Background and Purpose: Malignant melanoma is a high-grade skin cancer with high feasibility to metastasize to both regional and distant sites when detected late. Therefore, it is crucial to diagnose this type of cancer at an early stage to ensure effective treatment. The identification of melanocytic lesions is a difficult issue, even for experienced experts. The current development of information technology, particularly related to image analysis and machine learning, is an opportunity to support the work of specialists and detect malignant melanoma more effectively. The aim of this work is to present a melanocytic skin lesion ontology (MLSO) structure, which serves as a basis for a melanoma diagnosis system and includes the formalization of the experts' and literature knowledge. Subjects and Methods: MLSO describes the most commonly used melanoma assessing strategies: Argenziano's (also known as the 7-point checklist), Menzies', and Stolz's (based on the ABCD rule) strategies as well as Chaos and Clues. Results: In this work, a case study was conducted on the description of a dermatoscopic digital image of a melanocytic skin nevus. The nevus was evaluated according to all of the strategies included in the MLSO, and inferences were made based on these strategies. The analyzed lesion was classified as a benign nevus since no malignancy was indicated by any of the applied strategies. Conclusion: Initial results indicate the usefulness of MLSO in diagnosing skin cancer. A significant advantage of MLSO is that it provides results obtained using four strategies. Therefore, the results are more objective and the possible errors may be avoided. The MLSO structure is still developing and will be implemented into an automated skin cancer diagnosis system.

Objective: To compare the dosimetric parameters of step-shoot intensity-modulated radiotherapy (sIMRT), dynamic intensity-modulated radiotherapy (dIMRT), and volume-modulated arc therapy (VMAT) in thymoma and to study the feasibility of the ArcCHECK-3DVH system in three intensity-modulated radiotherapy plans to choose a more appropriate intensity-modulated radiotherapy for thymoma. Materials and Methods: Seventeen patients with thymoma were enrolled in this study. Treatment plans of sIMRT, dIMRT, and VMAT for each patient were based on the Monaco treatment planning system (TPS). Dosimetric verification was performed via the ArcCHECK-3DVH system. We compared and analyzed the 3D γ pass rates of the TPS dose calculation and ArcCHECK-3DVH system dose reconstruction with the three gamma criteria (3 mm/3%, 2 mm/2%, and 1 mm/1%) with a threshold of 10%. Dose–volume histogram analysis was used to compare the dose parameters for target volumes, and organs at risk (OARs), such as D_98%, D_50%, D_2%, D_max, V₂₀, and V_5. Monitor units (MUs) and delivery time were also compared. Results: There were significant differences in the three intensity-modulated radiotherapy plans. For target volume, VMAT showed the highest planning target volume (PTV) D_98% and the lowest PTV D_50% compared with sIMRT or dIMRT. The PTV D_2% of VMAT was lower than that of sIMRT and higher than that of dIMRT, and VAMT demonstrated the highest conformity index and MU, lowest homogeneity index, and shortest treatment delivery time. For the OARs, VMAT is not inferior to sIMRT and dIMRT in OARs protection. For the dosimetric verification, the entire area, PTV, lungs, heart, and spinal cord of VMAT showed the highest γ pass rates than the other two techniques under the gamma 3 mm/3% criteria, which was even more pronounced when the stricter gamma criteria of 2 mm/2% and 1 mm/1% were applied. Conclusion: VMAT can be applied to radiotherapy of thymoma, and the accuracy of treatment plan execution can be guaranteed through the ArcCHECK-3DVH system.

Purpose: To clarify the diagnostic performance of reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) and compare prostate cancer (PCa) detection rates of rFOV DWI-targeted biopsy (rFOV DWI-TB) with systemic biopsy (SB). Materials and Methods: Ninety-eight consecutive patients with suspected PCa (mean prostate-specific antigen [PSA]: 17.85 ng/mL, range, 4–28 ng/mL) were prospectively enrolled in this study. All rFOV DWI data were carried out using PI-RADS V 2.0 assessment category. All patients underwent a 10-core SB and a further 2–4 cores of rFOV DWI-TB. The performance of rFOV DWI was analyzed, and the cancer detection rates between two methods were compared. Results: The sensitivity, specificity, positive predictive value, and negative predictive value for detecting PCa with rFOV DWI were 85.11%, 92.16%, 90.91%, and 87.04%, respectively. Area under curve for rFOV DWI was 0.886. In the digital rectal examination (DRE) normal and PSA ≥ 10 ng/mL subgroups, the PCa detection rates were statistically greater for rFOV DWI-TB than for SB (both P < 0.05). The mean Gleason score of cancers detected by rFOV DWI-TB was significantly higher than that detected by SB (P < 0.05). In addition, the detection rate for rFOV DWI-TB cores was significantly better than for SB cores (P < 0.001). Conclusion: RFOV DWI allowed for good diagnostic performance in patients suspected of PCa. It may be useful for clinically significant PCa detecting.

Background and Objectives: Digital heart atlases play important roles in computational cardiac simulation and medical image analysis. During the past decades, various heart anatomy models were developed, but they mostly focused on the ventricular part. Recently, a number of whole-heart atlases were developed but they rarely modelled the motion features. This study constructed a whole-heart atlas incorporating dynamic cardiac motion. Materials and Methods: The shape and motion features of the atlas were learnt from a training set of 57 dynamic computed tomographic angiography images including 20 cardiac phases. Inter-subject variations of the heart anatomy and motion were incorporated into the atlas using the statistical shape modelling approach. Clinically relevant physiological parameters (e.g., chamber volumes, ejection fraction, and percentage of systolic phase) were correlated with the shape and motion variations using the linear regression approach. The shape and motion pattern of the atlas can be adapted by adjusting the physiological parameters. Results: Quantitative experiments were conducted to measure the anatomical accuracy of the atlas for whole-heart shape reconstruction of different subjects, a mean Dice score of 0.89–0.93 and a mean surface distance of 1.02–1.91 mm were achieved for the four heart chambers, respectively. Conclusions: This atlas provides a novel computational tool with adjustable shape and motion parameters for cardiac simulation research.

Background: The gold standard for gastric cancer detection is gastric histopathological image analysis, but there are certain drawbacks in the existing histopathological detection and diagnosis. Method: In this paper, based on the study of computer-aided diagnosis (CAD) system, graph-based features are applied to gastric cancer histopathology microscopic image analysis, and a classifier is used to classify gastric cancer cells from benign cells. Firstly, image segmentation is performed. After finding the region, cell nuclei are extracted using the k-means method, the minimum spanning tree (MST) is drawn, and graph-based features of the MST are extracted. The graph-based features are then put into the classifier for classification. Result: Different segmentation methods are compared in the tissue segmentation stage, among which are Level-Set, Otsu thresholding, watershed, SegNet, U-Net and Trans-U-Net segmentation; Graph-based features, Red, Green, Blue features, Grey-Level Co-occurrence Matrix features, Histograms of Oriented Gradient features and Local Binary Patterns features are compared in the feature extraction stage; Radial Basis Function (RBF) Support Vector Machine (SVM), Linear SVM, Artificial Neural Network, Random Forests, k-NearestNeighbor, VGG16, and Inception-V3 are compared in the classifier stage. It is found that using U-Net to segment tissue areas, then extracting graph-based features, and finally using RBF SVM classifier gives the optimal results with 94.29%. Conclusion: This paper focus on a graph-based features microscopic image analysis method for gastric cancer histopathology. The final experimental data shows that our analysis method is better than other methods in classifying histopathological images of gastric cancer.

Background: Some small sample size studies have yielded slightly inconsistent results for comparing the efficacy and toxicity of trifluridine/tipiracil (TAS-102) with or without bevacizumab. This meta-analysis aims to further investigate the additive effect and safety profile of bevacizumab when combined with TAS-102 in patients receiving a salvage-line treatment for metastatic colorectal cancer (mCRC). Methods: A systematic literature search was conducted using PubMed, Web of Science, Cochrane Library, and some oncological conferences by the end of February 2021. No restrictions were placed on the searches. Two reviewers independently performed the retrieval and selection according to the “Patient, Intervention, Comparison, Outcome, Study design” principle. The outcome endpoints included overall survival (OS), progression-free survival (PFS), disease control rate (DCR), and adverse events (AEs). Results: Six controlled trials which recruited 435 refractory mCRC patients were ultimately taken in. Our results suggested that the regimen of TAS-102 plus bevacizumab had a significant advantage in OS, PFS, and DCR over TAS-102 alone (hazard ratio (HR) = 0.43, 95% confidence interval (CI): 0.27–0.67, P < 0.001; HR = 0.48, 95% CI: 0.39–0.59, P < 0.001; OR = 3.19, 95% CI: 1.56–6.50, P = 0.001; respectively). In general, the incidence of AEs was slightly but not obviously higher in the combination therapy group than the monotherapy group (OR = 1.08; 95% CI: 0.89–1.30; P = 0.458). However, the most frequent grade 3 or worse AE was neutropenia (OR = 2.32; 95% CI: 1.53–3.52; P < 0.001) which was higher in the TAS-102 plus bevacizumab group. Meanwhile, the morbidity of anemia (OR = 0.43; 95% CI: 0.22–0.83; P = 0.013) was significantly higher in TAS-102 monotherapy group. Conclusion: TAS-102 plus bevacizumab has promising activity with a manageable safety profile in a salvage-line treatment for mCRC who are refractory or intolerant to standard chemotherapy.

Digitalizing clinical trials provide an opportunity to address challenges faced in the Phase I trial settings, where near real-time data capture and data interpretation are prerequisites for iterative decision-making to rapidly adapt trial designs based on emerging insights. Although digital technologies have driven significant improvements in many businesses and organizations, the adoption of digital technologies in clinical trials has been slow. In recognition of this lag, the UpSMART consortium, a 5-year funded program (2020–2024), has been established in Europe between the UK, Spain, and Italy to embrace digital technologies and drive benefits to patients. The consortium, led by the Cancer Research UK Manchester Institute Cancer Biomarker Centre, aims to 'digitalize' Experimental Cancer Medicine Centres in the UK and Early Drug Development Units in Spain and Italy by open-sourcing and sharing digital healthcare products between participating centers across the consortium. The goal is to optimize data capture and interpretation thus accelerating Phase I clinical research to ultimately benefit patients by allowing faster access to tomorrow's medicines.

Background and Purpose: The emergence of digitalized technology has greatly promoted the progress of craniomaxillofacial and head and neck surgery. This present study aimed to explore and describe the advantages of digital design combined with personalized three-dimensional (3D) printing technology in the treatment of deep oromaxillofacial-cervical tumors. Patients and Methods: Nine patients with deep tumor of oral and maxillofacial and neck region admitted to Xinjiang Medical University Affiliated First Hospital from June 2017 to March 2021 were all treated by the digitalized surgery. Preoperatively, radiological examination including computed tomography (CT) angiography, plain and enhanced CT scan, and magnetic resonance imaging were performed in all patients. The software packaged of MIMICS, 3-matic and MAYA was cooperatively used to offer 3D modeling and create 3D texturing for morphological and functional reconstruction. The application effect was assessed by analyzing the relevant data and every patient followed up regularly after the operation. Results: The reconstructed images were acquired through computer-aided three-dimension reconstruction, as well as the navigated devices were established through 3D printing. There were totally nine patients including 4 males and 5 females with a mean age of 48.5 years old, whose tumor size ranged from 1.5 cm × 2.2 cm to 3.5 cm × 4.2 cm. The analysis of data also showed that five cases were characterized by oromaxillofacial osseous defect, 2 primary lesions were adjacent to bone and 2 were noncontacted with bone; the location of 7 cases were closely next to blood vessels of oral-maxillofacial-cervical region, while 2 were contactless. Conclusions: Although the tumors occurred in the deeply maxillofacial area are difficult to resect due to several complex anatomical and functional subunits in this area, digital design combined with 3D technology is a promising tool to provide precise diagnosis with an accurately targeted treatment for maxillofacial deep tumor. The preoperative design and the combined navigation technology can further improve the accuracy and safety for curing deep maxillofacial and neck tumors.

Background and Purpose: Lots of clinical observations have found that there is a close relationship between the pathological changes of lateral pterygoid muscle (LPM) and temporomandibular disc displacement. On medical images, unfortunately, these occult dysfunctions of LPM could scarcely be detected by naked eyes. As the presence of intrinsic properties of the human body, textural feature is capable to effectively discover the subtle functional changes of involved tissues. This study aimed to evaluate the lateral pterygoid myospasm in patients with temporomandibular joint disorders (TMD) applying magnetic resonance imaging (MRI) texture analysis. Patients and Methods: From December 2019 to October 2020, totally nine patients suffered from unilateral spasm of LPM (which is a subtype of TMD) were evaluated by MRI, who were consecutively recruited from Xinjiang Medical University Affiliated First Hospital. Gray-level co-occurrence matrix method was used to analyze the textural features of MRI T2-weighted images with the maximum area of LPM scanned at axial (closed-mouth) plane. Independent samples t-test was performed to compare the relevant parameters of bilateral LPMs (healthy- and affected-side of one individual self-controlled trial). Results: There were no statistically significant values between the two sides of angular second moment, inversed differential moment, and entropy (P > 0.05). The contrast of the healthy-side (267.983 ± 45.952) was significantly higher than that of the affected-side (210.003 ± 29.613) (P < 0.05); and the autocorrelation of the healthy-side (4.536 ± 0.819) was significantly lower than that of the affected-side (6.563 ± 1.653) (P < 0.05). Conclusion: The texture contrast and autocorrelation have certain clinical meanings of diagnosis since they could identify the altered status of LPM, and could be considered as the efficient imaging biomarkers to assess LPM changes in patients with TMD.

Background: Clear aligners (CAs) can distalize mandibular molars. The present study aimed to study the efficiency and influencing the factors of CAs for mandibular molar distalization and to provide guidance for clinical design. Materials and Methods: The present study evaluated 32 adult orthodontic patients who needed mandibular molar distalization and were treated with CAs between September 2018 and September 2020 at the school of medicine. The cone-beam computed tomography images of T₀ (before orthodontic treatment) and T₁ (after mandibular molars were fully distalized) were collected, and the actual movements of mandibular molars were measured and compared with the expected movements. The efficiency of mandibular molar distalization during treatment was comprehensively evaluated, and the relevant factors were analyzed. Results: For mandibular first molar distalization, the average efficiency of the crown was 67.19% 9swn. 13%, and that of the root was 37.87% 7stn. 72%. There was a significant difference between the achieved movement amount and the expected amount (P < 0.05). For mandibular second molars, the average efficiency of the crown was 58.47% 7swn. 07%, and that of the root was 57.03% 3stn. 48%. There was a statistically significant difference between the achieved movement amount and the expected amount (P < 0.05). There was a significant negative correlation between the expected movement and the efficiency of the crown. Conclusions: CAs can achieve mandibular molar distalization, and the movement pattern of molars is mainly a tipping movement. To accomplish bodily movement, overcorrection should be fully considered. In addition, it is suggested that close attention should be given to observing root movement during molar distalization.