Abstract:Introduction
This study aimed to evaluate whether it is useful for junior physicians to use a three‐dimensional (3D) kidney model when evaluating the R.E.N.A.L. nephrometry score.
Materials and Methods
An expert and four urology residents retrospectively evaluated the R.E.N.A.L. nephrometry scores of 64 renal tumors (62 patients) that underwent robot‐assisted partial nephrectomy at our hospital. The expert evaluated 64 R.E.N.A.L. nephrometry scores with computed tomography (CT), whereas four residents evaluate… Show more
“…In navigation for PN, these models have been used for preoperative training and surgical simulations, with reports indicating significantly less blood loss compared to when navigation was not performed [17] . There have also been reports of a significant decrease in warm ischemia time when 3D printed models were employed for preoperative planning and intraoperative navigation [18] . In addition, it has been reported that they are not only useful for patient education but also for resident education, and they are beneficial in achieving the trifecta during the initial implementation of RAPN [19,20] .…”
Partial nephrectomy, a standard treatment for small renal cancers, has evolved through minimally invasive procedures such as laparoscopic and robot-assisted partial nephrectomy. The use of three-dimensional (3D) kidney models derived from preoperative computed tomography (CT) images has been investigated to improve surgical outcomes. This review explores various navigation techniques, such as 3D printing, virtual reality (VR), and augmented reality (AR), to address organ movement and deformation challenges during surgery. Despite the promising positive impact of these methods, as revealed by a systematic review in 2022, achieving the desired navigation accuracy remains elusive. The use of Virtual Reality and Augmented Reality, capable of overlaying the 3D model onto the surgical image in real-time, has shown potential. Still, we need advanced techniques, for instance, non-rigid 3D models employing nonlinear parametric deformation, to adapt to organ deformation. Additionally, the application of deep learning from artificial intelligence for high accuracy 3D navigation is an emerging area of interest. Although considerable progress has been achieved, a comprehensive, widely adoptable solution has yet to be discovered. The paper underscores the necessity for ongoing research and development in 3D navigation methods, anticipating their substantial contribution to future surgical procedures.
“…In navigation for PN, these models have been used for preoperative training and surgical simulations, with reports indicating significantly less blood loss compared to when navigation was not performed [17] . There have also been reports of a significant decrease in warm ischemia time when 3D printed models were employed for preoperative planning and intraoperative navigation [18] . In addition, it has been reported that they are not only useful for patient education but also for resident education, and they are beneficial in achieving the trifecta during the initial implementation of RAPN [19,20] .…”
Partial nephrectomy, a standard treatment for small renal cancers, has evolved through minimally invasive procedures such as laparoscopic and robot-assisted partial nephrectomy. The use of three-dimensional (3D) kidney models derived from preoperative computed tomography (CT) images has been investigated to improve surgical outcomes. This review explores various navigation techniques, such as 3D printing, virtual reality (VR), and augmented reality (AR), to address organ movement and deformation challenges during surgery. Despite the promising positive impact of these methods, as revealed by a systematic review in 2022, achieving the desired navigation accuracy remains elusive. The use of Virtual Reality and Augmented Reality, capable of overlaying the 3D model onto the surgical image in real-time, has shown potential. Still, we need advanced techniques, for instance, non-rigid 3D models employing nonlinear parametric deformation, to adapt to organ deformation. Additionally, the application of deep learning from artificial intelligence for high accuracy 3D navigation is an emerging area of interest. Although considerable progress has been achieved, a comprehensive, widely adoptable solution has yet to be discovered. The paper underscores the necessity for ongoing research and development in 3D navigation methods, anticipating their substantial contribution to future surgical procedures.
“…However, the use of 3D printing models provides a noninvasive environment for residents to gain valuable training and accumulate experience. Yamazaki et al 109 had four residents retrospectively assess R.E.N.A.L scores in 64 patients with renal tumors who underwent robot-assisted partial nephrectomy. Thirty-two patients were evaluated using CT alone, and the rest were evaluated using CT and 3D renal models, suggesting that the accuracy of R.E.N.A.L renal measurement scores of 3D models and CT was significantly higher than that of CT alone.…”
Additive manufacturing, commonly known as 3D printing, is a rapidly advancing technology with the capability to create intricate and precise structures. This technology has garnered significant attention in the medical field due to its ability to provide personalized diagnosis and treatment services. It finds applications in various areas, such as model printing, customized implants, and even organ printing. This review delves into the current uses of 3D printing in urology, including preoperative planning for surgeries, medical education, doctor− patient communication, and implant development. It also showcases examples of its utilization in both research and clinical settings. Moreover, the exploration of 3D printing for urethral repair and urinary organ reconstruction offers tailored solutions and the potential to replace conventional tissue engineering methods. The article provides an overview of the current applications of 3D printing technology in urology and discusses future prospects.
“…The application of 3DP models bridges the gap between two-dimensional (2D) imaging and realistic anatomy, as it accurately reproduces anatomical structures and pathologies, thereby providing more tangible information than conventional imaging data [ 19 ]. 3DP models also appear to be a significantly more useful and cost-effective technique than traditional cadaveric models in medical education [ 20 ], such as those used in undergraduate dentistry training [ 4 ], urology residents [ 21 ], first-year medical students [ 22 ], craniofacial traumas [ 23 ], oral and cranio-maxillofacial surgery [ 24 ]. However, recent SBME changes regarding 3DP models have focused only on undergraduate medical education [ 25 ].…”
Background
Simulation-based medical education (SBME) and three-dimensional printed (3DP) models are increasingly used in continuing medical education and clinical training. However, our understanding of their role and value in improving trainees’ understanding of the anatomical and surgical procedures associated with liver surgery remains limited. Furthermore, gender bias is also a potential factor in the evaluation of medical education. Therefore, the aim of this study was to evaluate the educational benefits trainees receive from the use of novel 3DP liver models while considering trainees’ experience and gender.
Methods
Full-sized 3DP liver models were developed and printed using transparent material based on anonymous CT scans. We used printed 3D models and conventional 2D CT scans of the liver to investigate thirty trainees with various levels of experience and different genders in the context of both small group teaching and formative assessment. We adopted a mixed methods approach involving both questionnaires and focus groups to collect the views of different trainees and monitors to assess trainees’ educational benefits and perceptions after progressing through different training programs. We used Objective Structured Clinical Examination (OSCE) and Likert scales to support thematic analysis of the responses to the questionnaires by trainees and monitors, respectively. Descriptive analyses were conducted using SPSS statistical software version 21.0.
Results
Overall, a 3DP model of the liver is of great significance for improving trainees’ understanding of surgical procedures and cooperation during operation. After viewing the personalized full-sized 3DP liver model, all trainees at the various levels exhibited significant improvements in their understanding of the key points of surgery (p < 0.05), especially regarding the planned surgical procedure and key details of the surgical procedures. More importantly, the trainees exhibited higher levels of satisfaction and self-confidence during the operation regardless of gender. However, with regard to gender, the results showed that the improvement of male trainees after training with the 3DP liver model was more significant than that of female trainees in understanding and cooperation during the surgical procedure, while no such trend was found with regard to their understanding of the base knowledge.
Conclusion
Trainees and monitors agreed that the use of 3DP liver models was acceptable. The improvement of the learning effect for practical skills and theoretical understanding after training with the 3DP liver models was significant. This study also indicated that training with personalized 3DP liver models can improve all trainees’ presurgical understanding of liver tumours and surgery and males show more advantage in understanding and cooperation during the surgical procedure as compared to females. Full-sized realistic 3DP models of the liver are an effective auxiliary teaching tool for SBME teaching in Chinese continuing medical education.
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