|Year : 2021 | Volume
| Issue : 1 | Page : 4
Application progress and potential of digital medicine in pediatric orthopedics
Yiwei Wang1, Minjie Fan1, Qamar Zaman2, Pengfei Zheng1
1 Department of Pediatric Orthopaedics, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
2 Department of General Physician, CDA Hospital, Islamabad, Pakistan
|Date of Submission||15-May-2021|
|Date of Decision||21-Jun-2021|
|Date of Acceptance||24-Jun-2021|
|Date of Web Publication||07-Dec-2021|
Department of Pediatric Orthopaedics, Children's Hospital of Nanjing Medical University, Nanjing, 210000, Jiangsu
Source of Support: None, Conflict of Interest: None
Computer technology has undergone decades of advancement since its emergence and has been extensively used in various fields of life. Under the existing environment of rapid development of information and data technology, computer technology has also shown significant application value and application potential in medical treatment. The combination of computer technology and medicine has formed a new field described as digital medicine. This article reviews the progress in the application of digital medicine in pediatric orthopedics from the aspects of three-dimensional (3D) model reconstruction, virtual reality technology, 3D printing, artificial intelligence, robots, and biomechanical analysis by finite element method. At the same time, this paper also preliminarily discusses the advantages and disadvantages of digital medicine in the current clinical application and possible future developments.
Keywords: Artificial intelligence, Digital medicine, Pediatric orthopedics, Three-dimensional printing
|How to cite this article:|
Wang Y, Fan M, Zaman Q, Zheng P. Application progress and potential of digital medicine in pediatric orthopedics. Digit Med 2021;7:4
| Introduction|| |
In the 1950s, the third scientific and technological revolution represented by electronic computer technology started. In the past decades, computer technology has been constantly developed and has been linked with transportation, finance, industry, and other specialties and widely used, bringing many modifications and conveniences to daily life. Medicine is also significantly influenced by computer technology, and through the combination of the two, an emerging multidisciplinary applied science came into being called as digital medicine.,,, Pediatric orthopedics is a subspecialty of orthopedics. The bones of children are still growing and developing, so the diagnosis and treatment of pediatric orthopedics is considerably different from adult orthopedics and has certain difficulties. The advent of digital medicine has brought new vitality into pediatric orthopedics. From the aspects of auxiliary disease diagnosis, auxiliary optimization of surgery, guidance of postoperative rehabilitation, etc., it makes pediatric orthopedics developing to personalized and intelligent, greatly improving the diagnosis effectiveness and treatment outcome. This article reviews the improvement in the application of digital medicine in pediatric orthopedics from the aspects of three-dimensional (3D) model reconstruction, virtual reality (VR) technology, 3D printing, artificial intelligence (AI), robots, and biomechanical analysis by finite element approach.
| Three-Dimensional Model Reconstruction|| |
With the advancement of computer software and hardware technology and digital image technology, medical 3D model reconstruction technology has come into being. 3D model reconstruction technology processes the two-dimensional data of computed tomography (CT) or magnetic resonance imaging of a particular anatomical structure by computer into 3D data in the way of demonstrating, to create a 3D model.
Using the 3D model, the surgeon can clearly recognize the structure and morphology of the area, accurately locate the lesion, and make an operation plan [Figure 1]. Tam et al. reported a 6-year-old girl with a large osteochondroma arising from the scapula. The tumor restricts the movement of the joint and presses the surrounding tissue at the same time, leading to the appearance of related symptoms. To minimize the risk of surgical excision, a 3D model of the scapula was created using CT data. Then, a realistic model was prepared using 3D printer to visualize the lesion and assisted into plan the surgical removal [Figure 1]. Holt et al. reported a 10-year-old girl with Down syndrome and left acetabular dysplasia who required acetabular osteotomy. The surgeon used CT data to create a 3D model of her pelvis and left proximal femur, which not only helped the surgeon to recognize complex anatomy and increase surgical precision, but also helped the surgeon to explain surgical procedure to the family and improved the doctor–patient communication and counseling process.
|Figure 1: Athree-dimensionalmodelofa12-year-old boy'sankle varus deformity for preoperative surgical planning.|
Click here to view
3D model provides a more reliable approach for determining the parameters of anatomical structures. Pasha et al. created 3D models of the spine and pelvis for 73 children with adolescent idiopathic scoliosis. The parameters of T1-T12 kyphosis, L1-S1 lordosis, and pelvic rotation were measured in these 3D models, which were used for comparison with those measured in 2D images. The results showed that 3D measurement has higher accuracy in sagittal evaluation of adolescent idiopathic scoliosis. Westberry and Carpenter assessed the consistency and reliability of 3D models of the lower extremity created at least 1 year apart in children. The results revealed that there were insignificant anatomical differences in proximal femur and pelvic alignment between the two 3D models, and the increase in the length of femur and tibia was also consistent with normal growth, demonstrating the reliability of the 3D model in parameter measurement.
By creating a 3D model of the patient, surgeon can decide on the surgical procedure before operation to improve the accuracy and safety of the operation. Guarino et al. created 3D models of 13 children with multiplane spinal or pelvic malformation based on CT images, which were provided to their surgeons. The results revealed that 3D model could be used for preoperative planning, intraoperative estimation, and communication with patients. Storelli et al. constructed 3D models of the forearm of children with forearm deformities and performed surgical simulations to select the optimal osteotomy position and produce patient-specific cutting jigs. This method supported precise planning of complex and multiple osteotomies and lessened the need of making an intraoperative decision. The postoperative results showed that forearm rotation and distal radioulnar joint stability was improved. Caffrey et al. used 3D models for the first time to compare changes of acetabular shape and volume after different pelvic osteotomies in children, including Pemberton osteotomy, Dega osteotomy, and San Diego osteotomy. The results indicated that San Diego osteotomy increased posterior acetabular coverage and led to acetabular anteversion, while Pemberton and Dega tended to increase the anterior acetabular coverage, leading to relative acetabular retroversion. This method provides a basis for patient-specific surgical planning and osteotomy selection to attain optimal coverage in the affected hip.
3D model reconstruction technology can be used not only in bone tissue but also in soft tissue. Barzan et al. established knee models that replicate the joint motion for eight healthy children. This model can be used to predict 3D tibiofemoral and patellofemoral joint kinematics. Different from other models, this model can also study the motion of various ligaments, such as anterior cruciate ligament, posterior cruciate ligament, and medial collateral ligament. The establishment of this model has potential clinical significance. First of all, it can be used to study how the anatomy of the knee joint affects the joint function in children under pathological conditions. Second, the model can be used to study the unstable joint motion caused by different ligament injuries through data modification. It can also be used to study the changes of joint function after operation.
Nerve tissue and vascular tissue are also the application direction of 3D model reconstruction technology. Zang et al. established models for 5 patients with thumb defect who underwent thumb reconstruction with toe transplantation. The model accurately simulates the length and angle of thumb bone reconstruction and can also design suitable blood vessels and nerves for the defect area. The results show that after using the three-dimensional model, the operation time is shortened, the appearance and function of the reconstructed thumb are good, and the 3D model accurately simulates the results of the reconstruction operation. However, the subjects of this study are adults, and there is no similar study in children with amputated limb reconstruction. Due to immature development and more fragile blood vessels and nerves in children, amputated limb reconstruction surgery is more difficult. We can expect the application of 3D reconstruction technology to solve this problem to a certain extent in the future.
To sum up, the 3D model reconstruction technique can help understand the clear anatomical structures and adjacent association of the target position, which facilitates the surgeons in making surgical plans and communicating with the children and their families., In the meantime, the surgeons can simulate the operation on the 3D models to select the best possible surgical procedure and ensure surgery outcome.
| Virtual Reality|| |
VR usually refers to interactive simulations created by computer hardware and software and provide users with an environment where graphic and visual effects and sound effects resembles real-world objects and events. Its applications in the medical field include visualization of anatomical structure, surgical planning, doctor–patient communication, and medical education.
During induction of anesthesia in children undergoing elective surgery, VR can efficiently alleviate preoperative anxiety in children and their parents, to increase children's compliance and parents' satisfaction. Ryu et al. randomly divided 60 children undergoing elective surgery under general anesthesia into the VR group and the control group. The VR group watched a 4-minute video of operating room, while the control group only received counseling concerning anesthesia and surgery. Then, the degree of anxiety was assessed, and the results showed that the anxiety score of children in the VR group was suggestively lower than that of children in the control group. Park et al. arranged the children and their parents/guardians in the trial group to watch the VR video at the same time. The results revealed that the children and their parents/guardians in the trial group had lower preoperative anxiety compared with the control group, and parents' satisfaction in the trial group was considerably greater than those in the control group.
Due to its immersive abilities, VR can act as a distractor that moves participants attention from real-world stimuli to the interactive virtual world. Therefore, VR can be used in pediatrics to reduce pain and anxiety during medical treatment, which has the characteristics of innovation, nonpharmacological, easily adaptable in hospitals, easy to use, and so on., Jivraj et al. conducted a randomized controlled trial on 90 children requiring cast removal and showed that VR could significantly reduce anxiety during and after cast removal compared with the control group. May et al. conducted a three-center randomized clinical trial and indicated that compared with non-immersive video game on a tablet, immersive VR was more effective in reducing pain and anxiety during transdermal bone pins or suture removal procedures.
Simulation-based medical education has shown to improve learning effect, but its applicability and function for training in pediatrics, especially for the diseases regarding infant, is limited. Zackoff et al. created a VR course about clinical pediatrics disease and compared it with other conventional medical education methods. The results showed that VR was superior in teaching efficiency to reading, educational teaching, online learning, and low-fidelity mannequins and was as equal or improved to high-fidelity mannequins and standardized patients, but less effective than bedside teaching. VR can accurately represent real-life environments and clinical setting in a standardized format, which is conductive to the teaching and training in clinical pediatrics.
In terms of the clinic, VR can help reduce the preoperative anxiety of children, while helping surgeons to communicate with patients and increase parental satisfaction. In addition, VR distracts children's attention and reduces pain during medical treatment. In terms of teaching, VR can clearly and comprehensively display the anatomical structure and characteristics of pediatric bones, making teaching more interesting and understanding and improves teaching efficiency.
Mixed reality (MR) is the further expansion of VR technology. By presenting virtual scene information in a real scene, it builds an interactive feedback information loop among the real world, the virtual world, and the user to enhance the practicality. VR allows for surgery simulation, whereas MR allows surgeons to overlay visual digital images on the surgical field of vision, providing holographical features consistent with the real world.,, However, only a few orthopedic surgeries on the adult have tried this new technology,, and there is a lack of research on its application in pediatric orthopedic surgery. It is believed that VR and MR assisted pediatric orthopedic surgery will become a new research hotspot soon.
| Three-Dimensional Printed Personalized Aids and Surgical Navigation Templates|| |
3D printing is a technology which is based on digital model files and uses bonded materials such as powdered metal or plastic to construct objects by printing layer by layer. That is, we first build models by computer modeling software, then divide the built 3D model into layer-by-layer sections, and finally print layer by layer using a 3D printer. Hence, 3D printing is often used in combination with computer-aided design (CAD), which can convert the designed 3D digital model into a physical model. Compared with traditional models, 3D-printed models have been widely used in clinical treatment due to their benefits of personalization and precision, which are very necessary personalized treatment in pediatric orthopedics., For example, as mentioned above, computer reconstruction of 3D models is often printed using 3D printing technology for the observation and communication of doctors and patients.
3D printing technology is widely used in the fabrication of customized surgical navigation templates [Figure 2]. Zheng et al. studied the feasibility of 3D-printed navigation template in femoral osteotomy in older children with developmental dysplasia of hip (DDH) and found that compared with the control group, the 3D-printed navigation template group required less operative time, intraoperative X-ray exposure times, and incidence of iatrogenic physical injury, and postoperative follow-up showed that the 3D-printed navigation template group was better than control group regarding their therapeutic effect. In general, 3D-printed navigation template simplified the operation and improved the surgical accuracy. Hu et al. used 3D-printed navigation template for the surgical treatment of children with varus deformity of elbow. The children underwent CT scanning and printed 3D navigation template. The navigation template was used for intraoperative auxiliary accurate osteotomy and Kirschner wire fixation. The data showed that compared with the traditional surgery, the 3D-printed navigation template group had shorter operation time and better postoperative deformity correction result, while there was no major difference in elbow joint function between the two groups. These studies demonstrated the effectiveness of 3D-printed navigation templates in pediatric orthopedic operations.
|Figure 2: A case of a 10-year-old boy with genu valgus deformity. (a) The full-length X-ray film of both lower limbs shows the right knee valgus deformity. (b) Preoperative computer-aided design of osteotomy scheme. (c) Software design of osteotomy navigation template. (d) Preoperative simulation of osteotomy using 3D printing model and navigation template.|
Click here to view
In addition, 3D printing is also used in pediatric plastic surgery. Bone defects are common in children with craniofacial fissure, and such bone defects are usually very complicated. However, there are few autologous bone donors available to children. That brings a lot of difficulties to the plastic surgery of children with craniofacial fissure. Hixon et al. established a bone reconstruction model of children with craniofacial fissure and printed out specific implants by 3D-printed cryogel scaffolds technology. These cryogel scaffolds have good mechanical durability and can be an ideal stent for the treatment of craniofacial fissure defects in children. Powell et al. developed a new high-fidelity facial flap surgery simulator using CAD and 3D printing. The simulator was tested by several otorhinolaryngologists or head and neck surgeons trained in plastic surgery. The simulator has a high degree of simulation and practicality and has great potential to be widely used in plastic surgery training in otorhinolaryngology or head and neck surgery. It proves the effect of 3D printing technology on pediatric plastic surgery in another way.
Personalized aids are also the application range of 3D printing technology. The conventional aids are mass-produced by the model, so they are hard to be suitable for each different patient. 3D printing technology can perfectly solve the problem and make personalized aids according to the different needs of each patient. Zhang et al. conducted a prospective study of adolescent idiopathic scoliosis to compare the therapeutic effects of 3D-printed orthoses with traditional thoracolumbar sacral orthoses. No results have been obtained in the current experiment, but theoretically 3D-printed orthoses surpass traditional thoracolumbar sacral orthoses in terms of patient discomfort, therapeutic effect, and need of surgery.
| Artificial Intelligence|| |
AI was first proposed in the 1950s and now has developed into an applied science with a complete theoretical system, which simulates and extends human intelligence. AI can solve different problems independently by reading and learning from basic data's, mainly through machine learning especially deep learning., At present, AI has been applied in auxiliary diagnosis, cooperative surgery, and other aspects.
Sun et al. collected anterior and posterior pelvic X-ray images of 10,219 children with DDH and divided them into “dislocation” and “non-dislocation” groups. Then, 9,081 X-ray images were randomly selected for deep learning system, and the remaining 1,138 cases were used to test the effect of deep learning. The results showed that the diagnosis of DDH by deep learning system was highly consistent with that of clinicians, and the diagnosis time of deep learning system was much less than that of clinicians, which was more convenient and reliable.
Bone age assessment is another important application of AI. At present, the most common traditional evaluation methods are Greulich-Pyle method and Tanner-Whitehouse method, both of which use X-ray images of hands and wrists for evaluation. Dallora et al. conducted a meta-analysis of recent studies on the use of machine learning to evaluate bone age and found that almost all of the existing studies can automatically evaluate the bone age of children, and the research subjects are still focused on X-rays of the hands and wrists, rarely through other imaging images such as magnetic resonance imaging. For example, Lee et al. developed a deep learning system for bone age assessment, using the pre-trained convolution neural network to evaluate the test images. They found that the error of the evaluation results is rarely more than 1 year old and almost no more than 2 years old, while the evaluation time for each image is only a few seconds, which is more accurate and rapid than the usual methods. In addition, the research of Dallora et al. also found that almost all of the systems presently used are based on data from Europe and the United States, so there may be some limitations, and more data from different regions or races may be needed in the future for more comprehensive and detailed research.
AI also has many advantages in auxiliary surgery. AI can traverse for surgeons during the operation, and its accuracy can greatly reduce the error in the operation and improve the success rate and effect of the operation. Some unexpected emergencies often occur during pediatric orthopedic surgery, which often need to be judged and dealt with by surgeons in a short time. However, due to time urgency or other factors, it is sometimes difficult for surgeons to make correct choices. At this time, AI can assist in the judgment and treatment of intraoperative emergencies., However, this technique is only used in preoperative risk factor assessment and operation selection, and more research is required for the practical application of pediatric orthopedic surgery.
| Robots Assisting in Surgery|| |
Surgery is an important treatment in pediatric orthopedics, and robots are widely used in auxiliary surgery. Robot-assisted surgery can improve the stability and accuracy of operation and increase the success rate and curative effect of surgery.
Gonzalez et al. compared the accuracy of robot-assisted and traditional methods for pediatric spinal surgery. Pedicle screw fixation is an important fixation method for spinal surgery. The placement accuracy of traditional surgery is about 90.0%, while with the assistance of robot, the accuracy can be as high as 98.7%, and there are no screw fixation-related complications. Morse et al. analyzed the errors caused by robot-assisted surgery and retrospectively analyzed 19 cases of robot-assisted pediatric spinal deformity correction surgery. 194 screws were originally planned, and 168 screws were placed, of which 15 had breaches and 2 had critical breaches. Overall, 98.8% of the robot-assisted screws did not have critical breaches. Morse et al. also found that the latter 9 cases took less time to place screws with higher accuracy and fewer breaches, indicating that surgeons are still not familiar with robot-assisted surgery and should learn more and be more careful in the early stage [Table 1].
|Table 1: Breach, Abandoned Screws and Trajectory Assessment by Pedicle Characteristics for All Patients and Adolescent Idiopathic Scoliosis (AIS) Patients.|
Click here to view
In addition to improving accuracy, robot-assisted surgery also has some advantages in other aspects. Sensakovic et al. developed a low-dose CT protocol combined with robot-assisted pediatric spinal surgery. Compared with the traditional protocol, the radiation dose was reduced by 84%–91%, but there was no significant difference in imaging quality, which was sufficient for clinical use.
Generally speaking, surgical robot can assist the operator to choose the optimal surgical approach and surgical angle and ensure the surgical accuracy. We can also control the robotic arm through AI to ensure the stability of surgical operation and optimize the choice of surgical operation at the same time, to improve the clinical effect of surgery, which is also an important direction of the development of orthopedic surgery in the future. However, robots can only assist doctors in surgery now, and we look forward to the emergence of fully automatic robots for surgery in the future. In addition, at present, the cost of robot-assisted surgery is high, and not all patients have the condition to use it. There is still a long way to go before the large-scale application of surgical robots.
| Biomechanical Analysis of Finite Element Method|| |
Biomechanical analysis is one of the important objectives of pediatric orthopedic research, which can assist in the study of fracture mechanical mechanism and analyze the force of human movement under physiological and pathological conditions. Especially in recent years, finite element analysis (FEA) and gait analysis have been widely used. As a result, the biomechanical analysis of pediatric orthopedics has a new improvement.
The concept of FEA has been put forward for a long time, that is, a complex problem is divided into a limited number of simple small problems and then solved separately, and finally the solution of the complex problem is derived from these solutions, but it also has some defects such as time-consuming and large amount of calculation. The emergence of computer technology solves these problems well, making the FEA method more efficient and practical, and can be widely used.
FEA can be used to compare the efficacy of different surgical treatments. Liu et al. compared the stability of three fixation methods for distal humeral metaphyseal–diaphyseal junction fractures in children. They simulated transverse, medial oblique, and lateral oblique fractures and fixed them with Kirschner Wires (K-wires), elastic stable intramedullary nails (ESIN), and lateral external fixation system (EF), respectively. The results showed that the effect of Kirschner wire was the best for transverse fracture, EF for internal oblique fracture, and ESIN for lateral oblique fracture. The antitorsion effect of Kirschner wire was better than that of ESIN and EF in three kinds of fractures. The FEA method plays a good guiding role in providing experimental data support for the selection of treatment schemes for complex diseases which are still controversial at present.
FEA is also used to develop personalized treatment plans for patients. Zhang et al. established a finite element model of a child with DDH to study the changes of cartilage contact pressure during closed reduction and to evaluate the efficacy of closed reduction and the risk of postoperative ischemic necrosis. Gozar et al. studied a child with clubfoot deformity, established a 3D model of his foot by computer, and carried out personalized correction treatment closest to the physiological model combined with FEA. Finally, the deformity was corrected after 3 months of treatment. With the further popularization of FEA, the treatment of more diseases is bound to use FEA, and patients will enjoy more personalized treatment programs.
| Summary|| |
Nowadays, the demand for medical treatment is increasing day by day, especially the family members of pediatric orthopedic patients have higher and higher demand for medical quality. Therefore, the development of pediatric orthopedic medical technology is very necessary. Now pediatric orthopedics has begun to develop in the direction of digitalization and intelligence, and computer technology has indeed brought many changes to pediatric orthopedics. Generally speaking, the emergence of digital medicine makes pediatric orthopedics more personalized and accurate, and great changes have taken place in disease diagnosis, treatment plan formulation, or the implementation of surgery and other treatment methods in the treatment process. In the future, digital medicine still has great development potential in pediatric orthopedics, the existing technology will certainly get greater development, and more advanced technology will be seen. From the point of view of the joint use of 3D model reconstruction technology and 3D printing technology, we can expect that more digital medical technologies can be combined and used at the same time, and perhaps unexpected results can be achieved. For example, can we expect the emergence of fully automatic surgical robots after the combination of AI and robots, so that doctors can say goodbye to surgery completely? The future pediatric orthopedics will be the real “digital pediatric orthopedics.”
Financial support and sponsorship
- This study was supported by grants from Jiangsu Provincial Key Research and Development Program (BE2019608) and Young Medical Talents Project of Jiangsu Province “Strengthening Health through Science and Education” (QNRC201609).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Steinhubl SR, Topol EJ. Digital medicine, on its way to being just plain medicine. NPJ Digit Med 2018;1:20175.
The Lancet. Is digital medicine different? Lancet 2018;392:95.
The Lancet. Making sense of our digital medicine Babel. Lancet 2018;392:1487.
Topol EJ. A decade of digital medicine innovation. Sci Transl Med. 2019;11: eaaw7610.
Tam MD, Laycock SD, Bell D, Chojnowski A. 3-D printout of a DICOM file to aid surgical planning in a 6 year old patient with a large scapular osteochondroma complicating congenital diaphyseal aclasia. J Radiol Case Rep 2012;6:31-7.
Holt AM, Starosolski Z, Kan JH, Rosenfeld SB. Rapid Prototyping 3D Model in Treatment of Pediatric Hip Dysplasia: A Case Report. Iowa Orthop J 2017;37:157-62.
Pasha S, Ecker M, Deeney V. Considerations in sagittal evaluation of the scoliotic spine. Eur J Orthop Surg Traumatol 2018;28:1039-45.
Westberry DE, Carpenter AM. 3D Modeling of Lower Extremities With Biplanar Radiographs: Reliability of Measures on Subsequent Examinations. J Pediatr Orthop 2019;39:521-6.
Guarino J, Tennyson S, McCain G, Bond L, Shea K, King H. Rapid prototyping technology for surgeries of the pediatric spine and pelvis: Benefits analysis. J Pediatr Orthop 2007;27:955-60.
Storelli DA, Bauer AS, Lattanza LL, McCarroll HR Jr., The use of computer-aided design and 3-dimensional models in the treatment of forearm malunions in children. Tech Hand Up Extrem Surg 2015;19:23-6.
Caffrey JP, Jeffords ME, Farnsworth CL, Bomar JD, Upasani VV. Comparison of 3 Pediatric Pelvic Osteotomies for Acetabular Dysplasia Using Patient-specific 3D-printed Models. J Pediatr Orthop 2019;39:e159-64.
Barzan M, Modenese L, Carty CP, Maine S, Stockton CA, Sancisi N, et al.
Development and validation of subject-specific pediatric multibody knee kinematic models with ligamentous constraints. J Biomech 2019;93:194-203.
Zang CW, Zhang JL, Meng ZZ, Liu LF, Zhang WZ, Chen YX, et al.
3D Printing Technology in Planning Thumb Reconstructions with Second Toe Transplant. Orthop Surg 2017;9:215-20.
Weiss PL, Rand D, Katz N, Kizony R. Video capture virtual reality as a flexible and effective rehabilitation tool. J Neuroeng Rehabil 2004;1:12.
Chinnock C. Virtual reality in surgery and medicine. Hosp Technol Ser 1994;13:1-48.
Sutherland J, Belec J, Sheikh A, Chepelev L, Althobaity W, Chow BJW, et al.
Applying Modern Virtual and Augmented Reality Technologies to Medical Images and Models. J Digit Imaging 2019;32:38-53.
Ryu JH, Park SJ, Park JW, Kim JW, Yoo HJ, Kim TW, et al.
Randomized clinical trial of immersive virtual reality tour of the operating theatre in children before anaesthesia. Br J Surg 2017;104:1628-33.
Park JW, Nahm FS, Kim JH, Jeon YT, Ryu JH, Han SH. The Effect of Mirroring Display of Virtual Reality Tour of the Operating Theatre on Preoperative Anxiety: A Randomized Controlled Trial. IEEE J Biomed Health Inform 2019;23:2655-60.
Arane K, Behboudi A, Goldman RD. Virtual reality for pain and anxiety management in children. Can Fam Physician 2017;63:932-4.
Gold JI, Mahrer NE. Is Virtual Reality Ready for Prime Time in the Medical Space? A Randomized Control Trial of Pediatric Virtual Reality for Acute Procedural Pain Management. J Pediatr Psychol 2018;43:266-75.
Eijlers R, Utens EMWJ, Staals LM, de Nijs PFA, Berghmans JM, Wijnen RMH, et al.
Systematic Review and Meta-analysis of Virtual Reality in Pediatrics: Effects on Pain and Anxiety. Anesth Analg 2019;129:1344-53.
Le May S, Tsimicalis A, Noel M, Rainville P, Khadra C, Ballard A, et al.
Immersive virtual reality vs. non-immersive distraction for pain management of children during bone pins and sutures removal: A randomized clinical trial protocol. J Adv Nurs 2021;77:439-47.
Jivraj BA, Schaeffer E, Bone JN, Stunden C, Habib E, Jacob J, et al.
The use of virtual reality in reducing anxiety during cast removal: A randomized controlled trial. J Child Orthop 2020;14:574-80.
Zackoff MW, Real FJ, Cruse B, Davis D, Klein M. Medical Student Perspectives on the Use of Immersive Virtual Reality for Clinical Assessment Training. Acad Pediatr 2019;19:849-51.
Lohre R, Warner JJP, Athwal GS, Goel DP. The evolution of virtual reality in shoulder and elbow surgery. JSES Int 2020;4:215-23.
Verhey JT, Haglin JM, Verhey EM, Hartigan DE. Virtual, augmented, and mixed reality applications in orthopedic surgery. Int J Med Robot 2020;16:e2067.
Yoo JS, Patel DS, Hrynewycz NM, Brundage TS, Singh K. The utility of virtual reality and augmented reality in spine surgery. Ann Transl Med 2019;7:S171.
Carl B, Bopp M, Saß B, Voellger B, Nimsky C. Implementation of augmented reality support in spine surgery. Eur Spine J 2019;28:1697-711.
Wu X, Liu R, Yu J, Xu S, Yang C, Shao Z, et al.
Mixed Reality Technology-Assisted Orthopedics Surgery Navigation. Surg Innov 2018;25:304-5.
Parthasarathy J, Krishnamurthy R, Ostendorf A, Shinoka T, Krishnamurthy R. 3D printing with MRI in pediatric applications. J Magn Reson Imaging 2020;51:1641-58.
Samaila EM, Negri S, Zardini A, Bizzotto N, Maluta T, Rossignoli C, et al.
Value of three-dimensional printing of fractures in orthopaedic trauma surgery. J Int Med Res 2020;48:1-9.
Zheng P, Xu P, Yao Q, Tang K, Lou Y. 3D-printed navigation template in proximal femoral osteotomy for older children with developmental dysplasia of the hip. Sci Rep 2017;7:44993.
Hu X, Zhong M, Lou Y, Xu P, Jiang B, Mao F, et al.
Clinical application of individualized 3D-printed navigation template to children with cubitus varus deformity. J Orthop Surg Res 2020;15:111.
Hixon KR, Melvin AM, Lin AY, Hall AF, Sell SA. Cryogel scaffolds from patient-specific 3D-printed molds for personalized tissue-engineered bone regeneration in pediatric cleft-craniofacial defects. J Biomater Appl 2017;32:598-611.
Powell AR, Srinivasan S, Green G, Kim J, Zopf DA. Computer-Aided Design, 3-D-Printed Manufacturing, and Expert Validation of a High-fidelity Facial Flap Surgical Simulator. JAMA Facial Plast Surg 2019;21:327-31.
Choo YJ, Boudier-Revéret M, Chang MC. 3D printing technology applied to orthosis manufacturing: Narrative review. Ann Palliat Med 2020;9:4262-70.
Zhang Y, Liang J, Xu N, Zeng L, Du C, Du Y, et al.
3D-printed brace in the treatment of adolescent idiopathic scoliosis: A study protocol of a prospective randomised controlled trial. BMJ Open 2020;10:e038373.
Fogel AL, Kvedar JC. Artificial intelligence powers digital medicine. NPJ Digit Med 2018;1:5.
Handelman GS, Kok HK, Chandra RV, Razavi AH, Lee MJ, Asadi H. eDoctor: Machine learning and the future of medicine. J Intern Med 2018;284:603-19.
Lee H, Park G, Lee KS, Jin H, Chun KJ, Kim JH. Knowledge, Adherence to Lifestyle Recommendations, and Quality of Life Among Koreans With Heart Failure. J Cardiovasc Pharmacol Ther 2020;25:324-31.
Zhang SC, Sun J, Liu CB, Fang JH, Xie HT, Ning B. Clinical application of artificial intelligence-assisted diagnosis using anteroposterior pelvic radiographs in children with developmental dysplasia of the hip. Bone Joint J 2020;102-B:1574-81.
Bian Z, Guo Y, Lyu X, Yang Z, Cheung JPY. Relationship between hand and wrist bone age assessment methods. Medicine (Baltimore) 2020;99:e22392.
Dallora AL, Anderberg P, Kvist O, Mendes E, Diaz Ruiz S, Sanmartin Berglund J. Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis. PLoS One 2019;14:e0220242.
Lee H, Tajmir S, Lee J, Zissen M, Yeshiwas BA, Alkasab TK, et al.
Fully Automated Deep Learning System for Bone Age Assessment. J Digit Imaging 2017;30:427-41.
Gödeke J, Muensterer O, Rohleder S. [Artificial intelligence in pediatric surgery: Present and future]. Chirurg 2020;91:222-8.
Tjardes T, Heller RA, Pförringer D, Lohmann R, Back DA, AG Digitalisierung der DGOU. [Artificial intelligence in orthopedics and trauma surgery]. Chirurg 2020;91:201-5.
Gonzalez D, Ghessese S, Cook D, Hedequist D. Initial intraoperative experience with robotic-assisted pedicle screw placement with stealth navigation in pediatric spine deformity: an evaluation of the first 40 cases. J Robot Surg 2020;3:1-7.
Morse KW, Heath M, Avrumova F, Defrancesco C, Fabricant PD, Lebl DR, et al. Comprehensive Error Analysis for Robotic-assisted Placement of Pedicle Screws in Pediatric Spinal Deformity: The Initial Learning Curve. J Pediatr Orthop. 2021; 40: pp. e524-32.
Sensakovic WF, O'Dell MC, Agha A, Woo R, Varich L. CT Radiation Dose Reduction in Robot-assisted Pediatric Spinal Surgery. Spine (Phila Pa 1976) 2017;42:E417-24.
Liu C, Kamara A, Liu T, Yan Y, Wang E. Mechanical stability study of three techniques used in the fixation of transverse and oblique metaphyseal-diaphyseal junction fractures of the distal humerus in children: A finite element analysis. J Orthop Surg Res 2020;15:34.
Zhang Z, Sui D, Qin H, Li H, Zhang Z. Contact pressure distribution of the hip joint during closed reduction of developmental dysplasia of the hip: A patient-specific finite element analysis. BMC Musculoskelet Disord 2020;21:600.
Gozar H, Derzsi Z, Chira A, Nagy Ö, Benedek T. Finite-element-based 3D computer modeling for personalized treatment planning in clubfoot deformity: Case report with technique description. Medicine (Baltimore) 2018;97:e11021.
[Figure 1], [Figure 2]