staff and patients, it is necessary to make facilities for development of staff knowledge, to eliminate defects of staff training by managers, and also to consider standards.

Objective: The purpose of this study was to analyze how fat distribution in the rotator cuff interval (RCI) in normal volunteer shoulders determines the coracohumeral ligament (CHL) visualization, including the CHL visualization rate, type, and thickness, using routine magnetic resonance imaging (MRI). Materials and Methods: This study prospectively analyzed 120 shoulder joints in 60 normal volunteer individuals (30 males and 30 females) using MRI to identify the fat distribution type in the RCI as well as the CHL visualization rate, type, and thickness. Results: The fat in the RCI was visualized in 110 of 120 shoulders (91.7%) while the fat in the RCI was not identifiable in 8.3% of normal volunteer shoulders. The fat distribution in the RCI was classified into five types: Type A (52.5%), Type B (26.7%), Type C (5.8%), Type D (6.7%), and Type E (8.3%). The CHL types included the horizontal type (73.3%), upsloping type (12.5%), downsloping type (5.9%), and unseen type (8.3%) (The CHL was not identifiable in 8.3% of normal volunteer shoulders). No significant difference existed for the fat distribution types in the RCI or the CHL visualization rate, types, or thickness in either different lateral shoulders or different gender shoulders, using a Chi-square test (P > 0.05). In addition, no significant correlation emerged between body mass index (23.4 ± 2.5, n = 110) and the CHL thickness (3.1 ± 1.3 mm) in normal volunteer shoulders, using the Pearson correlation test (n = 110) (r = −0.095, P> 0.05). Conclusion: MRI is a satisfactory method for determining the fat distribution in the RCI and CHL depiction in normal volunteer shoulders. The fat distribution in the RCI determines the CHL visualization, including the CHL visualization rate, type, and thickness.

Objectives: This single-center prospective, case-controlled study investigated satisfaction and esthetic results as rated by the physician and patient, respectively, by following up thirty patients with aging face, who underwent facial autologous fat grafting with platelet-rich plasma (PRP). Materials and Methods: A retrospective review of thirty patients, who were suffering from facial sagging or partial depression and requiring autologous fat grafting between February 2012 and September 2015. Photograph was taken before and 3-month after the operation. Patient and physician satisfaction was rated using visual analog scale (VAS) ranging from 1 (least satisfied) to 10 (most satisfied) 3 months after the operation. Statistical difference between the patient and physician satisfaction scores was analyzed by SPSS 17.0 software. Results: The patients' average age was 34.5 ± 1.2 years. The average VAS score of physician satisfaction was 7.9 ± 1.0, and the average VAS score of patient satisfaction was 8.0 ± 1.2. There was no statistically significant difference between the two groups in scores (P = 0.859; P > 0.05). Conclusion: There is no evidence that different donor sites or different donor-site preparation will lead to different outcomes. Multilevel injection is recommended for autologous fat injection. The high satisfaction scores indicated a good esthetic result of facial autologous fat grafting with PRP. Autologous fat as one of the popular soft tissue fillers is durable and safe. The biggest challenge is the high variation in absorption rate. PRP may lead to higher survival rate of fat and satisfaction level. The stability of survival rate of autologous fat grafting with PRP and the connection between complications and PRP technique need further study.

Objective: To fully understand the original spatial position and three-dimensional (3D) anatomical morphology of cardiac skeleton (CS), and to quickly locate its position in patient-specific computed tomography angiography (CTA) images. Materials and Methods: First, we segmented and reconstructed 3D models of CS and its attached valves with Amira software, defined valve planes based on Chinese visible human 5 (CVH5), and then computed its geometric transformation matrix and applied them in locating the valve planes in patient-specific CTA images. Results: We reconstructed a 3D CS model based on CVH5 images which keep the original spatial position and its normal anatomical appearance. The 3D structures include aortic valve annulus (AVA), mitral valve annulus, tricuspid valve annulus, pulmonary valve annulus, and its attached valves. With the relative geometric transformation matrix, we quickly located the patient-specific valve planes that are vertical to each valve in CTA images. Conclusions: CVH5 dataset can be used in reconstructing the 3D model of CS, which is difficult for clinical images, such as CT, magnetic resonance imaging, and traditional anatomical method to achieve. Our method of 3D reconstruction presents more anatomical details than clinical images and keeps the original shape and position. We can define each valve plane on the CVH5 model and show its corresponding plane in patient-specific CTA images, which can be observed on each valve plane at the same time based on the consistent reference.

Objective: To evaluate, the feasibility and efficacy of three-dimensional (3D) digital navigation, 3D design, and 3D printing in the surgical treatment of giant tumors in thoracic cavity. Patients and Methods: A 62-year-old male patient had a giant tumor in the left thoracic cavity. The tumor constricted the left lobe with the left chest wall being involved. We performed high-precision consecutive thin-sectional computed tomography (CT) scanning and obtained the 3D model of the tumor, lung, pulmonary, tracheobronchial tree, sternum, ribs, and costal cartilage with self-developed 3D image processing software. Before surgery, we also carried out digital navigation, printed out the tumor and the chest wall that is intended to be reconstructed, and developed the surgery program for the giant tumor. At the same time, 3D chest wall titanium was produced based on 3D printing. We performed giant tumor resection and sutured the titanium plate to the chest wall of the patient to repair the chest wall defect. After surgery, we performed CT scans and 3D reconstruction in order to determine the efficacy of surgical treatment. Results: The results showed that we successfully designed the repair surgery program for chest wall defect after the tumor resection. Titanium based on the 3D printing-assisted design completely fit the chest wall defect. Blood loss was significantly reduced compared to conventional titanium suture. There were fewer postoperative complications, and patient recovery was fast. Conclusion: We conclude that 3D printing-assisted resection of tumors in the thoracic cavity and chest wall reconstruction contributes to developing surgery program and performing complex thoracic surgery, which improves the efficacy of surgery, shortens the operation time, reduces the abrasion of conventional steel implant to the residual sternum, ribs, chest wall muscle and pleura, decreases the bleeding, abnormal breathing, and achieves the developmental shift to digital and personalized cardiothoracic surgery.

Objective: Smartphones have evolved from luxury to essential need items in general population nowadays. iOS by Apple, Android by Google, Windows by Microsoft and Blackberry account for the majority of smartphone operating system which are currently in use today. Materials and Methods: The present study was done among 350 students of medical, dental, nursing and physiotherapy streams to know the prevalence of smartphone use and attitude towards its use. Of the 350 students enrolled in the study, 257 completed the questionnaire with a response rate of 73.4%. Results: Out of 222, 198 had android devices, 13 had iPhones, and 11 had other operating systems including Windows and Blackberry. 191 (74.3%) of the subjects had a working email account. Conclusion: First year students have positive perception towards smartphone use and medical schools should encourage the use of medical applications among them. However, students and medical professionals should be cautious of the negative issues with smartphone use.

Objective: Transjugular intrahepatic portacaval shunt (TIPS) is a traditional and effective treatment for variceal bleeding in cirrhotic patients with portal hypertension. However, in patients with a Budd-Chiari syndrome or other unaccessible hepatic veins, a direct puncture through the inferior caval vein may be inevitable. Direct intrahepatic portacaval shunt (DIPS) also has several advantages compared with TIPS. So we are expected to explore a digitalized model of DIPS and find the suitable shunt pathway of DIPS. Materials and Methods: We chose four hundred serial sectional images from the internal jugular vein superior margin to the edge interior hepatic from Chinese Visible Human Dataset. Surface and volume reconstruction were performed by 3D Doctor 3.5 software programs(ABLE SOFTWARE). Results: We reconstructed a digitalized model including liver and relevant vessels. It can display distribution characteristics and spatial structure relationship of intrahepatic vessels from any positions and angles. Conclusion: DIPS represents a useful addition to the endovascular techniques for managing complications of portal hypertension. The model of DIPS provides a good 3D morphological reference of image diagnostics and interventional therapy for DIPS.

Objective: To investigate the treatment effects on port-wine stains (PWSs) using the red, green, and blue (RGB) color measuring and analyzing system in combination with a personal computer. Methods: Twenty patients with PWSs were evaluated both by the RGB color measuring and analyzing system and by the experienced plastic surgeons through a blind test. Then, the two treatment effects were compared. Results: The mean treatment effect was 51.6 ± 24% by RGB method, ranging from 2% to 98%, and that of the clinician evaluation was 47.13 ± 24.6%, ranging from 15% to 90%. There was no significant difference in treatment effects as evaluated by both the clinicians and the RGB measuring and analyzing system method on average (P > 0.05). The subjective clinical grades correlated well with the treatment effects obtained by the proposed computer-assisted RGB measuring and analyzing system (correlation coefficient, 0.87). Conclusions: RGB color measure and analysis system could replace clinician for the evaluation of treatment effects on PWSs and it is an easy, objective, quantitative, and cost-effective method, and can be useful for the evaluation of treatment effects on PWSs.

Objective: To assess prevalence, usage pattern, and risk of internet addiction (IA) among undergraduate students of a health institution from Delhi. Materials and Methods: A cross-sectional descriptive study was carried out during March-April 2015 using 20-item Young's IA test, a Likert scale-based interview schedule with scores ranging from 0 to 100 points with a higher score indicating greater internet dependency. Background variables included sociodemographic details, general health practices, self-assessment of mental health status, inter-personal relation (family/friends), personality type, and global satisfaction in life. The scoring pattern was analyzed in the form of low risk (score ≤49 points) and high risk (score ≥50 points) for IA. The proportion, Chi-square test, adjusted, and un-adjusted odds ratio (OR) (95% confidence interval) were computed using regression analysis. Results: Out of 202, 40.6% were MBBS students, followed by 35.6% from nursing, and 23.8% from medical lab technology stream; 68.3% were females; the mean age was 20.3 ± 1.4 years; and 61.9% were residing in hostels. It was observed that 44 (21.8%) and 22 (10.9%) students had ever consumed alcohol and smoked, respectively, while only 42 (20.8%) were engaged in physical activity (≥30 min) during most (≥5) of the days of the week. Based on self-assessment, 33 (16.3%) were globally dissatisfied and 88 (43.6%) reported themselves to be introverts. The majority of students were using internet for educational purpose (98%), entertainment (95.0%), accessing social sites (92.5%), checking E-mails (76.2%), and pornographic websites (45%). With regard to IA, 171 (84.7%) were at low risk (score ≤49) and 31 (15.4%) were at high risk (score ≥50). Male students (P = 0.001), ever consumed alcohol (P = 0.003), ever smoker (P = 0.02), and regular physical activity (P = 0.04) were found to be significantly associated with a high risk of IA based on Chi-square test, but none were found significant at higher levels of analyses (adjusted OR). No significant association of IA was found with mental status, global satisfaction, inter-personal relationship, or personality type. Conclusion: A large majority (84.7%) of students in our study are found to be at low risk of internet addiction.

Objective: The aim was to evaluate diagnostic accuracy of 640 slice computed tomography angiography (640-CTCA) in diagnosis of coronary artery stenosis. Materials and Methods: Selective coronary angiography (SCA) and 640 slice CTCA were performed in 120 patients with suspected coronary artery disease (CAD) (78 male, 42 female, aged from 36 to 79 years old, with an average of 58.23 years). Various post-processing reconstructions of coronary arteries and branches, such as volumetric imaging, multi-planar reconstruction, curved planar reconstruction, maximum intensity projection were used. The coronary segments, with statistical evaluations combined with its diameter ≥1.5 mm were collected to analyze the diagnosis accuracy of 640-CTCA on coronary artery stenosis, with SCA as the reference standard. Results: About 96.91% (1535/1584) of coronary artery segments were evaluable arteries, and the sensitivity, specificity, positive and negative predictive value of 640-CTCA for detecting coronary artery stenosis were 93.44%, 99.59%, 95.00% and 99.45% respectively. 3.09% (49/1584) of coronary artery segments could not be evaluated due to motion artifact in 21 segments, calcification in 18 segments and poor display of lumen in 10 segments. There were no significant differences in the diagnostic accuracy of coronary artery stenosis between 640-CTCA and SCA. Conclusion: 640-CTCA has a higher accuracy and specificity, which is a reliable tool in the screening of CAD, coronary surgery, preoperative evaluation and the postoperative follow-up.

Objective: To investigate the causes for retinal artery occlusion and cerebral infarction resulting from cosmetic facial autologous fat injections. Materials and Methods: Twenty-seven retrospective, noncomparative cases with artery occlusion caused by facial autologous fat injections were included. Injection sites, basic demographic information (age, sex, and laterality of the involved eyes), best-corrected visual acuities (BVCAs), fundus fluorescein angiography, optical coherence tomography findings, brain magnetic resonance imaging, and associated ocular and systemic manifestations were collected as study information. Twenty-seven cases were classified according to artery occlusion, which led to blindness and brain infarction, as relationship between blindness and brain infarction may provide clues to help us figure out the process of arterial blockage. Results: Of the 27 cases, 13 patients had ophthalmic artery occlusion (OAO), 6 had central retinal artery occlusion (CRAO), and 3 had branch retinal artery occlusion (BRAO). Injection sites were the glabellar area (9 cases), nasolabial area (5 cases), forehead area (4 cases), periocular area (2 cases), nose area and nasal area (2 cases), multiple places (2 cases), and other areas (3 cases). Injection at different injection sites may lead to blindness, which means that emboli went into the blood by different branches of the external carotid artery, and eventually blocked the ophthalmic artery and its branches. Concomitant brain infarction developed in 13 cases with retinal artery occlusion. The high probability of occurrence of cerebral infarction indicated that internal carotid artery could be a flow path of emboli. Conclusion: Cosmetic facial autologous fat injections may cause retinal artery occlusion. Under the pressure of injection, fat emboli go through the terminal artery of face into the ophthalmic artery counter currently. In some cases, retrograde arterial embolism also causes brain infarction. Middle cerebral artery occlusion is closely associated with OAO.

Background and Objective: A smartphone is a cellular phone with an integrated computer that enables it to perform a wide array of tasks in addition to its primary purpose. Technological growth has been paralleled by a similar rise in the capabilities of modern day smartphones. And they have found their way into medical education as well as practice. iOS and Android based phones constitute the bulk of the smartphones. Together with their associated applications (apps), these devices have become an indispensable tool for the medical resident and practicing physician. The aim of this study is to make an objective assessment of the status of smartphones as a learning aid and practice tool among medical residents. Materials and Methods: The study was conducted on post-graduate trainees in the largest teaching hospital in Jammu province. The residents were approached in the hospital and requested to fill a pre-formulated questionnaire. 90 residents from different specialities were approached over a period of seven days. Results: 80% of the interviewees said they possessed a smartphone. The percentage was lower in first year trainees and highest in third year trainees. Android and iOS based phones were the devices most commonly used. 90% of those with smartphones said they used it for clinical or academic purposes in the hospital. Conclusion: A fairly large percentage of medical residents own smartphones. Most of them use these for clinical and academic purposes. Online resources and pre-installed apps are the two common resources accessed. There is a need for improving the credibility of online resources, and development of more medical apps for smartphones.

Objective: The aim was to explore image quality and radiation dose in patients with different heart rates in 640-slice volume computed tomography (CT) coronary angiography by using tube voltage of 100 kV. Materials and Methods: The 220 consecutive patients clinically suspected or confirmed of coronary artery disease were divided into three groups: 67 cases in 1 beat group (heart rate <65 bpm); 134 cases in 2 beats group (65 bpm ≤heart rate <80 bpm); 19 cases in 3 beats group (heart rate >80 bpm). When scanning was completed, the best phase for coronary arteries would be chosen. Various postprocessing reconstructions of coronary arteries and branches, such as volume reconstruction (VR), maximum density projection, multiplanar reconstruction, curved surface reconstruction, were used. We classified image quality and made statistical analysis according to 4-grades method. We also compared scalability of coronary arterial segments and radiation doses between the groups. Results: There were no significant differences in the scalability of coronary arterial segments between the groups. Effective radiation doses of the three groups were (2.5±0.8) mSv, (8.4±3.1) mSv and (11.2±3.8)mSv. The radiation doses between the groups showed statistical difference (P < 0.05). Conclusion: 640-slice volume CT can be adapted to changes during heart rate, and ensure the image quality under the condition of 100 kV, and radiation doses were significantly reduced in patients with heart rate <65 bpm.

Objective: To explore the changes of brain structural integrity in patients with posttraumatic stress disorders (PTSD) using diffusion tensor imaging (DTI). Patients and Methods: Twenty PTSD patients who underwent a traffic accident and 20 non-PTSD patients were selected from the Department of Rehabilitation, Southwest Hospital of the Third Military Medical University in Chongqing, China, between January 2007 and December 2013. Using voxel-based analysis, we investigated fractional anisotropy (FA) and mean diffusivity (MD) in PTSD patients. Linear correlation analysis was employed to detect the relationship between FA and MD in regions of interest, and to obtain PTSD Checklist-Civilian Version scores. Results: When compared with the non-PTSD group, the FA of PTSD patients significantly decreased in bilateral middle frontal gyrus, right superior frontal gyrus, and left putamen (P < 0.005). The MD of PTSD patients increased mainly in bilateral middle frontal gyrus, anterior cingulate cortex, left amygdala, left insula, and left globus pallidus (P <0.005). Pearson correlation analysis revealed that the FA value of right middle frontal cortex (MFC) had a significant negative correlation with the PTSD score (r = −0.628, P = 0.039), while the MD value of right MFC and left amygdala had a significant positive correlation with the PTSD score (r = 0.630, P = 0.047; r = 0.632, P = 0.041, respectively). Conclusion: The abnormalities of structural integrity in the amygdala and middle frontal gyrus may be the structural foundation of emotional and memory dysfunction in PTSD.