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

Three-dimensional virtual model for robot-assisted partial nephrectomy: a propensity-score matching analysis with a contemporary control group

PURPOSE

To compare two cohorts of patients submitted to robot-assisted partial nephrectomy (RAPN) with vs without the use of three-dimensional virtual models (3DVMs).

METHODS

We screened a prospective consecutive cohort of 152 patients submitted to RAPN with 3DVM and 1264 patients submitted to RAPN without 3DVM between 2019 and 2022. Propensity score matching analysis (PSMA) was applied. Primary endpoint was to evaluate whereas RAPNs with 3DVM were superior in terms of functional outcomes at 12-month. Secondary endopoints were to compare perioperative and oncological outcomes. Multivariable logistic regression analyses (MVA) tested the associations of clinically significant eGFR drop and 3DVMs. Subgroups analysis was performed for PAUDA-risk categories.

RESULTS

100 patients for each group were analyzed after PSMA. RAPN with 3DVM presented a higher rate of selective/no clamping procedure (32% vs 16%, p = 0.03) and a higher enucleation rate (40% vs 29%, p = 0.04). As concern to primary endopoint, 12-month functional preservation performed better within 3DVM group in terms of creatinine serum level (median 1.2 [IQR 1.1-1.4] vs 1.6 [IQR 1.1-1.8], p = 0.03) and eGFR (median 64.6 [IQR 56.2-74.1] vs 52.3 [IQR 49.2-74.1], p = 0.03). However, this result was confirmed only in the PADUA ≥ 10 renal masses. Regarding secondary endpoints, no significative difference emerged between the two cohorts. MVA confirmed 3DVM as a protective factor for clinically significant eGFR drop only in high-risk (PADUA ≥ 10) masses.

CONCLUSIONS

RAPN performed with the use of 3DVM assistance resulted in lower incidence of global ischemia and higher rate of enucleations. The positive impact of such technology was found at 12-month only in high-risk renal masses.

Preparing for the Worst: Management and Predictive Factors of Open Conversion During Minimally Invasive Renal Tumor Surgery (UroCCR-135 Study)

Background and objective

Data regarding open conversion (OC) during minimally invasive surgery (MIS) for renal tumors are reported from big databases, without precise description of the reason and management of OC. The objective of this study was to describe the rate, reasons, and perioperative outcomes of OC in a cohort of patients who underwent MIS for renal tumor initially. The secondary objective was to find the factors associated with OC.

Methods

Between 2008 and 2022, of the 8566 patients included in the UroCCR project prospective database (NCT03293563), who underwent laparoscopic or robot-assisted minimally invasive partial (MIPN) or radical (MIRN) nephrectomy, 163 experienced OC. Each center was contacted to enlighten the context of OC: "emergency OC" implied an immediate life-threatening situation not reasonably manageable with MIS, otherwise "elective OC". To evaluate the predictive factors of OC, a 2:1 paired cohort on the UroCCR database was used.

Key findings and limitations

The incidence rate of OC was 1.9% for all cases of MIS, 2.9% for MIRN, and 1.4% for MIPN. OC procedures were mostly elective (82.2%). The main reason for OC was a failure to progress due to anatomical difficulties (42.9%). Five patients (3.1%) died within 90 d after surgery. Increased body mass index (BMI; odds ratio [OR]: 1.05, 95% confidence interval [CI]: 1.01-1.09, p = 0.009) and cT stage (OR: 2.22, 95% CI: 1.24-4.25, p = 0.008) were independent predictive factors of OC.

Conclusions and clinical implications

In MIS for renal tumors, OC was a rare event (1.9%), caused by various situations, leading to impaired perioperative outcomes. Emergency OC occurred once every 300 procedures. Increased BMI and cT stage were independent predictive factors of OC.

Patient summary

The incidence rate of open conversion (OC) in minimally invasive surgery for renal tumors is low. Only 20% of OC procedures occur in case of emergency, and others are caused by various situations. Increased body mass index and cT stage were independent predictive factors of OC.

Comparison of Perioperative, Functional, and Oncologic Outcomes of Open vs. Robot-Assisted Off-Clamp Partial Nephrectomy: A Propensity Scored Match Analysis

Off-clamp partial nephrectomy represents one of the latest developments in nephron-sparing surgery, with the goal of preserving renal function and reducing ischemia time. The aim of this study was to evaluate and compare the functional, oncologic, and perioperative outcomes between off-clamp robot-assisted partial nephrectomy (off-C RAPN) and off-clamp open partial nephrectomy (off-C OPN) through a propensity score-matched (PSM) analysis. A 1:1 PSM analysis was used to balance variables potentially affecting postoperative outcomes. To report surgical quality, 1 year trifecta was used. Univariable Cox regression analysis was performed to identify predictors of trifecta achievement. The Kaplan-Meier method was used to compare cancer-specific survival (CSS), overall survival (OS), disease-free survival (DFS), and metastasis-free survival (MFS) probabilities between groups. Overall, 542 patients were included. After PSM analysis, two homogeneous cohorts of 147 patients were obtained. The off-C RAPN cohort experienced shorter length of stay (LoS) (3.4 days vs. 5.4 days; p < 0.001), increased likelihoods of achieving 1 year trifecta (89.8% vs. 80.3%; p = 0.03), lower postoperative Clavien-Dindo ≤ 2 complications (1.3% vs. 18.3%, p < 0.001), and lower postoperative transfusion rates (3.4% vs. 12.2%, p = 0.008). At univariable analysis, the surgical approach (off-C RAPN vs. off-C OPN, OR 2.22, 95% CI 1.09-4.46, p = 0.02) was the only predictor of 1 year trifecta achievement. At Kaplan-Meier analysis, no differences were observed between the two groups in terms of OS (log-rank p = 0.451), CSS (log-rank p = 0.476), DFS (log-rank p = 0.678), and MFS (log-rank p = 0.226). Comparing RAPN and OPN in a purely off-clamp scenario, the minimally invasive approach proved to be a feasible and safe surgical approach, with a significantly lower LoS and minor rate of postoperative complications and transfusions as a result of improved surgical quality expressed by higher 1 year trifecta achievement.

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.

Metaverse and Telementoring: From Surgery to Workshop

BACKGROUND

The Coronavirus 2019 (COVID-19) pandemic has favored the growth of telemedicine systems and in this context the idea of Metaverse was born and developed. A 3D reality in which people can interact with each other through digital reproductions of themselves. Metaverse has already been tested in numerous medical fields due to its ability to combine visual and auditory information with tactile sensations. The purpose of this study is to highlight its potential also in its ability to be used as a telementoring place where the skills and knowledge of surgeons from all over the world can be combined.

MATERIAL AND METHODS

The first HPB Surgery Workshop was held at the "Metaverse Surgical Hospital, USA". During the workshop, surgeons located in various parts of the world reported on hepatic, pancreatic and biliary tract surgery and remotely supported the execution of a robotic liver resection.

RESULTS

The Metaverse gave the opportunity for surgeons to meet and discuss HPB pathologies and its surgical strategies and for surgeons in training to interface with experts by participating in a moment of advanced training.

CONCLUSION

In the Metaverse, telementoring can be used at very low cost to improve clinical and surgical practice.

First-in-human real-time AI-assisted instrument deocclusion during augmented reality robotic surgery

The integration of Augmented Reality (AR) into daily surgical practice is withheld by the correct registration of pre-operative data. This includes intelligent 3D model superposition whilst simultaneously handling real and virtual occlusions caused by the AR overlay. Occlusions can negatively impact surgical safety and as such deteriorate rather than improve surgical care. Robotic surgery is particularly suited to tackle these integration challenges in a stepwise approach as the robotic console allows for different inputs to be displayed in parallel to the surgeon. Nevertheless, real-time de-occlusion requires extensive computational resources which further complicates clinical integration. This work tackles the problem of instrument occlusion and presents, to the authors' best knowledge, the first-in-human on edge deployment of a real-time binary segmentation pipeline during three robot-assisted surgeries: partial nephrectomy, migrated endovascular stent removal, and liver metastasectomy. To this end, a state-of-the-art real-time segmentation and 3D model pipeline was implemented and presented to the surgeon during live surgery. The pipeline allows real-time binary segmentation of 37 non-organic surgical items, which are never occluded during AR. The application features real-time manual 3D model manipulation for correct soft tissue alignment. The proposed pipeline can contribute towards surgical safety, ergonomics, and acceptance of AR in minimally invasive surgery.

The rationale for nephron-sparing surgery in unilateral non-syndromic Wilms tumour

The central question of nephron-sparing surgery in unilateral non-syndromic Wilms tumour sits at a crossroads between surgery, oncology, and nephrology. There has been a significant paradigm shift in paediatric oncology towards reducing toxicity and addressing long-term treatment-related sequalae amongst childhood cancer survivors. After paediatric nephrectomy and 30-50 years of follow-up, 40% of patients will have chronic kidney disease, including 22% with hypertension and 23% with albuminuria. It is difficult to predict which patients will progress to develop hypertension, reduced glomerular filtration rate, albuminuria, and a higher cardiovascular risk. For these reasons, nephron-sparing surgery when it is technically feasible must be considered. To decrease the incidence of positive surgical margins (viable tumour present at a resection margin), incomplete lymph node sampling, and complications, these procedures should be performed at specialist and experienced reference centres. Based on the impacts of individual treatment pathways, survivors of childhood WT need to be followed through adulthood for early detection of chronic kidney disease, hypertension, and prevention of cardiovascular events.

Robotic Vena Cava Thrombectomy with Three-dimensional Augmented Reality Guidance

Robotic surgery has recently been used for treatment of renal cell carcinoma (RCC) and neoplastic thrombus located in the renal vein or inferior vena cava (IVC). Accurate identification of the thrombus location is crucial, and three-dimensional augmented reality (3D AR) may be valuable in achieving this. We enrolled patients with nonmetastatic RCC and level 0-I venous thrombus (Mayo Clinic classification) for robot-assisted radical nephrectomy and thrombectomy with 3D AR guidance. Five patients were prospectively enrolled; three had a level 0 thrombus and two had a level I thrombus. The mean operative time was 123 ± 15 min, mean IVC clamping time was 9.4 ± 6.8 min, and mean estimated blood loss was 750 ± 150 ml. The AR system allowed precise estimation of the thrombus location in all cases. No intraoperative complications or postoperative Clavien-Dindo grade >2 complications occurred. Use of 3D AR guidance allowed correct estimation of the limits of the thrombus and guided the surgeon in selecting an appropriate surgical strategy.

Metaverse Surgical Planning with Three-dimensional Virtual Models for Minimally Invasive Partial Nephrectomy

The recent integration of new virtual visualization modalities with artificial intelligence and high-speed internet connection has opened the door to the advent of the metaverse in medicine. In this totally virtual environment, three-dimensional virtual models (3DVMs) of the patient's anatomy can be visualized and discussed via digital avatars. Here we present for the first time a metaverse preoperative clinical case discussion before minimally invasive partial nephrectomy. The surgeons' digital avatars met in a virtual room and participated in a virtual consultation on the surgical strategy and clamping approach before the procedure. Robotic or laparoscopic procedures are then carried out according to the simulated surgical strategy. We demonstrate how this immersive virtual reality experience overcomes the barriers of distance and how the quality of surgical planning is enriched by a great sense of "being there", even if virtually. Further investigation will improve the quality of interaction with the models and among the avatars.

Partial nephrectomy for renal tumors: recommendations of the Italian Society of Urology RCC working group

INTRODUCTION

Partial nephrectomy (PN) aims to remove renal tumors while preserving renal function without affecting oncological and perioperative surgical outcomes. Aim of this paper is to summarize the current evidence on PN and to provide evidence-based recommendations on indications, surgical technique, perioperative management and postoperative surveillance of PN for renal tumors in the Italian clinical and health care system context.

EVIDENCE ACQUISITION

This review is the result of an interactive peer-reviewing process of the recent literature on PN for renal tumors carried out by an expert panel composed of members of the Italian Society of Urology (SIU) Renal Cell Carcinoma Working Group.

EVIDENCE SYNTHESIS

PN for localized renal tumors is not inferior to radical nephrectomy in terms of survival outcomes while significantly better preserving renal function. Loss of renal function after PN is influenced by medical comorbidities/preoperative renal function and surgical variables such volume of parenchyma preserved and ischemia time. Urologists should select the clamping strategy during PN based on their experience and patient-specific factors. PN can be performed with any surgical approach based on surgeon's expertise and skills. Robotic PN has the potential to expand the minimally invasive indications without interfering with oncological outcomes. The use of 3D virtual models, real time ultrasound and fluorescence tools to assess the anatomy and vascularization of renal tumors during PN may allow a more accurate preoperative planning and intraoperative guidance. Proper postoperative surveillance protocols are essential to detect tumor recurrences and assess functional outcomes.

CONCLUSIONS

PN is the standard of care for treatment of localized T1 renal tumors. Recent data supports PN also for selected T2-T3a tumors in experienced institutions. Careful preoperative planning, adequate surgical skills and volumes and appropriate postoperative management and surveillance are paramount to optimize PN oncological and functional outcomes.

Computer Vision and Machine-Learning Techniques for Automatic 3D Virtual Images Overlapping During Augmented Reality Guided Robotic Partial Nephrectomy

OBJECTIVES

The research's purpose is to develop a software that automatically integrates and overlay 3D virtual models of kidneys harboring renal masses into the Da Vinci robotic console, assisting surgeon during the intervention.

INTRODUCTION

Precision medicine, especially in the field of minimally-invasive partial nephrectomy, aims to use 3D virtual models as a guidance for augmented reality robotic procedures. However, the co-registration process of the virtual images over the real operative field is performed manually.

METHODS

In this prospective study, two strategies for the automatic overlapping of the model over the real kidney were explored: the computer vision technology, leveraging the super-enhancement of the kidney allowed by the intraoperative injection of Indocyanine green for superimposition and the convolutional neural network technology, based on the processing of live images from the endoscope, after a training of the software on frames from prerecorded videos of the same surgery. The work-team, comprising a bioengineer, a software-developer and a surgeon, collaborated to create hyper-accuracy 3D models for automatic 3D-AR-guided RAPN. For each patient, demographic and clinical data were collected.

RESULTS

Two groups (group A for the first technology with 12 patients and group B for the second technology with 8 patients) were defined. They showed comparable preoperative and post-operative characteristics. Concerning the first technology the average co-registration time was 7 (3-11) seconds while in the case of the second technology 11 (6-13) seconds. No major intraoperative or postoperative complications were recorded. There were no differences in terms of functional outcomes between the groups at every time-point considered.

CONCLUSION

The first technology allowed a successful anchoring of the 3D model to the kidney, despite minimal manual refinements. The second technology improved kidney automatic detection without relying on indocyanine injection, resulting in better organ boundaries identification during tests. Further studies are needed to confirm this preliminary evidence.

3D Model Artificial Intelligence-Guided Automatic Augmented Reality Images during Robotic Partial Nephrectomy

More than ever, precision surgery is making its way into modern surgery for functional organ preservation. This is possible mainly due to the increasing number of technologies available, including 3D models, virtual reality, augmented reality, and artificial intelligence. Intraoperative surgical navigation represents an interesting application of these technologies, allowing to understand in detail the surgical anatomy, planning a patient-tailored approach. Automatic superimposition comes into this context to optimally perform surgery as accurately as possible. Through a dedicated software (the first version) called iKidney, it is possible to superimpose the images using 3D models and live endoscopic images during partial nephrectomy, targeting the renal mass only. The patient is 31 years old with a 28 mm totally endophytic right-sided renal mass, with a PADUA score of 9. Thanks to the automatic superimposition and selective clamping, an enucleoresection of the renal mass alone was performed with no major postoperative complication (i.e., Clavien-Dindo < 2). iKidney-guided partial nephrectomy is safe, feasible, and yields excellent results in terms of organ preservation and functional outcomes. Further validation studies are needed to improve the prototype software, particularly to improve the rotational axes and avoid human help. Furthermore, it is important to reduce the costs associated with these technologies to increase its use in smaller hospitals.

[Intervention planning in modern renal surgery]

BACKGROUND

Three-dimensional (3D) reconstruction in renal surgery offers significant benefits in planning of the operation itself, in patient education and training fellows.

OBJECTIVE

The goal was to study the possible application and use of 3D reconstruction in modern renal surgery.

METHODS

A literature search in PubMed using keywords "3D" and "renal surgery" within the last 10 years of publication was performed.

RESULTS

The search revealed 655 articles among them 53 reviews. Relevant for this article were 120 articles which included 14 reviews. The publication statistics showed a strong increase in the last 10 years which may reflect the increasing application and demand for 3D technology in the field of renal surgery. Especially in robot-assisted minimally invasive surgery applications, the use of 3D technology was studied more often. The technical standards are not yet uniform and 3D printing in complex renal surgery remains cost- and time-intensive. Nevertheless, the results of the pioneering clinical studies showed positive results, and 3D technology can be used not only in planning the operation, but in patient education and also the training of fellows and staff. A limitation to more complex cases seems to be sensible for this is still a costly tool. To identify complex cases in renal surgery, the established renometric scoring systems should be used more broadly in daily practice to identify patients who would profit most from this technique.

CONCLUSION

In complex renal surgery, 3D reconstruction and modelling is rational; furthermore, it can be useful in patient education and in training of fellows.

A systematic review of robot-assisted partial nephrectomy outcomes for advanced indications: Large tumors (cT2-T3), solitary kidney, completely endophytic, hilar, recurrent, and multiple renal tumors

Objective

Robot-assisted partial nephrectomy (RAPN) has become widely used for treatment of renal cell carcinoma and it is expanding in the field of complex renal masses. The aim of this systematic review was to analyze outcomes of RAPN for completely endophytic renal masses, large tumors (cT2-T3), renal cell carcinoma in solitary kidney, recurrent tumors, completely endophytic and hilar masses, and simultaneous and multiple tumors.

Methods

A comprehensive search in the PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials databases was performed in December 2022 for English language papers. The primary endpoint was to evaluate the role of RAPN in the setting of each category of complex renal masses considered. The secondary endpoint was to evaluate the surgical and functional outcomes.

Results

After screening 1250 records, 43 full-text manuscripts were selected, comprising over 8500 patients. Twelve and thirteen studies reported data for endophytic and hilar renal masses, respectively. Five and three studies reported outcomes for cT2-T3 and solitary kidney patients, respectively. Four studies focused on redo-RAPN for recurrent tumors. Two studies investigated simultaneous bilateral renal masses and five reports focused on multiple tumor excision in ipsilateral kidney.

Conclusion

Over the past decade, evidence supporting the use of RAPN for the most challenging nephron-sparing surgery indications has continuously grown. Although limitations remain including study design and lack of detailed long-term functional and oncological outcomes, the adoption of RAPN for the included advanced indications is associated with favorable surgical outcomes with good preservation of renal function without compromising the oncological result. Certainly, a higher likelihood of complication might be expected when facing extremely challenging cases. However, none of these indications should be considered per se an exclusion criterion for performing RAPN. Ultimately, a risk-adapted approach should be employed.

Three-dimensional Virtual Models of the Kidney with Colored Perfusion Regions: A New Algorithm-based Tool for Optimizing the Clamping Strategy During Robot-assisted Partial Nephrectomy

BACKGROUND

An empirical selective clamping strategy based on the direction of the arterial branches can lead to failures during partial nephrectomy, even when assisted by three-dimensional virtual models (3DVMs).

OBJECTIVE

To develop and test new 3DVMs that include kidney perfusion regions and evaluate their intraoperative accuracy in guiding selective clamping and their impact on postoperative renal function.

DESIGN, SETTING, AND PARTICIPANTS

For patients with a kidney suitable for nephron-sparing surgery, 3DVMs were supplemented with a Voronoi diagram, a Euclidean distance-based mathematical tool, to calculate vascular-dominant regions the kidney.

SURGICAL PROCEDURE

Robot-assisted partial nephrectomy guided by perfusion-region (PR)-3DVMs.

MEASUREMENTS

All anatomic information given by the PR-3DVMs was collected. Selective or superselective clamping was planned and performed intraoperatively when feasible under 3DVM assistance. Changes in split renal function (SRF) and estimated renal plasmatic flow (ERPF) were evaluated for 51 patients who underwent baseline and 3-mo postoperative renal scintigraphy.

RESULTS AND LIMITATIONS

A total of 103 patients were prospectively enrolled. The median number of kidney and tumor perfusion regions were 8 (interquartile range [IQR] 7-10) and 3 (IQR 2-3), respectively. A clampless, selective clamping, and global clamping strategy was applied in eight (7.8%), 79 (76.6%), and 16 (15.5%) cases, respectively, with no differences between planning and surgery in terms of the number or order of arteries clamped or the perfusion regions that underwent ischemia. Among the 51 patients who underwent renal scintigraphy, the mean SRF decreased by 11.3%, 7.7%, and 1.7% after global, selective, and superselective clamping, respectively (p = 0.004). Similar results were obtained for ERPF (18.9%, 9.9%, and 6.0%; p = 0.02). The main limitation is the need for a bioengineer to manually refine the 3DVMs.

CONCLUSIONS

Use of mathematical algorithms for 3DVMs allows precise estimation of kidney perfusion regions to maximize the efficacy of selective clamping and minimize renal function impairment.

PATIENT SUMMARY

Three-dimensional models that include regions of blood flow to the kidney can be used to guide clamping of blood vessels when part of the kidney is being surgically removed. More limited clamping can reduce damage to the remaining portion of the kidney and result in better recovery of kidney function after surgery.

Percutaneous tumor ablation versus image guided robotic-assisted partial nephrectomy for cT1b renal cell carcinoma: a comparative matched-pair analysis (UroCCR 80)

BACKGROUND

Partial nephrectomy (PN) is the gold standard treatment for cT1b renal tumors. Percutaneous guided thermal ablation (TA) has proven oncologic efficacy with low morbidity for the treatment of small renal masses (<3 cm). Recently, 3D image-guided robot-assisted PN (3D-IGRAPN) has been described, and decreased perioperative morbidity compared to standard RAPN has been reported. Our objective was to compare two minimally invasive image-guided nephron-sparing procedures (TA vs. 3D-IGRAPN) for the treatment of cT1b renal cell carcinomas (4.1-7 cm).

METHODS

Patients treated with TA and 3D-IGRAPN for cT1b renal cell carcinoma, prospectively included in the UroCCR database (NCT03293563), were pair-matched for tumor size, pathology, and RENAL score. The primary endpoint was the local recurrence rate between the two groups. Secondary endpoints included metastatic evolution, perioperative complications, decrease in renal function, and length of hospitalization.

RESULTS

A total of 198 patients were included and matched into two groups of 72 patients. The local recurrence rate was significantly higher in the TA group than that in the 3D-IGRAPN group (4.2% vs. 15.2%, P=0.04). Metastatic evolution and perioperative outcomes such as major complications, eGFR decrease, and length of hospitalization did not differ significantly between the two groups.

CONCLUSIONS

3D-IGRAPN resulted in a significantly lower local recurrence rate and comparable rates of complications and metastatic evolution compared with thermal ablation.

Three-Dimensional Customized Imaging Reconstruction for Urological Surgery: Diffusion and Role in Real-Life Practice from an International Survey

Despite the arising interest in three-dimensional (3D) reconstruction models from 2D imaging, their diffusion and perception among urologists have been scarcely explored. The aim of the study is to report the results of an international survey investigating the use of such tools among urologists of different backgrounds and origins. Beyond demographics, the survey explored the degree to which 3D models are perceived to improve surgical outcomes, the procedures mostly making use of them, the settings in which those tools are mostly applied, the surgical steps benefiting from 3D reconstructions and future perspectives of improvement. One hundred responders fully completed the survey. All levels of expertise were allowed; more than half (53%) were first surgeons, and 59% had already completed their training. Their main application was partial nephrectomy (85%), followed by radical nephrectomy and radical prostatectomy. Three-dimensional models are mostly used for preoperative planning (75%), intraoperative consultation and tailoring. More than half recognized that 3D models may highly improve surgical outcomes. Despite their recognized usefulness, 77% of responders use 3D models in less than 25% of their major operations due to costs or the extra time taken to perform the reconstruction. Technical improvements and a higher availability of the 3D models will further increase their role in surgical and clinical daily practice.

Does tumor rupture during robot-assisted partial nephrectomy have an impact on mid-term tumor recurrences?

BACKGROUND

Intraoperative kidney tumor rupture (TR) can occur during robot-assisted partial nephrectomy (RAPN) in daily clinical practice, but there are no solid guidelines on the management and implications of it. The purpose of the study was to investigate the impact of TR on tumor recurrences, what a surgeon should do if this adverse event occurs, and how to avoid it.

PATIENTS AND METHODS

We retrospectively analyzed the first 100 patients who underwent RAPN at University Medical Centre Ljubljana, between 2018 and 2021. Patients were stratified into 2 groups (TR and no-TR) and were compared according to patient, tumor, pathologic, perioperative and postoperative characteristics and tumor recurrences, using the Mann-Whitney U test and chi-squared test.

RESULTS

Of the 100 patients, 14 had TR (14%); this occurred in tumors with higher RENAL nephrometry scores (P = 0.028) and mostly with papillary renal cell carcinomas (P = 0.043). Median warm ischemia time was longer for the TR group (22 vs. 15 min, P = 0.026). In terms of studied outcomes, there were no cases of local or distant recurrence after a median observation time of 39 months (interquartile range, 31-47 months) in both groups. We observed positive surgical margins on the final oncologic report in one case in the no-TR group.

CONCLUSIONS

Tumor rupture during RAPN seems to be of no mid-term oncologic importance. According to presented results, we would recommend surgeons to proceed with tumor resection if this event occurs and abstain from conversion to radical nephrectomy or open partial nephrectomy. However, more similar cases should be studied to make more solid conclusions.

Artificial Intelligence-Based Hyper Accuracy Three-Dimensional (HA3D®) Models in Surgical Planning of Challenging Robotic Nephron-Sparing Surgery: A Case Report and Snapshot of the State-of-the-Art with Possible Future Implications

Recently, 3D models (3DM) gained popularity in urology, especially in nephron-sparing interventions (NSI). Up to now, the application of artificial intelligence (AI) techniques alone does not allow us to obtain a 3DM adequate to plan a robot-assisted partial nephrectomy (RAPN). Integration of AI with computer vision algorithms seems promising as it allows to speed up the process. Herein, we present a 3DM realized with the integration of AI and a computer vision approach (CVA), displaying the utility of AI-based Hyper Accuracy Three-dimensional (HA3D^®) models in preoperative planning and intraoperative decision-making process of challenging robotic NSI. A 54-year-old Caucasian female with no past medical history was referred to the urologist for incidental detection of the right renal mass. Preoperative contrast-enhanced abdominal CT confirmed a 35 × 25 mm lesion on the anterior surface of the upper pole (PADUA 7), with no signs of distant metastasis. CT images in DICOM format were processed to obtain a HA3D^® model. RAPN was performed using Da Vinci Xi surgical system in a three-arm configuration. The enucleation strategy was achieved after selective clamping of the tumor-feeding artery. Overall operative time was 85 min (14 min of warm ischemia time). No intra-, peri- and post-operative complications were recorded. Histopathological examination revealed a ccRCC (stage pT1aNxMx). AI is breaking new ground in medical image analysis panorama, with enormous potential in organ/tissue classification and segmentation, thus obtaining 3DM automatically and repetitively. Realized with the integration of AI and CVA, the results of our 3DM were accurate as demonstrated during NSI, proving the potentialities of this approach for HA3D^® models' reconstruction.

A three-dimensional renal tumor anatomy and intrarenal relationship nephrometry (ADDD) for robot-assisted partial nephrectomy : 3D-CT based nephrometry for RAPN

OBJECTIVE

To develop a 3D scoring system of tumor anatomy and intrarenal relationship for assessing surgical complexity and outcomes of robot-assisted partial nephrectomy (RAPN).

METHODS

We prospectively enrolled patients with a renal tumor who had a 3D model and underwent RAPN between Mar 2019 and Mar 2022. The ADDD nephrometry consisted of the contact surface area between tumor and parenchyma (A), the depth of tumor invasion into the renal parenchyma (D1), the distance from tumor to the main intrarenal artery (D2), and to the collecting system (D3). The primary outcomes included perioperative complication rate and trifecta outcome (WIT ≤ 25 min, negative surgical margins, and no major complications).

RESULTS

We enrolled a total of 301 patients. The mean tumor size was 2.93 ± 1.44 cm. There were 104 (34.6%) patients, 119 (39.5%) patients, and 78 (25.9%) patients in the low-, intermediate-, and high-risk groups, respectively. Each point increase in the ADDD score increased the risk of complications [hazard ratio (HR) 1.501]. A lower grade indicated a lower risk of failed trifecta (HR low group 15.103, intermediate group 9.258) and renal function damage (HR low risk 8.320, intermediate risk 3.165) compared to the high-risk group. The AUC of ADDD score and grade were 0.738 and 0.645 for predicting major complications, 0.766 and 0.714 for predicting trifecta outcome, and 0.746 and 0.730 for predicting postoperative renal function reservation.

CONCLUSION

The 3D-ADDD scoring system shows the tumor anatomy and its intraparenchymal relationships and has better efficacy in predicting surgical outcomes of RAPN.

New Generation of 3D Virtual Models with Perfusional Zones: Perioperative Assistance for the Best Pedicle Management during Robotic Partial Nephrectomy

Selective clamping during robot-assisted partial nephrectomy (RAPN) may reduce ischemia-related functional impairment. The intraoperative use of 3D-virtual models (3DVMs) can improve surgical planning, resulting in a greater success rate for selective clamping. Our goal is to introduce a new generation of 3DVMs, which consider the perfusion volumes of the kidney. Patients listed for RAPN from 2021 to 2022 were recruited. A selective clamping strategy was designed and intraoperatively performed based on the specifically generated 3DVMs. The effectiveness of selective clamping was evaluated using near-infrared-fluorescence imaging (NIRF) and 3DVM. Perfusion areas extensions were compared, and relevant preoperative characteristics were analyzed. In 61 of 80 (76.25%) cases, selective clamping was performed. The concordance between the 3DVM areas and the NIRF-enhanced areas was verified (k = 0.91). According to the distribution of perfused areas crossing the tumor, there were one, two, three, four, and five crossing areas, with relative perfusion rates of 13.75%, 35%, 32.5%, 13.75%, and 5%, respectively. Lesion diameter and mesorenal location were the only factors related to a higher number (>3) of perfusion volumes crossing the lesion. The implementation of mathematical algorithms to 3DVMs allows for precise estimation of the perfusion zone of each arterial branch feeding the organ, leading to the performance of safe and effective pedicle management planning.

Health Information Technology Usability Evaluation Scale (Health-ITUES) and User-Experience Questionnaire (UEQ) for 3D Intraoperative Cognitive Navigation (ICON3DTM) System for Urological Procedures

Backgound and objectives: In recent years, the adoption of 3D models for surgical planning and intraoperative guidance has gained a wide diffusion. The aim of this study was to evaluate the surgeons' perception and usability of ICON3D^TM platform for robotic and laparoscopic urological surgical procedures. Materials and Methods: During the 10th edition of the Techno-Urology Meeting, surgeons and attendees had the opportunity to test the new ICON3D^TM platform. The capability of the user to manipulate the model with hands/mouse, the software usability, the quality of the 3D model's reproduction, and the quality of its use during the surgery were evaluated with the Health Information Technology Usability Evaluation Scale (Health-ITUES) and the User-Experience Questionnaire (UEQ). Results: Fifty-three participants responded to the questionnaires. Based on the answers to the Health-ITUES questionnaire, ICON3D^TM resulted to have a positive additional value in presurgical/surgical planning with 43.4% and 39.6% of responders that rated 4 (agree) and 5 (strongly agree), respectively. Regarding the UEQ questionnaire, both mouse and infrared hand-tracking system resulted to be easy to use for 99% of the responders, while the software resulted to be easy to use for 93.4% of the responders. Conclusions: In conclusion, ICON3D^TM has been widely appreciated by urologists thanks to its various applications, from preoperative planning to its support for intraoperative decision-making in both robot-assisted and laparoscopic settings.

Improving Augmented Reality Through Deep Learning: Real-time Instrument Delineation in Robotic Renal Surgery

Several barriers prevent the integration and adoption of augmented reality (AR) in robotic renal surgery despite the increased availability of virtual three-dimensional (3D) models. Apart from correct model alignment and deformation, not all instruments are clearly visible in AR. Superimposition of a 3D model on top of the surgical stream, including the instruments, can result in a potentially hazardous surgical situation. We demonstrate real-time instrument detection during AR-guided robot-assisted partial nephrectomy and show the generalization of our algorithm to AR-guided robot-assisted kidney transplantation. We developed an algorithm using deep learning networks to detect all nonorganic items. This algorithm learned to extract this information for 65 927 manually labeled instruments on 15 100 frames. Our setup, which runs on a standalone laptop, was deployed in three different hospitals and used by four different surgeons. Instrument detection is a simple and feasible way to enhance the safety of AR-guided surgery. Future investigations should strive to optimize efficient video processing to minimize the 0.5-s delay currently experienced. General AR applications also need further optimization, including detection and tracking of organ deformation, for full clinical implementation.