The Use of 3-Dimensional, Virtual Reality Models for Surgical Planning of Robotic Partial Nephrectomy

Visual extended reality tools in image-guided surgery in urology: a systematic review

PURPOSE

The aim of this systematic review is to assess the clinical implications of employing various Extended Reality (XR) tools for image guidance in urological surgery.

METHODS

In June 2023, a systematic electronic literature search was conducted using the Medline database (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy was designed based on the PICO (Patients, Intervention, Comparison, Outcome) criteria. Study protocol was registered on PROSPERO (registry number CRD42023449025). We incorporated retrospective and prospective comparative studies, along with single-arm studies, which provided information on the use of XR, Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) in urological surgical procedures. Studies that were not written in English, non-original investigations, and those involving experimental research on animals or cadavers were excluded from our analysis. The quality assessment of comparative and cohort studies was conducted utilizing the Newcastle-Ottawa scale, whilst for randomized controlled trials (RCTs), the Jadad scale was adopted. The level of evidence for each study was determined based on the guidelines provided by the Oxford Centre for Evidence-Based Medicine.

RESULTS

The initial electronic search yielded 1,803 papers after removing duplicates. Among these, 58 publications underwent a comprehensive review, leading to the inclusion of 40 studies that met the specified criteria for analysis. 11, 20 and 9 studies tested XR on prostate cancer, kidney cancer and miscellaneous, including bladder cancer and lithiasis surgeries, respectively. Focusing on the different technologies 20, 15 and 5 explored the potential of VR, AR and MR. The majority of the included studies (i.e., 22) were prospective non-randomized, whilst 7 and 11 were RCT and retrospective studies respectively. The included studies that revealed how these new tools can be useful both in preoperative and intraoperative setting for a tailored surgical approach.

CONCLUSIONS

AR, VR and MR techniques have emerged as highly effective new tools for image-guided surgery, especially for urologic oncology. Nevertheless, the complete clinical advantages of these innovations are still in the process of evaluation.

Intraoperative image-guidance during robotic surgery: is there clinical evidence of enhanced patient outcomes?

BACKGROUND

To date, the benefit of image guidance during robot-assisted surgery (IGS) is an object of debate. The current study aims to address the quality of the contemporary body of literature concerning IGS in robotic surgery throughout different surgical specialties.

METHODS

A systematic review of all English-language articles on IGS, from January 2013 to March 2023, was conducted using PubMed, Cochrane library's Central, EMBASE, MEDLINE, and Scopus databases. Comparative studies that tested performance of IGS vs control were included for the quantitative synthesis, which addressed outcomes analyzed in at least three studies: operative time, length of stay, blood loss, surgical margins, complications, number of nodal retrievals, metastatic nodes, ischemia time, and renal function loss. Bias-corrected ratio of means (ROM) and bias-corrected odds ratio (OR) compared continuous and dichotomous variables, respectively. Subgroup analyses according to guidance type (i.e., 3D virtual reality vs ultrasound vs near-infrared fluoresce) were performed.

RESULTS

Twenty-nine studies, based on 11 surgical procedures of three specialties (general surgery, gynecology, urology), were included in the quantitative synthesis. IGS was associated with 12% reduction in length of stay (ROM 0.88; p = 0.03) and 13% reduction in blood loss (ROM 0.87; p = 0.03) but did not affect operative time (ROM 1.00; p = 0.9), or complications (OR 0.93; p = 0.4). IGS was associated with an estimated 44% increase in mean number of removed nodes (ROM 1.44; p < 0.001), and a significantly higher rate of metastatic nodal disease (OR 1.82; p < 0.001), as well as a significantly lower rate of positive surgical margins (OR 0.62; p < 0.001). In nephron sparing surgery, IGS significantly decreased renal function loss (ROM 0.37; p = 0.002).

CONCLUSIONS

Robot-assisted surgery benefits from image guidance, especially in terms of pathologic outcomes, namely higher detection of metastatic nodes and lower surgical margins. Moreover, IGS enhances renal function preservation and lowers surgical blood loss.

Three-dimensional computed tomography-based resection process map for robot-assisted partial nephrectomy: propensity score matching of a single-center retrospective study

BACKGROUND AND OBJECTIVES

We aimed to examine the effect of preoperative three-dimensional (3D) computed tomography (CT)-based resection process map (RPM) imaging on the outcomes of robot-assisted partial nephrectomy (RAPN).

METHODS

We retrospectively analyzed 177 patients (RPM group, n = 92; non-RPM group, n = 85) who underwent this surgery between November 2012 and April 2022. Patient-specific contrast-enhanced CT images were used to construct an RPM, a 3D representation of the kidney showing the planned tumor resection and a 5 mm safety margin. Outcome analyses were performed using propensity score matching. The primary endpoint was the trifecta achievement rate.

RESULTS

We extracted 90 cases. The trifecta achievement rate showed no significant differences between the RPM (73.3%) and non-RPM groups (73.3%). However, the RPM group had fewer Grade 3 and higher complications (0.0% vs. 13.3%, p = 0.026). The da Vinci Xi (OR 3.38, p = 0.016) and tumor diameter (OR 0.95, p = 0.013) were independent factors affecting trifecta achievement in multivariate analysis. Using RPM imaging was associated with the absence of Grade 3 and higher perioperative complications (OR 5.33, p = 0.036) in univariate analysis.

CONCLUSIONS

Using preoperative 3D CT-based RPM images before RAPN may not affect trifecta achievement, but may reduce serious complication occurrence by providing detailed information on tumor resection.

Patient-specific simulations and navigation systems for partial nephrectomy

Partial nephrectomy (PN) is the standard treatment for T1 renal cell carcinoma. PN is affected more by surgical variations and requires greater surgical experience than radical nephrectomy. Patient-specific simulations and navigation systems may help to reduce the surgical experience required for PN. Recent advances in three-dimensional (3D) virtual reality (VR) imaging and 3D printing technology have allowed accurate patient-specific simulations and navigation systems. We reviewed previous studies about patient-specific simulations and navigation systems for PN. Recently, image reconstruction technology has developed, and commercial software that converts two-dimensional images into 3D images has become available. Many urologists are now able to view 3DVR images when preparing for PN. Surgical simulations based on 3DVR images can change surgical plans and improve surgical outcomes, and are useful during patient consultations. Patient-specific simulators that are capable of simulating surgical procedures, the gold-standard form of patient-specific simulations, have also been reported. Besides VR, 3D printing is also useful for understanding patient-specific information. Some studies have reported simulation and navigation systems for PN based on solid 3D models. Patient-specific simulations are a form of preoperative preparation, whereas patient-specific navigation is used intraoperatively. Navigation-assisted PN procedures using 3DVR images have become increasingly common, especially in robotic surgery. Some studies found that these systems produced improvements in surgical outcomes. Once its accuracy has been confirmed, it is hoped that this technology will spread further and become more generalized.

Editorial by Reza Mehrazin and Shirin Razdan on p. 388-389 of this issue: Can preoperative planning using IRIS™ three-dimensional anatomical virtual models predict operative findings during robot-assisted partial nephrectomy?

Objective

To evaluate the predictive validity of IRIS™ (Intuitive Surgical®, Sunnyvale, CA, USA) as a planning tool for robot-assisted partial nephrectomy (RAPN) by assessing the degree of overlap with intraoperative execution.

Methods

Thirty-one patients scheduled for RAPN by four experienced urologists were enrolled in a prospective study. Prior to surgery, urologists reviewed the IRIS™ three-dimensional model on an iphone Operating System (iOS) app and completed a questionnaire outlining their surgical plan including surgical approach, and ischemia technique as well as confidence in executing this plan. Postoperatively, questionnaires assessing the procedural approach, clinical utility, efficiency, and effectiveness of IRIS™ were completed. The degree of overlap between the preoperative and intraoperative questionnaires and between the planned approach and actual execution of the procedure was analyzed. Questionnaires were answered on a 5-point Likert scale and scores of 4 or greater were considered positive.

Results

Mean age was 65.1 years with a mean tumor size of 27.7 mm (interquartile range 17.5-44.0 mm). Hilar tumors consisted of 32.3%; 48.4% of patients had R.E.N.A.L. nephrometry scores of 7-9. On preoperative questionnaires, the surgeons reported that in 67.7% cases they were confident that they can perform the procedure successfully, and on intraoperative questionnaires, the surgeons reported that in 96.8% cases IRIS™ helped achieve good spatial sensation of the anatomy. There was a high degree of overlap between preoperative and intraoperative questionnaires for the surgical approach, interpreting anatomical details and clinical utility. When comparing plans for selective or off-clamp, the preoperative plan was executed in 90.0% of cases intraoperatively.

Conclusion

A high degree of overlap between the preoperative surgical approach and intraoperative RAPN execution was found using IRIS™. This is the first study to evaluate the predictive accuracy of IRIS™ during RAPN by comparing preoperative plan and intraoperative execution.

Artificial Intelligence in Surgical Training for Kidney Cancer: A Systematic Review of the Literature

The prevalence of renal cell carcinoma (RCC) is increasing due to advanced imaging techniques. Surgical resection is the standard treatment, involving complex radical and partial nephrectomy procedures that demand extensive training and planning. Furthermore, artificial intelligence (AI) can potentially aid the training process in the field of kidney cancer. This review explores how artificial intelligence (AI) can create a framework for kidney cancer surgery to address training difficulties. Following PRISMA 2020 criteria, an exhaustive search of PubMed and SCOPUS databases was conducted without any filters or restrictions. Inclusion criteria encompassed original English articles focusing on AI's role in kidney cancer surgical training. On the other hand, all non-original articles and articles published in any language other than English were excluded. Two independent reviewers assessed the articles, with a third party settling any disagreement. Study specifics, AI tools, methodologies, endpoints, and outcomes were extracted by the same authors. The Oxford Center for Evidence-Based Medicine's evidence levels were employed to assess the studies. Out of 468 identified records, 14 eligible studies were selected. Potential AI applications in kidney cancer surgical training include analyzing surgical workflow, annotating instruments, identifying tissues, and 3D reconstruction. AI is capable of appraising surgical skills, including the identification of procedural steps and instrument tracking. While AI and augmented reality (AR) enhance training, challenges persist in real-time tracking and registration. The utilization of AI-driven 3D reconstruction proves beneficial for intraoperative guidance and preoperative preparation. Artificial intelligence (AI) shows potential for advancing surgical training by providing unbiased evaluations, personalized feedback, and enhanced learning processes. Yet challenges such as consistent metric measurement, ethical concerns, and data privacy must be addressed. The integration of AI into kidney cancer surgical training offers solutions to training difficulties and a boost to surgical education. However, to fully harness its potential, additional studies are imperative.

Immersive Virtual Reality for Patient-Specific Preoperative Planning: A Systematic Review

Background. Immersive virtual reality (iVR) facilitates surgical decision-making by enabling surgeons to interact with complex anatomic structures in realistic 3-dimensional environments. With emerging interest in its applications, its effects on patients and providers should be clarified. This systematic review examines the current literature on iVR for patient-specific preoperative planning. Materials and Methods. A literature search was performed on five databases for publications from January 1, 2000 through March 21, 2021. Primary studies on the use of iVR simulators by surgeons at any level of training for patient-specific preoperative planning were eligible. Two reviewers independently screened titles, abstracts, and full texts, extracted data, and assessed quality using the Quality Assessment Tool for Studies with Diverse Designs (QATSDD). Results were qualitatively synthesized, and descriptive statistics were calculated. Results. The systematic search yielded 2,555 studies in total, with 24 full-texts subsequently included for qualitative synthesis, representing 264 medical personnel and 460 patients. Neurosurgery was the most frequently represented discipline (10/24; 42%). Preoperative iVR did not significantly improve patient-specific outcomes of operative time, blood loss, complications, and length of stay, but may decrease fluoroscopy time. In contrast, iVR improved surgeon-specific outcomes of surgical strategy, anatomy visualization, and confidence. Validity, reliability, and feasibility of patient-specific iVR models were assessed. The mean QATSDD score of included studies was 32.9%. Conclusions. Immersive VR improves surgeon experiences of preoperative planning, with minimal evidence for impact on short-term patient outcomes. Future work should focus on high-quality studies investigating long-term patient outcomes, and utility of preoperative iVR for trainees.

Three-dimensional Model-assisted Minimally Invasive Partial Nephrectomy: A Systematic Review with Meta-analysis of Comparative Studies

CONTEXT

Use of three-dimensional (3D) guidance for nephron-sparing surgery (NSS) has increased in popularity, especially for laparoscopic and robotic approaches. Different 3D visualization modalities have been developed as promising new tools for surgical planning and intraoperative navigation.

OBJECTIVES

To summarize and evaluate the impact of 3D models on minimally invasive NSS in terms of perioperative, functional, and oncological outcomes.

EVIDENCE ACQUISITION

A systematic literature search was conducted in December 2021 using the Medline (PubMed), Embase (Ovid), Scopus, and Web of Science databases. The protocol was registered on PROSPERO (CRD42022300948). The search strategy used the PICOS (Population, Intervention, Comparison, Outcome, Study design) criteria and article selection was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias and the quality of the articles included were assessed. A dedicated data extraction form was used to collect the data of interest. Meta-analysis was performed using the Mantel-Haenszel method for binary outcomes, with results summarized as the odds ratio (OR), and the inverse variance method for continuous data, with results reported as the mean difference (MD). All effect estimates are reported with the 95% confidence interval (CI) and p ≤ 0.05 was considered statistically significant. All analyses were performed using R software and the meta package.

EVIDENCE SYNTHESIS

The initial electronic search identified 450 papers, of which 17 met the inclusion criteria and were included in the analysis. Use of 3D technology led to a significant reduction in the global ischemia rate (OR 0.22, 95% CI 0.07-0.76; p = 0.02) and facilitated more frequent enucleation (OR 2.54, 95% CI 1.36-4.74; p < 0.01) and less frequent opening of the collecting system (OR 0.36, 95% CI 0.15-0.89; p = 0.03) and was associated with less blood loss (MD 23.1 ml, 95% CI 31.8-14.4; p < 0.01). 3D guidance for NSS was associated with a significant reduction in the transfusion rate (OR 0.20, 95% CI 0.07-0.56; p < 0.01). There were no significant differences in rates of conversion to radical nephrectomy, minor and major complications, change in glomerular filtration rate, or surgical margins (all p > 0.05).

CONCLUSIONS

3D guidance for NSS is associated with lower rates of detriment and surgical injury to the kidney. Specifically, a lower amount of nontumor renal parenchyma is exposed to ischemia or sacrificed during resection, and opening of the collecting system is less frequent. However, use of 3D technology does not lead to significant improvements in oncological or functional outcomes.

PATIENT SUMMARY

We reviewed the use of three-dimensional tools for minimally invasive surgery for partial removal of the kidney in patients with kidney cancer. The evidence suggests that these tools have benefits during surgery, but do not lead to significant improvements in cancer control or functional outcomes for patients.

Systematic Review of Comparative Studies of 3D Models for Preoperative Planning in Minimally Invasive Partial Nephrectomy

Background: The employment of 3-dimensional (3D) virtual models of the organs and tumors, obtained from conventional 2-dimensional (2D) imaging (i.e. computed tomography scan and magnetic resonance imaging) have already demonstrated an outstanding potential in urology, especially in renal surgery. Objectives: The aim of this systematic review is to provide an updated focus on the results obtained from the preoperative employment of 3D virtual imaging reconstructions in nephron sparing oncological surgery. Methods: A systematic literature search was conducted in April 2022 using Medline (via PubMed), Embase (via Ovid), Scopus, and Web of Science. The search strategy used PICO criteria and article selection was conducted in accordance with the PRISMA guidelines. The risk of bias and the quality of the articles included were assessed. A dedicated data extraction form was used to collect the data of interest. Results: The initial electronic search identified 471 papers, of which 13 ultimately met the inclusion criteria and were included in the review. 11 studies reported outcomes of virtual models, 2 studies focused on printed 3D models. In these studies, the application of 3D models for preoperative planning has been reported to increase the selective clamping rate and reducing the opening of collecting system, blood loss and loss of renal function. Conclusions: 3D virtual models seem to provide some surgical benefits for preoperative planning especially for complex renal masses. In the next future the continuous evolution of this technology may further increase its field of application and its potential clinical benefit.

Clinical experience of using virtual 3D modelling for pre and intraoperative guidance during robotic-assisted partial nephrectomy

Objective:

Surgical planning for robotic-assisted partial nephrectomy is widely performed using two-dimensional computed tomography images. It is unclear to what extent two-dimensional images fully simulate surgical anatomy and case complexity. To overcome these limitations, software has been developed to reconstruct three-dimensional models from computed tomography data. We present the results of a feasibility study, to explore the role and practicality of virtual three-dimensional modelling (by Innersight Labs) in the context of surgical utility for preoperative and intraoperative use, as well as improving patient involvement.

Methods:

A prospective study was conducted on patients undergoing robotic-assisted partial nephrectomy at our high volume kidney cancer centre. Approval from a research ethics committee was obtained. Patient demographics and tumour characteristics were collected. Surgical outcome measures were recorded. The value of the three-dimensional model to the surgeon and patient was assessed using a survey. The prospective cohort was compared against a retrospective cohort and cases were individually matched using RENAL (radius, exophytic/endophytic, nearness to collecting system or sinus, anterior/posterior, location relative to polar lines) scores.

Results:

This study included 22 patients. Three-dimensional modelling was found to be safe for this prospective cohort and resulted in good surgical outcome measures. The mean (standard deviation) console time was 158.6 (35) min and warm ischaemia time was 17.3 (6.3) min. The median (interquartile range) estimated blood loss was 125 (50–237.5) ml. Two procedures were converted to radical nephrectomy due to the risk of positive margins during resection. The median (interquartile range) length of stay was 2 (2–3) days. No postoperative complications were noted and all patients had negative surgical margins. Patients reported improved understanding of their procedure using the three-dimensional model.

Conclusion:

This study shows the potential benefit of three-dimensional modelling technology with positive uptake from surgeons and patients. Benefits are improved perception of vascular anatomy and resection approach, and procedure understanding by patients. A randomised controlled trial is needed to evaluate the technology further.

Level of evidence:

2b

New imaging technologies for robotic kidney cancer surgery

Objective

Kidney cancers account for approximately 2% of all newly diagnosed cancer in 2020. Among the primary treatment options for kidney cancer, urologist may choose between radical or partial nephrectomy, or ablative therapies. Nowadays, robotic-assisted partial nephrectomy (RAPN) for the management of renal cancers has gained popularity, up to being considered the gold standard. However, RAPN is a challenging procedure with a steep learning curve.

Methods

In this narrative review, different imaging technologies used to guide and aid RAPN are discussed.

Results

Three-dimensional visualization technology has been extensively discussed in RAPN, showing its value in enhancing robotic-surgery training, patient counseling, surgical planning, and intraoperative guidance. Intraoperative imaging technologies such as intracorporeal ultrasound, near-infrared fluorescent imaging, and intraoperative pathological examination can also be used to improve the outcomes following RAPN. Finally, artificial intelligence may play a role in the field of RAPN soon.

Conclusion

RAPN is a complex surgery; however, many imaging technologies may play an important role in facilitating it.

Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit

Background: Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonography. Translating 2D images into digital 3-dimensional (3D) models may improve both preoperative planning and surgical guidance. The da Vinci^® robotic surgical system is a platform suitable for the integration of multiple imaging modalities into one single view. In this study, we describe multimodal imaging options and introduce the Robotic Liver Surgery Cockpit; Methods: in-house developed software was used and validated for segmentation and registration to create a virtual reality 3D model of the liver based on preoperative imaging. The accuracy of the 3D models in the clinical setting was objectively assessed in 15 patients by measuring tumor diameters and subjectively with a postoperative conducted questionnaire; Results: Implementation and applicability of the 3D model in the surgical cockpit was feasible in all patients and the quality of the 3D reconstructions was high in 14 (93%) of cases. Tumor diameters measured on CT and/or MR imaging were comparable to automated measurements using the segmentation software and 3D models; Conclusions: the 3D model was successfully incorporated in the robotic surgery console as part of a multimodality imaging platform and aided the surgeon in planning and guidance of the resection. Future studies should focus on further automation of 3D rendering and progress into augmented reality.

Contemporary Management of Locally Advanced and Recurrent Rectal Cancer: Views from the PelvEx Collaborative

Pelvic exenteration is a complex operation performed for locally advanced and recurrent pelvic cancers. The goal of surgery is to achieve clear margins, therefore identifying adjacent or involved organs, bone, muscle, nerves and/or vascular structures that may need resection. While these extensive resections are potentially curative, they can be associated with substantial morbidity. Recently, there has been a move to centralize care to specialized units, as this facilitates better multidisciplinary care input. Advancements in pelvic oncology and surgical innovation have redefined the boundaries of pelvic exenterative surgery. Combined with improved neoadjuvant therapies, advances in diagnostics, and better reconstructive techniques have provided quicker recovery and better quality of life outcomes, with improved survival This article provides highlights of the current management of advanced pelvic cancers in terms of surgical strategy and potential future developments.

Robotic partial nephrectomy in 3D virtual reconstructions era: is the paradigm changed?

CONTEXT

The development of a tailored, patient-specific medical and surgical approach is becoming object of intense research. In kidney oncologic surgery, where a clear understanding of case-specific surgical anatomy is considered a key point to optimize the perioperative outcomes, such philosophy gained increasing importance. Recently, important advances in 3D virtual modeling technologies have fueled the interest for their application in the field of robotic minimally invasive surgery for kidney tumors.

OBJECTIVE

To provide a synthesis of current applications of 3D virtual models for robot-assisted partial nephrectomy.

EVIDENCE ACQUISITION

Medline, PubMed, the Cochrane Database, and Embase were screened for Literature regarding the use of 3D virtual models for robot-assisted partial nephrectomy (RAPN).

EVIDENCE SYNTHESIS

The use of 3D virtual models for RAPN has been tested in different settings, including surgical indication and planning, intraoperative guidance, and training. Currently, several studies are available on the application of this technology for surgical planning, demonstrating impact on clinical outcomes such as renal function recovery, whilst experiences concerning their intraoperative application for navigation are still experimental. One of the latest innovations in this field is represented by the development of dedicated softwares able to automatically overlap the 3D virtual models to the real anatomy, to perform augmented reality procedures.

CONCLUSIONS

The available Literature suggests a potentially crucial role of 3D virtual reconstructions during RAPN. Encouraging results concerning surgical planning and indication, intraoperative navigation, and surgical training are available. In the future, artificial intelligence may represent the key to further improve the 3D virtual modeling technology during RAPN.

Artificial intelligence and simulation in urology

INTRODUCTION AND OBJECTIVE

Artificial intelligence (AI) is in full development and its implementation in medicine has led to an improvement in clinical and surgical practice. One of its multiple applications is surgical training, with the creation of programs that allow avoiding complications and risks for the patient. The aim of this article is to analyze the advantages of AI applied to surgical training in urology.

MATERIAL AND METHODS

A literary research is carried out to identify articles published in English regarding AI applied to medicine, especially in surgery and the acquisition of surgical skills.

RESULTS

Surgical training has evolved over time thanks to AI. A model for surgical learning where skills are acquired in a progressive way while avoiding complications to the patient, has been created. The use of simulators allows a progressive learning, providing trainees with procedures that increase in number and complexity. On the other hand, AI is used in imaging tests for surgical or treatment planning.

CONCLUSION

Currently, the use of AI in daily clinical practice has led to progress in medicine, specifically in surgical training.

Artificial intelligence and simulation in urology

INTRODUCTION AND OBJECTIVE

Artificial intelligence (AI) is in full development and its implementation in medicine has led to an improvement in clinical and surgical practice. One of its multiple applications is surgical training, with the creation of programs that allow avoiding complications and risks for the patient. The aim of this article is to analyze the advantages of AI applied to surgical training in urology.

MATERIAL AND METHODS

A literary research is carried out to identify articles published in English regarding AI applied to medicine, especially in surgery and the acquisition of surgical skills.

RESULTS

Surgical training has evolved over time thanks to AI. A model for surgical learning where skills are acquired in a progressive way while avoiding complications to the patient, has been created. The use of simulators allows a progressive learning, providing trainees with procedures that increase in number and complexity. On the other hand, AI is used in imaging tests for surgical or treatment planning.

CONCLUSION

Currently, the use of AI in daily clinical practice has led to progress in medicine, specifically in surgical training.

Virtual Reality in Preoperative Planning of Adolescent Idiopathic Scoliosis Surgery Using Google Cardboard

OBJECTIVE

Preoperative planning in spine surgery is a fundamental step of the surgical workup and is often assisted by direct visualization of anatomical 2-dimensional images. This process is time-consuming and may excessively approximate the 3-dimensional (3D) nature of spinal anatomy. Virtual reality (VR) is an emerging technology capable of reconstructing an interactive 3D anatomical model that can be freely explored and manipulated.

METHODS

Sixty patients with adolescent idiopathic scoliosis underwent correction of the scoliotic curve by posterior arthrodesis after preoperative planning using traditional on-screen visualization of computed tomography scans (control group, n = 30) or exploration of a 3D anatomical model in VR using Google Cardboard (Google Inc.) (VR group, n = 30). Mean operative time, blood loss, length of hospital stay, and surgeon's satisfaction were assessed after surgery.

RESULTS

The use of VR led to a significant decrease in operative time and bleeding while increasing the surgeon's satisfaction compared to the control group.

CONCLUSION

Preoperative planning with VR turned out to be effective in terms of operative time and blood loss reduction. Moreover, such technology proved to be reproducible, costeffective, and more satisfactory compared to conventional planning.

3D modeling in adherent perinephric fat prediction in nephron-sparing surgery planning in patients with localized renal neoplasms

STUDY OBJECTIVE

To develop a 3D-image based morphometry scoring system for Adherent Perinephric Fat (APF) prediction in nephron-sparing surgery in renal neoplasm patients.

MATERIALS AND METHODS

The retrospective study involved 391 patients who underwent a laparoscopic partial nephrectomy performed by five surgeons from January 2014 till December 2018. The surgery involved the 3D virtual operation planning with «Amira» 3D modeling software. With the multivariate logistic regression models, we developed a scoring system based on 3D-models. We tested the significance and sensitivity of new scoring system in a comparative ROC analysis with Mayo Adhesive Probability Score (MAP).

RESULTS

We found APF in 111 patients (28.4%). The univariate analysis revealed that significant indicators included mean age 59.88 (55-67) (p < 0.001), male sex (p < 0.001), Body Mass Index (BMI) >30 (21.47-35.08) kg/m² (p < 0.001), arterial hypertension (p < 0.001), coronary heart disease (p = 0.019), diabetes mellitus (p = 0.005), urolithiasis (p = 0.002). The multivariate regression analysis identified three most significant indicators in 3D models evaluation: additional >5 mm shadows in perirenal space OR = 7.3 (3.6-15.3) (p < 0.001), the number of shadows >5 OR = 3.8 (2.1-6.8) (p < 0.001), the wide shadow base at the renal parenchymal level OR = 0.293 (0.146-0.588) (p = 0.001). The scoring of these indicators comprises a new prediction scale (0-5). The ROC analysis revealed AUC 0.816 (95% CI 0.772-0.861) p < 0.001 of the MAP score, and AUC = 0.803 (95% CI 0.758-0.848) p < 0.001 of the scoring system developed in the present study.

CONCLUSIONS

The statistical findings comparison of the scoring system that we developed with those of MAP scale suggests that the scoring system is efficient and applicable.

Ex Vivo Porcine Model for Robot-Assisted Partial Nephrectomy Simulation at a High-Volume Tertiary Center: Resident Perception and Validation Assessment Using the Global Evaluative Assessment of Robotic Skills Tool

Introduction: With increased demands on surgeon productivity and outcomes, residency robotics training increasingly relies on simulations. The objective of this study is to assess the validity and effectiveness of an ex vivo porcine training model as a useful tool to improve surgical skill and confidence with robot-assisted partial nephrectomy (RAPN) among urology residents. Methods: A 2.5 cm circular area of ex vivo porcine kidneys was marked as the area of the tumor. Tumor excision and renorrhaphy was performed by trainees using a da Vinci Si robot. All residents ranging from postgraduate year (PGY) 2 to 5 participated in four training sessions during the 2017 to 2018 academic year. Each session was videorecorded and scored using the global evaluative assessment of robotic skills (GEARS) by faculty members. Results: Twelve residents completed the program. Initial mean GEARS score was 16.7 and improved by +1.4 with each subsequent session (p = 0.008). Initial mean excision, renorrhaphy, and total times were 8.2, 13.9, and 22.1 minutes, which improved by 1.6, 2.0, and 3.6 minutes, respectively (all p < 0.001). Residents' confidence at performing RAPN and robotic surgery increased after completing the courses (p = 0.012 and p < 0.001, respectively). Overall, residents rated that this program has greatly contributed to their skill (4/5) and confidence (4.1/5) in robotic surgery. Conclusions: An ex vivo porcine simulation model for RAPN and robotic surgery provides measurable improvement in GEARS score and reduction in procedural time, although significant differences for all PGY levels need to be confirmed with larger study participation. Adoption of this simulation in a urology residency curriculum may improve residents' skill and confidence in robotic surgery.

A virtual reality-based data analysis for optimizing freehand external ventricular drain insertion

PURPOSE

This work exploits virtual reality technique to analyse and optimize the preoperative planning of freehand external ventricular drain (EVD) insertion. Based on the three-dimensional (3D) virtual brain models, neurosurgeons can directly observe the anatomical landmarks and complete the simulated EVD insertion. Simulation data is used to optimize preoperative planning parameters to ensure the surgical performance.

METHODS

We used the computed tomography (CT) scans to construct the 3D virtual brain models. A group of EVD insertions were simulated by inserting virtual catheters at different entry points. The key parameters including the location of entry point, the catheter orientation, the catheter tip position on lateral ventricles, and the insertion depth were recorded. A data analysis method was then applied to optimize these parameters, resulting in the optimal parameters for the EVD insertion.

RESULTS

When the lateral distance of entry point ranged from 2.5 to 3 cm, the success rate of 204 cases was 97.79%, which was higher than that of the classic method (59.52%). The optimal insertion angle towards the sagittal plane ranged from 10.46° to 12.73°. To prevent penetrating the lateral ventricles, the insertion depth was optimized to be 3.28 to 4.58 cm.

CONCLUSIONS

The proposed data analysis method is helpful to optimize the key parameters of the preoperative planning, and provides useful references for neurosurgeons to perform the freehand EVD insertion. The EVD insertion experiments on 3D printing model had a success rate of 93.75%, which verified the effectiveness of the data analysis.

Evaluation of Interactive Virtual Reality as a Preoperative Aid in Localizing Renal Tumors

Introduction: A detailed understanding of renal tumor anatomy is required to perform partial nephrectomy. We evaluated the utility of a CT-based interactive virtual reality (iVR) display to assist surgeons' understanding of the precise location of the renal tumor. Methods: CT scans and iVR models of 11 patients with a mean R.E.N.A.L. nephrometry score of 6.9 were evaluated. Seven faculty urologists and six urology residents reviewed CT scans and positioned each tumor onto a digital three-dimensional model of the same kidney, although without the tumor present. A week later, participants repeated the session using both iVR models and CT scans. For both time points, the overlap between the surgeon-inserted tumor and the actual tumor location was calculated. Participants answered a 1 to 10 Likert scale survey to gauge their understanding of renal and tumor anatomy based on CT alone vs CT+iVR. Results: Median tumor overlap for the entire cohort was 28% after CT review and 42% after CT+iVR (p = 0.05); among faculty urologists, for CT+iVR vs CT alone, percentage overlap improved (47% vs 33%, p = 0.033) and the incidence of 0% overlap decreased (19%-4%, p = 0.024), respectively. Among residents, there was no significant difference for either percentage overlap or 0% overlap for CT vs CT+iVR. The percentage overlap for the two tumors with high R.E.N.A.L. nephrometry scores (i.e., 10) increased from 51% to 67% after using CT+iVR (p = 0.039). The combination of CT+iVR was an independent predictor of improved overlap vs CT alone (odds ratio 2.22, 95% confidence interval 1.04-4.78, p = 0.039). Faculty surgeons' survey responses showed an improved understanding of the tumor location and shape with the addition of iVR (p < 0.05). Conclusions: The addition of patient-specific iVR models to standard CT imaging improved the ability of faculty urologists to accurately configure the location of a renal tumor, and improved their understanding of tumor anatomy.

SlicerVR for Medical Intervention Training and Planning in Immersive Virtual Reality

Virtual reality (VR) provides immersive visualization that has proved to be useful in a variety of medical applications. Currently, however, no free open-source software platform exists that would provide comprehensive support for translational clinical researchers in prototyping experimental VR scenarios in training, planning or guiding medical interventions. By integrating VR functions in 3D Slicer, an established medical image analysis and visualization platform, SlicerVR enables virtual reality experience by a single click. It provides functions to navigate and manipulate the virtual scene, as well as various settings to abate the feeling of motion sickness. SlicerVR allows for shared collaborative VR experience both locally and remotely. We present illustrative scenarios created with SlicerVR in a wide spectrum of applications, including echocardiography, neurosurgery, spine surgery, brachytherapy, intervention training and personalized patient education. SlicerVR is freely available under BSD type license as an extension to 3D Slicer and it has been downloaded over 7,800 times at the time of writing this article.

Effect of 3-Dimensional Virtual Reality Models for Surgical Planning of Robotic-Assisted Partial Nephrectomy on Surgical Outcomes: A Randomized Clinical Trial

IMPORTANCE

Planning complex operations such as robotic-assisted partial nephrectomy requires surgeons to review 2-dimensional computed tomography or magnetic resonance images to understand 3-dimensional (3-D), patient-specific anatomy.

OBJECTIVE

To determine surgical outcomes for robotic-assisted partial nephrectomy when surgeons reviewed 3-D virtual reality (VR) models during operative planning.

DESIGN, SETTING, AND PARTICIPANTS

A single-blind randomized clinical trial was performed. Ninety-two patients undergoing robotic-assisted partial nephrectomy performed by 1 of 11 surgeons at 6 large teaching hospitals were prospectively enrolled and randomized. Enrollment and data collection occurred from October 2017 through December 2018, and data analysis was performed from December 2018 through March 2019.

INTERVENTIONS

Patients were assigned to either a control group undergoing usual preoperative planning with computed tomography and/or magnetic resonance imaging only or an intervention group where imaging was supplemented with a 3-D VR model. This model was viewed on the surgeon's smartphone in regular 3-D format and in VR using a VR headset.

MAIN OUTCOMES AND MEASURES

The primary outcome measure was operative time. It was hypothesized that the operations performed using the 3-D VR models would have shorter operative time than those performed without the models. Secondary outcomes included clamp time, estimated blood loss, and length of hospital stay.

RESULTS

Ninety-two patients (58 men [63%]) with a mean (SD) age of 60.9 (11.6) years were analyzed. The analysis included 48 patients randomized to the control group and 44 randomized to the intervention group. When controlling for case complexity and other covariates, patients whose surgical planning involved 3-D VR models showed differences in operative time (odds ratio [OR], 1.00; 95% CI, 0.37-2.70; estimated OR, 2.47), estimated blood loss (OR, 1.98; 95% CI, 1.04-3.78; estimated OR, 4.56), clamp time (OR, 1.60; 95% CI, 0.79-3.23; estimated OR, 11.22), and length of hospital stay (OR, 2.86; 95% CI, 1.59-5.14; estimated OR, 5.43). Estimated ORs were calculated using the parameter estimates from the generalized estimating equation model. Referent group values for each covariate and the corresponding nephrometry score were summed across the covariates and nephrometry score, and the sum was exponentiated to obtain the OR. A mean of the estimated OR weighted by sample size for each nephrometry score strata was then calculated.

CONCLUSIONS AND RELEVANCE

This large, randomized clinical trial demonstrated that patients whose surgical planning involved 3-D VR models had reduced operative time, estimated blood loss, clamp time, and length of hospital stay.

TRIAL REGISTRATION

ClinicalTrials.gov identifiers (1 registration per site): NCT03334344, NCT03421418, NCT03534206, NCT03542565, NCT03556943, and NCT03666104.

A case of allograft ureteral stone successfully treated with antegrade ureteroscopic lithotripsy: use of a 3D-printed model to determine the ideal approach

We present the case of a 46-year-old man who underwent successful antegrade ureteroscopy for lithiasis in his allograft ureter. At a scheduled follow-up 15 years after transplantation, computed tomography (CT) detected a 12-mm renal stone in the renal pelvis of the transplanted kidney. During his follow-up, gross hematuria was seen; the stone moved to the ureter, causing hydronephrosis. Ultrasound and non-contrast CT revealed hydronephrosis and a 15-mm stone in the transplanted ureter. Considering the stone size, location, and the difficulty of the access to the anastomosed ureteral orifice, percutaneous ureteroscopic approach was planned. Due to the anatomical difficulty regarding his allograft kidney, we planned to prepare a 3D image and model for selecting the best percutaneous approach. The procedure was performed and a stone-free status was acquired without complication. Under precise simulation, we performed successful antegrade ureteroscopy for lithiasis in the allograft ureter supported by 3D imaging. Use of a 3D printed model may aid in a safe and effective procedure for lithiasis in the allograft kidney and ureter.