Three-dimensional Elastic Augmented-reality Robot-assisted Radical Prostatectomy Using Hyperaccuracy Three-dimensional Reconstruction Technology: A Step Further in the Identification of Capsular Involvement

Reduction of surgical complications via 3D models during robotic assisted radical prostatectomy: review of current evidence and meta-analysis

The use of 3-dimensional (3D) technology has become increasingly popular across different surgical specialities to improve surgical outcomes. 3D technology has the potential to be applied to robotic assisted radical prostatectomy to visualise the patient's prostate anatomy to be used as a preoperative and peri operative surgical guide. This literature review aims to analyse all relevant pre-existing research on this topic. Following PRISMA guidelines, a search was carried out on PubMed, Medline, and Scopus. A total of seven studies were included in this literature review; two of which used printed-3D models and the remaining five using virtual augmented reality (AR) 3D models. Results displayed variation with select studies presenting that the use of 3D models enhances surgical outcomes and reduces complications whilst others displayed conflicting evidence. The use of 3D modelling within surgery has potential to improve various areas. This includes the potential surgical outcomes, including complication rates, due to improved planning and education.

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.

Intraoperative technologies to assess margin status during radical prostatectomy - a narrative review

Positive surgical margin (PSM) is a frequent concern for surgeons performing radical prostatectomy for prostate cancer (PCa). PSM are recognized as risk factors for earlier biochemical recurrence and expose patients to adjuvant or salvage treatments such as external radiotherapy and hormonotherapy. Several strategies have been established to reduce PSM rate, while still allowing safe nerve-sparing surgery. Precise preoperative staging by multiparametric magnetic resonance imaging (mpMRI) and fusion biopsy is recommended to identify suspicious areas of extracapsular extension (ECE) that warrant special attention during dissection. However, even with optimal imaging, ECE can be missed, some cancers are not well defined or visible, and capsular incision during surgery remains an issue. Hence, intraoperative frozen section techniques, such as the neurovascular structure-adjacent frozen section examination (NeuroSAFE) have been developed and lately widely disseminated. The NeuroSAFE technique reduces PSM rate while allowing higher rate of nerve-sparing surgery. However, its use is limited to high volume or expert center because of its high barrier-to-entry in terms of logistics, human resources and expertise, as well as cost. Also, NeuroSAFE is a time-consuming process, even in expert hands. To address these issues, several technologies have been developed for an ex vivo and in vivo use. Ex vivo technology such as fluorescent confocal microscopy and intraoperative PET-CT require the extraction of the specimen for preparation, and digital images acquisition. In vivo technology, such as augmented reality based on mpMRI images and PSMA-fluorescent guided surgery have the advantage to provide an intracorporeal analysis of the completeness of the resection. The current manuscript provides a narrative review of established techniques, and details several new and promising techniques for intraoperative PSM assessment.

Evaluation of margins during radical prostatectomy: confocal microscopy vs frozen section analysis

OBJECTIVES

To test the performance of ex vivo fluorescence confocal microscopy (FCM; Vivascope 2500M-G4), as compared to intra-operative frozen section (IFS) analysis, to evaluate surgical margins during robot-assisted radical prostatectomy (RARP), with final pathology as the reference standard.

METHODS

Overall, 54 margins in 45 patients treated with RARP were analysed with: (1) ex vivo FCM; (2) IFS analysis; and (3) final pathology. FCM margins were evaluated by two different pathologists (experienced [M.I.: 10 years] vs highly experienced [G.R.: >30 years]) as strongly negative, probably negative, doubtful, probably positive, or strongly positive. First, inter-observer agreement (Cohen's κ) between pathologists was tested. Second, we reported the sensitivity, specificity, positive predictive (PPV) and negative predictive value (NPV) of ex vivo FCM. Finally, agreement between ex vivo FCM and IFS analysis (Cohen's κ) was reported. For all analyses, four combinations of FCM results were evaluated.

RESULTS

At ex vivo FCM, the inter-observer agreement between pathologists ranged from moderate (κ = 0.74) to almost perfect (κ = 0.90), according to the four categories of results. Indeed, at ex vivo FCM, the highly experienced pathologist reached the best balance between sensitivity (70.5%) specificity (91.8%), PPV (80.0%) and NPV (87.1%). Conversely, on IFS analysis, the sensitivity, specificity, PPV and NPV were, respectively, 88.2% vs 100% vs 100% vs 94.8%. The agreement between the ex vivo FCM and IFS analyses ranged from moderate (κ = 0.62) to strong (κ = 0.86), according to the four categories of results.

CONCLUSION

Evaluation of prostate margins at ex vivo FCM appears to be feasible and reliable. The agreement between readers encourages its widespread use in daily practice. Nevertheless, as of today, the performance of FCM seems to be sub-par when compared to the established standard of care (IFS analysis).

Artificial Intelligence in Urologic Robotic Oncologic Surgery: A Narrative Review

With the rapid increase in computer processing capacity over the past two decades, machine learning techniques have been applied in many sectors of daily life. Machine learning in therapeutic settings is also gaining popularity. We analysed current studies on machine learning in robotic urologic surgery. We searched PubMed/Medline and Google Scholar up to December 2023. Search terms included "urologic surgery", "artificial intelligence", "machine learning", "neural network", "automation", and "robotic surgery". Automatic preoperative imaging, intraoperative anatomy matching, and bleeding prediction has been a major focus. Early artificial intelligence (AI) therapeutic outcomes are promising. Robot-assisted surgery provides precise telemetry data and a cutting-edge viewing console to analyse and improve AI integration in surgery. Machine learning enhances surgical skill feedback, procedure effectiveness, surgical guidance, and postoperative prediction. Tension-sensors on robotic arms and augmented reality can improve surgery. This provides real-time organ motion monitoring, improving precision and accuracy. As datasets develop and electronic health records are used more and more, these technologies will become more effective and useful. AI in robotic surgery is intended to improve surgical training and experience. Both seek precision to improve surgical care. AI in ''master-slave'' robotic surgery offers the detailed, step-by-step examination of autonomous robotic treatments.

Automatic 3D Augmented-Reality Robot-Assisted Partial Nephrectomy Using Machine Learning: Our Pioneer Experience

The aim of "Precision Surgery" is to reduce the impact of surgeries on patients' global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called "ikidney", based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6-13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process.

Targeted augmented reality-guided transperineal prostate biopsies study: initial experience

Background

Transperineal biopsy of magnetic resonance imaging (MRI)-detected prostate lesions is now the established technique used in prostate cancer (CaP) diagnostics. Virtual Surgery Intelligence (VSI) Holomedicine by Apoqlar (Hamburg, Germany) is a mixed reality (MR)/augmented reality (AR) software platform that runs on the HoloLens II system (Microsoft, Redford, USA). Multiparametric prostate MRI images were converted into 3D holograms and added into a MR space, enabling visualization of a 3D hologram and image-assisted prostate biopsy.

Objective

The Targeted Augmented Reality-GuidEd Transperineal (TARGET) study investigated the feasibility of performing AR-guided prostate biopsies in a MR framework, using the VSI platform in patients with MRI-detected prostate lesions.

Methods

Ten patients with a clinical suspicion of CaP on MRI (Prostate Imaging-Reporting and Data System, PI-RADS 4/5) were uploaded to the VSI HoloLens system. Two MR/AR-guided prostate biopsies were then acquired using the PrecisionPoint Freehand transperineal biopsy system. Cognitive fusion biopsies were performed as standard of care following the MR/AR-guided prostate biopsies.

Results

All 10 patients successfully underwent MR/AR-guided prostate biopsy after 3D MR images were overlaid on the patient's body. Prostatic tissue was obtained in all MR/AR-guided specimens. Seven patients (70%) had matching histology in both the standard and MR/AR-guided biopsies. The remaining three had ISUP (International Society of Urological Pathology) Grade 2 CaP. There were no immediate complications.

Conclusion

We believe this is a world first. The initial feasibility data from the TARGET study demonstrated that an MR/AR-guided prostate biopsy utilizing the VSI Holomedicine system is a viable option in CaP diagnostics. The next stage in development is to combine AR images with real-time needle insertion and to provide further data to formally appraise the sensitivity and specificity of the technique.

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.

A new mixed reality tool for training in minimally invasive robotic-assisted surgery

Robotic-assisted surgery (RAS) is developing an increasing role in surgical practice. Therefore, it is of the utmost importance to introduce this paradigm into surgical training programs. However, the steep learning curve of RAS remains a problem that hinders the development and widespread use of this surgical paradigm. For this reason, it is important to be able to train surgeons in the use of RAS procedures. RAS involves distinctive features that makes its learning different to other minimally invasive surgical procedures. One of these features is that the surgeons operate using a stereoscopic console. Therefore, it is necessary to perform RAS training stereoscopically. This article presents a mixed-reality (MR) tool for the stereoscopic visualization, annotation and collaborative display of RAS surgical procedures. The tool is an MR application because it can display real stereoscopic content and augment it with virtual elements (annotations) properly registered in 3D and tracked over time. This new tool allows the registration of surgical procedures, teachers (experts) and students (trainees), so that the teacher can share a set of videos with their students, annotate them with virtual information and use a shared virtual pointer with the students. The students can visualize the videos within a web environment using their personal mobile phones or a desktop stereo system. The use of the tool has been assessed by a group of 15 surgeons during a robotic-surgery master's course. The results show that surgeons consider that this tool can be very useful in RAS training.

Three-dimensional automatic artificial intelligence driven augmented-reality selective biopsy during nerve-sparing robot-assisted radical prostatectomy: A feasibility and accuracy study

Objective

To evaluate the accuracy of our new three-dimensional (3D) automatic augmented reality (AAR) system guided by artificial intelligence in the identification of tumour's location at the level of the preserved neurovascular bundle (NVB) at the end of the extirpative phase of nerve-sparing robot-assisted radical prostatectomy.

Methods

In this prospective study, we enrolled patients with prostate cancer (clinical stages cT1c-3, cN0, and cM0) with a positive index lesion at target biopsy, suspicious for capsular contact or extracapsular extension at preoperative multiparametric magnetic resonance imaging. Patients underwent robot-assisted radical prostatectomy at San Luigi Gonzaga Hospital (Orbassano, Turin, Italy), from December 2020 to December 2021. At the end of extirpative phase, thanks to our new AAR artificial intelligence driven system, the virtual prostate 3D model allowed to identify the tumour's location at the level of the preserved NVB and to perform a selective excisional biopsy, sparing the remaining portion of the bundle. Perioperative and postoperative data were evaluated, especially focusing on the positive surgical margin (PSM) rates, potency, continence recovery, and biochemical recurrence.

Results

Thirty-four patients were enrolled. In 15 (44.1%) cases, the target lesion was in contact with the prostatic capsule at multiparametric magnetic resonance imaging (Wheeler grade L2) while in 19 (55.9%) cases extracapsular extension was detected (Wheeler grade L3). 3D AAR guided biopsies were negative in all pathological tumour stage 2 (pT2) patients while they revealed the presence of cancer in 14 cases in the pT3 cohort (14/16; 87.5%). PSM rates were 0% and 7.1% in the pathological stages pT2 and pT3 (<3 mm, Gleason score 3), respectively.

Conclusion

With the proposed 3D AAR system, it is possible to correctly identify the lesion's location on the NVB in 87.5% of pT3 patients and perform a 3D-guided tailored nerve-sparing even in locally advanced diseases, without compromising the oncological safety in terms of PSM rates.

A Systematic Review of New Imaging Technologies for Robotic Prostatectomy: From Molecular Imaging to Augmented Reality

New imaging technologies play a pivotal role in the current management of patients with prostate cancer. Robotic assisted radical prostatectomy (RARP) is a standard of care for localized disease and through the already imaging-based console subject of research towards combinations of imaging technologies and RARP as well as their impact on surgical outcomes. Therefore, we aimed to provide a comprehensive analysis of the currently available literature for new imaging technologies for RARP. On 24 January 2023, we performed a systematic review of the current literature on Pubmed, Scopus and Web of Science according to the PRISMA guidelines and Oxford levels of evidence. A total of 46 studies were identified of which 19 studies focus on imaging of the primary tumor, 12 studies on the intraoperative tumor detection of lymph nodes and 15 studies on the training of surgeons. While the feasibility of combined approaches using new imaging technologies including MRI, PSMA-PET CT or intraoperatively applied radioactive and fluorescent dyes has been demonstrated, the prospective confirmation of improvements in surgical outcomes is currently ongoing.

Robotic-assisted versus laparoscopic radical prostatectomy for prostate cancer: the first separate systematic review and meta-analysis of randomised controlled trials and non-randomised studies

BACKGROUND

Due to the lack of sufficient evidence, it is not clear whether robotic-assisted radical prostatectomy (RARP) or laparoscopic radical prostatectomy (LRP) is better for prostate cancer. The authors conducted this study by separately pooling and analysing randomised controlled trials (RCTs) and non-randomised studies to compare the perioperative, functional, and oncologic outcomes between RARP and LRP.

METHODS

A systematic literature search was performed in March 2022 using Cochrane Library, Pubmed, Embase, Medline, Web of Science, and China National Knowledge Infrastructure. Two independent reviewers performed literature screening, data extraction and quality assessment according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement. Subgroup analysis and sensitivity analysis were performed.

RESULTS

A total of 46 articles were included, including 4 from 3 RCTs and 42 from non-randomised studies. For RCTs, meta-analysis showed that RARP and LRP were similar in blood loss, catheter indwelling time, overall complication rate, overall positive surgical margin and biochemical recurrence rates, but quantitative synthesis of non-randomised studies showed that RARP was associated with less blood loss [weighted mean difference (WMD)=-71.99, 95% CI -99.37 to -44.61, P <0.001], shorter catheterization duration (WMD=-1.03, 95% CI -1.84 to -0.22, P =0.010), shorter hospital stay (WMD=-0.41, 95% CI -0.68 to -0.13, P =0.004), lower transfusion rate (OR=0.44, 95% CI 0.35-0.56, P <0.001), lower overall complication rate (OR=0.72, 95% CI 0.54-0.96, P =0.020), and lower biochemical recurrence rate (OR=0.78, 95% CI 0.66-0.92, P =0.004), compared with LRP. Both meta-analysis of RCTs and quantitative synthesis of non-randomised studies showed that RARP was associated with improved functional outcomes. From the results of the meta-analysis of RCTs, RARP was higher than LRP in terms of overall continence recovery [odds ratio (OR)=1.60, 95% CI 1.16-2.20, P =0.004), overall erectile function recovery (OR=4.07, 95% CI 2.51-6.60, P <0.001), continence recovery at 1 month (OR=2.14, 95% CI 1.25-3.66, P =0.005), 3 (OR=1.51, 95% CI 1.12-2.02, P =0.006), 6 (OR=2.66, 95% CI 1.31-5.40, P =0.007), and 12 months (OR=3.52, 95% CI 1.36-9.13, P =0.010) postoperatively, and potency recovery at 3 (OR=4.25, 95% CI 1.67-10.82, P =0.002), 6 (OR=3.52, 95% CI 1.31-9.44, P =0.010), and 12 months (OR=3.59, 95% CI 1.78-7.27, P <0.001) postoperatively, which were consistent with the quantitative synthesis of non-randomised studies. When sensitivity analysis was performed, the results remained largely unchanged, but the heterogeneity among studies was greatly reduced.

CONCLUSION

This study suggests that RARP can improve functional outcomes compared with LRP. Meanwhile, RARP has potential advantages in perioperative and oncologic outcomes.

3D-Reconstructed Contact Surface Area and Tumour Volume on Magnetic Resonance Imaging Improve the Prediction of Extraprostatic Extension of Prostate Cancer

This study is to determine whether the volume and contact surface area (CSA) of a tumour with an adjacent prostate capsule on MRI in a three-dimensional (3D) model that can predict side-specific extraprostatic extension (EPE) at radical prostatectomy (RP). Patients with localised prostate cancer (PCa) who underwent robot-assisted RP between July 2015 and March 2021 were included in this retrospective study. MRI-based 3D prostate models incorporating the PCa volume and location were reconstructed. The tumour volume and surface variables were extracted. For the prostate-to-tumour and tumour-to-prostate CSAs, the areas in which the distances were ≤ 1, ≤ 2, ≤ 3, ≤ 4, and ≤ 5 mm were defined, and their surface (cm2) were determined. Differences in prostate sides with and without pathological EPE were analysed. Multivariable logistic regression analysis to find independent predictors of EPE. Overall, 75/302 (25%) prostate sides showed pathological EPE. Prostate sides with EPE had higher cT-stage, higher PSA density, higher percentage of positive biopsy cores, higher biopsy Gleason scores, higher radiological tumour stage, larger tumour volumes, larger prostate CSA, and larger tumour CSA (all p < 0.001). Multivariable logistic regression analysis showed that the radiological tumour stage (p = 0.001), tumour volume (p < 0.001), prostate CSA (p < 0.001), and tumour CSA (p ≤ 0.001) were independent predictors of pathological EPE. A 3D reconstruction of tumour locations in the prostate improves prediction of extraprostatic extension. Tumours with a higher 3D-reconstructed volume, a higher surface area of tumour in contact with the prostate capsule, and higher surface area of prostate capsule in contact with the tumour are at increased risk of side-specific extraprostatic extension.

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.

Prostate MRI for Improving Personalized Risk Prediction of Incontinence and Surgical Planning: The Role of Membranous Urethral Length Measurements and the Use of 3D Models

Prostate MRI has an important role in prostate cancer diagnosis and treatment, including detection, the targeting of prostate biopsies, staging and guiding radiotherapy and active surveillance. However, there are other ''less well-known'' applications which are being studied and frequently used in our highly specialized medical center. In this review, we focus on two research topics that lie within the expertise of this study group: (1) anatomical parameters predicting the risk of urinary incontinence after radical prostatectomy, allowing more personalized shared decision-making, with special emphasis on the membranous urethral length (MUL); (2) the use of three-dimensional models to help the surgical planning. These models may be used for training, patient counselling, personalized estimation of nerve sparing and extracapsular extension and may help to achieve negative surgical margins and undetectable postoperative PSA values.

Impact of 3D printed models on quantitative surgical outcomes for patients undergoing robotic-assisted radical prostatectomy: a cohort study

BACKGROUND

Three-dimensional (3D) printed anatomic models can facilitate presurgical planning by providing surgeons with detailed knowledge of the exact location of pertinent anatomical structures. Although 3D printed anatomic models have been shown to be useful for pre-operative planning, few studies have demonstrated how these models can influence quantitative surgical metrics.

OBJECTIVE

To prospectively assess whether patient-specific 3D printed prostate cancer models can improve quantitative surgical metrics in patients undergoing robotic-assisted radical prostatectomy (RARP).

METHODS

Patients with MRI-visible prostate cancer (PI-RADS V2 ≥ 3) scheduled to undergo RARP were prospectively enrolled in our IRB approved study (n = 82). Quantitative surgical metrics included the rate of positive surgical margins (PSMs), operative times, and blood loss. A qualitative Likert scale survey to assess understanding of anatomy and confidence regarding surgical approach was also implemented.

RESULTS

The rate of PSMs was lower for the 3D printed model group (8.11%) compared to that with imaging only (28.6%), p = 0.128. The 3D printed model group had a 9-min reduction in operating time (213 ± 42 min vs. 222 ± 47 min) and a 5 mL reduction in average blood loss (227 ± 148 mL vs. 232 ± 114 mL). Surgeon anatomical understanding and confidence improved after reviewing the 3D printed models (3.60 ± 0.74 to 4.20 ± 0.56, p = 0.62 and 3.86 ± 0.53 to 4.20 ± 0.56, p = 0.22).

CONCLUSIONS

3D printed prostate cancer models can positively impact quantitative patient outcomes such as PSMs, operative times, and blood loss in patients undergoing RARP.

CT Three-Dimensional Visualization Model in Diagnosis and Treatment of Stress Urinary Incontinence: A Retrospective Study

OBJECTIVE

To study the clinical effect of stress urinary incontinence sling surgery based on CT 3-dimensional visualization model, and to explore the value of three-dimensional visualization model in the diagnosis and treatment of stress urinary incontinence.

METHODS

Patients with stress urinary incontinence in our center from October 2020 to March 2022 were studied retrospectively. Among them, 16 cases received preoperative 3-dimensional visualization model construction, 18 cases did not use preoperative 3-dimensional model construction. The perioperative results, the postoperative results and the correlation between some related parameters of 3-dimensional visualization model and the severity of stress urinary incontinence were analyzed.

RESULTS

Compared with traditional surgery, the operation time of 3D group is significantly shorter (P < 0.05). There was no significant difference in intraoperative blood loss, perioperative fever, bleeding, micturition, pudendal or inguinal pain and postoperative symptom improvement. The posterior vesicourethral angle measured by 3-dimensional reconstruction model was correlated with ICI-Q-SF score.

CONCLUSIONS

The construction of three-dimensional visualization model of stress urinary incontinence can be used in clinic as a safe and effective new preoperative evaluation technique, and more potential applications can be further explored.

Effect of augmented reality navigation technology on perioperative safety in partial nephrectomies: A meta-analysis and systematic review

Aim

To evaluate the impact of augmented reality surgical navigation (ARSN) technology on short-term outcomes of partial nephrectomy (PN).

Methods

A systematic literature search was conducted in PubMed, Embase, Cochrane, and Web of Science for eligible studies published through March 28, 2022. Two researchers independently performed the article screening, data extraction and quality review. Data analysis was performed using Cochrane Review Manager software.

Results

A total of 583 patients from eight studies were included in the analysis, with 313 in the ARSN-assisted PN group (AR group) and 270 in the conventional PN group (NAR group). ARSN-assisted PN showed better outcomes than conventional surgery in terms of operative time, estimated blood loss, global ischemia rate, warm ischemia time, and enucleation rate. However, there were no significant differences in the rate of Conversion to radical nephrectomy (RN), postoperative estimated glomerular filtration rate (eGFR), positive margin rate, and postoperative complication rate.

Conclusion

The utilization of ARSN can improve the perioperative safety of PN. Compared with conventional PN, ARSN-assisted PN can reduce intraoperative blood loss, shorten operative time, and improve renal ischemia. Although direct evidence is lacking, our results still suggest a potential advantage of ARSN in improving renal recovery after PN. However, as the ARSN system is still in an exploratory stage, its relevance in PN have been poorly reported. Additional high-quality randomized controlled trial (RCT) studies will be required to confirm the effect of ARSN on PN.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=301798, identifier PROSPERO ID: CRD42022301798.

Intraoperative 3D-US-mpMRI Elastic Fusion Imaging-Guided Robotic Radical Prostatectomy: A Pilot Study

INTRODUCTION

When performing a nerve-sparing (NS) robotic radical prostatectomy (RARP), cancer location based on multiparametric MRI (mpMRI) is essential, as well as the location of positive biopsy cores outside mpMRI targets. The aim of this pilot study was to assess the feasibility of intraoperative 3D-TRUS-mpMRI elastic fusion imaging to guide RARP and to evaluate its impact on the surgical strategy.

METHODS

We prospectively enrolled 11 patients with organ-confined mpMRI-visible prostate cancer (PCa), histologically confirmed at transperineal fusion biopsy using Koelis Trinity. Before surgery, the 3D model of the prostate generated at biopsy was updated, showing both mpMRI lesions and positive biopsy cores, and was displayed on the Da Vinci robotic console using TilePro™ function.

RESULTS

Intraoperative 3D modeling was feasible in all patients (median of 6 min). The use of 3D models led to a major change in surgical strategy in six cases (54%), allowing bilateral instead of monolateral NS, or monolateral NS instead of non-NS, to be performed. At pathologic examination, no positive surgical margins (PSMs) were reported. Bilateral PCa presence was detected in one (9%), four (36%), and nine (81%) patients after mpMRI, biopsy, and RARP, respectively. Extracapsular extension was found in two patients (18%) even if it was not suspected at MRI.

CONCLUSIONS

Intraoperative 3D-TRUS-mpMRI modeling with Koelis Trinity is feasible and reliable, helping the surgeon to maximize functional outcomes without increasing the risk of positive surgical margins. The location of positive biopsy cores must be registered in 3D models, given the rates of bilateral involvement not seen at mpMRI.

Three-dimensional Augmented Reality-guided Robotic-assisted Kidney Transplantation: Breaking the Limit of Atheromatic Plaques

BACKGROUND

Robotic-assisted kidney transplantation (RAKT) has shown solid results as a minimally invasive alternative to the standard open approach (open kidney transplantation [OKT]). However, RAKT is still limited in those cases where the recipient's iliac vessels present atherosclerotic plaques, frequently found in elder patients and in those subjected to long-term hemodialysis. Unlike OKT, where the surgeon can palpate the arterial plaques, in minimally invasive surgery the haptic feedback is missing, making the vascular clamping and arteriotomy unsafe.

OBJECTIVE

To employ three-dimensional (3D) imaging reconstruction using augmented reality (AR) to intraoperatively locate the plaques during the crucial steps of kidney transplantation.

DESIGN, SETTING, AND PARTICIPANTS

Our study was conducted according to the Idea, Development, Exploration, Assessment, and Long-term follow-up (IDEAL) model for surgical innovation. Three-dimensional virtual models were obtained from high-accuracy computed tomography scan imaging and superimposed on the vessels during RAKT using the Da Vinci console software.

SURGICAL PROCEDURE

Three-dimensional AR-guided robotic-assisted kidney transplantation.

MEASUREMENTS

The correspondence of virtual models with the real anatomy of patients was assessed comparing vessels' and plaques' measures.

RESULTS AND LIMITATIONS

We tested the possibility of using the AR in the setting of vascular surgery by checking the correspondence of the virtual models to the real vessels. During the accuracy assessment, we investigated the anatomy of the iliac plaques and the capacity of the virtual models to correctly represent them. Finally, we tested the efficacy of the virtual model superimposition on the real vessels with plaques during RAKT in the recipients of living donor grafts. The main limitation consists in training needed to correctly superimpose virtual models on the real field.

CONCLUSIONS

The employment of 3D AR allowed surgeons to overcome one of the main limitations of RAKT, setting the foundation to expand its indications to patients with advanced atheromatic vascular disease.

PATIENT SUMMARY

The use of three-dimensional augmented reality guidance during kidney transplantation (KT) has the potential to "navigate" the surgeon during KT, allowing a safer procedure in patients with atheromatic vascular disease.

Development and clinical applicability of MRI-based 3D prostate models in the planning of nerve-sparing robot-assisted radical prostatectomy

The interpretation of conventional MRI may be limited by the two-dimensional presentation of the images. To develop patient-specific MRI prostate-based virtual and three-dimensional (3D)-printed models. To assess the association between 3D imaging and the pathological outcome of RARP specimen. To assess the clinical applicability of 3D models to guide nerve-sparing robot-assisted radical prostatectomy (RARP). We created virtual 3D and 3D-printed 3D models of 20 prostate cancer patients retrospectively. A comparison was made between conventional MRI and 3D-reconstructed images. The concordance between tumour lesion location in 3D models and pathology reporting of RARP specimens was assessed. Seven urologists assessed the side-specific extent of nerve-sparing based on (1) conventional MR images, (2) virtual 3D models, and (3) 3D-printed models. Clinically relevant changes in nerve-sparing and the absolute agreement between observers was analyzed using the Chi-square test and intra-class correlation coefficient (ICC). The index lesion was correctly visualized in 19/20 (95%) 3D models and the expected location of extraprostatic extension was correctly visualized in all 3D models. Clinically relevant changes in the planned extent of nerve-sparing between MRI and virtual 3D models and MRI and 3D-printed models were found in 25% and 26%. The ICC of the planned extent of nerve-sparing between urologists was 0.40 (95% CI 0.28-0.55) for conventional MRI, 0.52 (95% CI 0.39-0.66) for virtual 3D models and 0.58 (95% CI 0.45-0.71) for 3D-printed models. 3D models of the MRI prostate to guide RARP could aid urologists in the planning of nerve-sparing surgery as shown by a higher inter-observer agreement.

The impact of 3D models on positive surgical margins after robot-assisted radical prostatectomy

PURPOSE

To evaluate the role of 3D models on positive surgical margin rate (PSM) rate in patients who underwent robot-assisted radical prostatectomy (RARP) compared to a no-3D control group. Secondarily, we evaluated the postoperative functional and oncological outcomes.

METHODS

Prospective study enrolling patients with localized prostate cancer (PCa) undergoing RARP with mp-MRI-based 3D model reconstruction, displayed in a cognitive or augmented-reality fashion, at our Centre from 01/2016 to 01/2020. A control no-3D group was extracted from the last two years of our Institutional RARP database. PSMr between the two groups was evaluated and multivariable linear regression (MLR) models were applied. Finally, Kaplan-Meier estimator was used to calculate biochemical recurrence at 12 months after the intervention.

RESULTS

160 patients were enrolled in the 3D Group, while 640 were selected for the Control Group. A more conservative NS approach was registered in the 3D Group (full NS 20.6% vs 12.7%; intermediate NS 38.1% vs 38.0%; standard NS 41.2% vs 49.2%; p = 0.02). 3D Group patients had lower PSM rates (25 vs. 35.1%, p = 0.01). At MLR models, the availability of 3D technology (p = 0.005) and the absence of extracapsular extension (ECE, p = 0.004) at mp-MRI were independent predictors of lower PSMr. Moreover, 3D model represented a significant protective factor for PSM in patients with ECE or pT3 disease.

CONCLUSION

The availability of 3D models during the intervention allows to modulate the NS approach, limiting the occurrence of PSM, especially in patients with ECE at mp-MRI or pT3 PCa.

Autonomous Bionanorobots via a Cage-Shaped Silsesquioxane Vehicle for In Vivo Heavy Metal Detoxification

Nanorobots hold great promise for integrated drug delivery systems that are responsive to molecular triggers. Herein, we successfully developed an automatic smart bionanorobot that has transport capability and recognizes and removes zinc ions from poisoned cells based on nanoscale polyhedral oligomeric silsesquioxane molecules. This intelligent bionanorobot can easily move inside and outside the cell and find zinc ions owing to its highly selective recognition to zinc ions and high cell permeability, especially the well-combined high penetration and strong binding energy. More importantly, it was also found that this intelligent bionanorobot can restore round HeLa cells to a normal fusiform cell morphology following high-concentration zinc treatment and does not interfere with cell proliferation and division. It was also shown by in vivo experiments that the bionanorobot can inhibit persistent enlargement of the liver caused by zinc ion poisoning.

A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery

Introduction

The current study presents a deep learning framework to determine, in real‐time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The resulting augmented video flow is streamed back to the surgeon as a support during laparoscopic robot‐assisted procedures.

Methods

This framework exploits semantic segmentation and, thereafter, two techniques, based on Convolutional Neural Networks and motion analysis, were used to infer the rotation.

Results

The segmentation shows optimal accuracies, with a mean IoU score greater than 80% in all tests. Different performance levels are obtained for rotation, depending on the surgical procedure.

Discussion

Even if the presented methodology has various degrees of precision depending on the testing scenario, this work sets the first step for the adoption of deep learning and augmented reality to generalise the automatic registration process.

Combination of holographic imaging with robotic partial nephrectomy for renal hilar tumor treatment

OBJECTIVES

To evaluate the clinical value of the holographic imaging technology in combination with robotic-assisted partial nephrectomy (RAPN) for renal hilar tumor treatment.

PATIENTS AND METHODS

From Dec. 2018 to Dec. 2021, patients diagnosed with renal hilar tumor were included in this retrospective study. Before the surgery, the engineers established the holographic image models based on the enhanced CT data. The models were used in patient consultation, pre-surgery planning and surgery simulation. During the RAPN, the navigation was achieved by real-time overlapping of the holographic images on the robotic surgery endoscopic views. The navigation technique helped the surgeon to identify the important anatomic structures such as tumor, renal vein, renal artery, and pelvis.

RESULTS

There were total of eight patients with renal hilar tumor who underwent RAPN combined with holographic imaging technique. The mean age was 57.3 years, the median ASA score was 2. The mean tumor size was 42.4 mm and the median RENAL Nephrometry score was 9.5. The clinical stages were cT1a (37.5%) and cT1b (62.5%). All the procedures were performed uneventfully by one surgeon. The mean operative time was 144.3 min, and the mean warm ischemia time was 27.9 min. The mean estimated blood loss was 86.3 ml. There was no conversion to open surgery or radical nephrectomy. There were no Clavien-Dindo ≥ 3 perioperative complications.

CONCLUSIONS

Using the holographic imaging technique, the pre-surgery planning, simulation of renal arterial clamp and excision of the tumor, and intraoperative navigation were feasible and helpful in facilitating RAPN.

Application of a three-dimensional visualization model in intraoperative guidance of percutaneous nephrolithotomy

OBJECTIVES

To establish a three-dimensional visualization model of percutaneous nephrolithotomy, apply it to guiding intraoperative puncture in a mixed reality environment, and evaluate its accuracy and clinical value.

METHODS

Patients with percutaneous nephrolithotomy indications were prospectively divided into three-dimensional group and control group with a ratio of 1:2. For patients in three-dimensional group, positioning markers were pasted on the skin and enhanced computed tomography scanning was performed in the prone position. Holographic three-dimensional models were made and puncture routes were planned before operation. During the operation, the three-dimensional model was displayed through HoloLens glass and visually registered with the patient's body. Puncture of the target renal calyx was performed under three-dimensional-image guiding and ultrasonic monitoring. Patients in the control group underwent routine percutaneous nephrolithotomy in the prone position under the monitoring of B-ultrasound. Deviation distance of the kidney, puncture time, puncture attempts, channel coincidence rate, stone clearance rate, and postoperative complications were assessed.

RESULTS

Twenty-one and 40 patients were enrolled in three-dimensional and control group, respectively. For three-dimensional group, the average deviation between virtual and real kidney was 3.1 ± 2.9 mm. All punctures were performed according to preoperative planning. Compared with the control group, the three-dimensional group had shorter puncture time (8.9 ± 3.3 vs 14.5 ± 6.1 min, P < 0.001), fewer puncture attempts (1.4 ± 0.6 vs 2.2 ± 1.5, P = 0.009), and might also have a better performance in stone clearance rate (90.5% vs 72.5%, P = 0.19) and postoperative complications (P = 0.074).

CONCLUSIONS

The percutaneous nephrolithotomy three-dimensional model manifested acceptable accuracy and good value for guiding puncture in a mixed reality environment.

"Augmented reality" applications in urology: a systematic review

INTRODUCTION

Augmented reality (AR) applied to surgical procedures refers to the superimposition of preoperative or intra-operative images onto the operative field. Augmented reality has been increasingly used in myriad surgical specialties including Urology. The following study reviews advances in the use of AR for improvements in urologic outcomes.

EVIDENCE ACQUISITION

We identified all descriptive, validity, prospective randomized/nonrandomized trials and retrospective comparative/noncomparative studies about the use of AR in Urology up until March 2021. The MEDLINE, Scopus, and Web of Science databases were used for literature search. We conducted the study selection according to the PRISMA (Preferred Reporting Items for Systematic Reviews and meta-analysis statement) guidelines. We limited included studies to only those using AR, excluding all that used virtual reality technology.

EVIDENCE SYNTHESIS

A total of 60 studies were identified and included in the present analysis. Overall, 19 studies were descriptive/validity/phantom studies for specific AR methodologies, 4 studies were case reports, and 37 studies included clinical prospective/retrospective comparative studies.

CONCLUSIONS

Advances in AR have led to increasing registration accuracy as well as increased ability to identify anatomic landmarks and improve outcomes during Urologic procedures such as RARP and robot-assisted partial nephrectomy.

Prediction of surgical margin status and location after radical prostatectomy using positive biopsy sites on 12-core standard prostate biopsy

We evaluated the surgical margin status after radical prostatectomy according to sites positive for prostate cancer on standard 12-core transrectal ultrasound-guided prostate biopsy. Among patients who underwent radical prostatectomy at Boramae Medical Center, 520 patients with preoperative prostate-specific antigen (PSA) level < 20 ng/mL and locally confined prostate cancer on preoperative magnetic resonance imaging, treated with nerve-sparing radical prostatectomy, were included in the analysis. The surgical margin was positive for cancer in 166 (31.9% of the total) patients. The preoperative PSA level (9.3 vs. 8.0, ng/mL p = 0.001) and number of positive cores on 12-core prostate biopsy (4.1 vs. 3.4, p = 0.003) were significantly higher in patients with positive surgical margins. Moreover, the biopsy Gleason grade was higher in patients with positive surgical margins (p = 0.001). However, the pathologic Gleason grade and tumor volume were equivalent between the 2 groups. On multivariate analysis, the detection of prostate cancer on anterior lateral biopsy was associated with an increased rate of positive surgical margins (hazard ratio [HR]: 1.781, p = 0.008) after adjusting for other variables. Anterior lateral (HR: 1.919, p = 0.020), basal lateral (HR: 9.176, p < 0.001), basal medial (HR: 3.302, p = 0.031), and mid lateral (HR: 2.501, p = 0.044) biopsies were associated with positive apical, posterior, basal, and lateral surgical margins, respectively, after adjusting for other variables. The sites of prostate cancer on standard 12-core prostate biopsy could be useful for predicting surgical margin positivity after radical prostatectomy. In other words, clinicians should consider the sites of prostate cancer on prostate biopsy to reduce margin positivity after radical prostatectomy.

A Platform and Multisided Market for Translational, Software-Defined Medical Procedures in the Operating Room (OP 4.1): Proof-of-Concept Study

Background

Although digital and data-based technologies are widespread in various industries in the context of Industry 4.0, the use of smart connected devices in health care is still in its infancy. Innovative solutions for the medical environment are affected by difficult access to medical device data and high barriers to market entry because of proprietary systems.

Objective

In the proof-of-concept project OP 4.1, we show the business viability of connecting and augmenting medical devices and data through software add-ons by giving companies a technical and commercial platform for the development, implementation, distribution, and billing of innovative software solutions.

Methods

The creation of a central platform prototype requires the collaboration of several independent market contenders, including medical users, software developers, medical device manufacturers, and platform providers. A dedicated consortium of clinical and scientific partners as well as industry partners was set up.

Results

We demonstrate the successful development of the prototype of a user-centric, open, and extensible platform for the intelligent support of processes starting with the operating room. By connecting heterogeneous data sources and medical devices from different manufacturers and making them accessible for software developers and medical users, the cloud-based platform OP 4.1 enables the augmentation of medical devices and procedures through software-based solutions. The platform also allows for the demand-oriented billing of apps and medical devices, thus permitting software-based solutions to fast-track their economic development and become commercially successful.

Conclusions

The technology and business platform OP 4.1 creates a multisided market for the successful development, implementation, distribution, and billing of new software solutions in the operating room and in the health care sector in general. Consequently, software-based medical innovation can be translated into clinical routine quickly, efficiently, and cost-effectively, optimizing the treatment of patients through smartly assisted procedures.

Three-dimensional Model Reconstruction: The Need for Standardization to Drive Tailored Surgery

The clinical utility of three-dimensional virtual models has been widely explored for preoperative planning, patient counseling, surgical training, and intraoperative navigation. There is now a need for standardized methodology for construction of these models so that their utility can be realized in routine practice to achieve the goal of individualized treatment for patients.

Virtual reality of three-dimensional surgical field for surgical planning and intraoperative management

PURPOSE

To investigate the impact of virtual reality (VR) technologies on urological surgeries, specifically in the management of prostate cancer and renal cancer.

METHODS

A non-systematic review of the literature was performed. Medline, Pubmed, and the Cochrane Database were screened for studies regarding the use of VR technologies in the management of prostate and renal cancer.

RESULTS

In the management of prostate cancer, VR technologies have been increasingly applied for diagnosis with magnetic resonance imaging/ultrasound fusion biopsy, surgical training using a simulator, surgical navigation in robot-assisted radical prostatectomy, and targeted focal therapy. In partial nephrectomy, surgical simulation and intra-surgical guidance with three-dimensional VR have been used for better understanding of the hilar vascular information, tumor location, and positional relationships of the tumor-feeding vessel and pyelocaliceal system.

CONCLUSIONS

VR contributes to the education, training, and simulation of surgical procedures as well as helping the surgeons to tailor surgical planning on each patient. Further prospective studies are needed to assess the beneficial impacts of this technology for both the physician and patient by objective parameters.

Selection of patients for nerve sparing surgery in robot‐assisted radical prostatectomy

Context

Robot‐assisted radical prostatectomy (RARP) has become the standard surgical procedure for localized prostate‐cancer (PCa). Nerve‐sparing surgery (NSS) during RARP has been associated with improved erectile function and continence rates after surgery. However, it remains unclear what are the most appropriate indications for NSS.

Objective

The objective of this study is to systematically review the available parameters for selection of patients for NSS. The weight of different clinical variables, multiparametric magnetic‐resonance‐imaging (mpMRI) findings, and the impact of multiparametric‐nomograms in the decision‐making process on (side‐specific) NSS were assessed.

Evidence acquisition

This systematic review searched relevant databases and included studies performed from January 2000 until December 2020 and recruited a total of 15 840 PCa patients. Studies were assessed that defined criteria for (side‐specific) NSS and associated them with oncological safety and/or functional outcomes. Risk of bias assessment was performed.

Evidence synthesis

Nineteen articles were eligible for full‐text review. NSS is primarily recommended in men with adequate erectile function, and with low‐risk of extracapsular extension (ECE) on the side‐of NSS. Separate clinical and radiological variables have low accuracy for predicting ECE, whereas nomograms optimize the risk‐stratification and decision‐making process to perform or to refrain from NSS when oncological safety (organ‐confined disease, PSM rates) and functional outcomes (erectile function and continence rates) were assessed.

Conclusions

Consensus exists that patients who are at high risk of ECE should refrain from NSS. Several multiparametric preoperative nomograms were developed to predict ECE with increased accuracy compared with single clinical, pathological, or radiological variables, but controversy exists on risk thresholds and decision rules on a conservative versus a less‐conservative surgical approach. An individual clinical judgment on the possibilities of NSS set against the risks of ECE is warranted.

Patient summary

NSS is aimed at sparing the nerves responsible for erection. NSS may lead to unfavorable tumor control if the risk of capsule penetration is high. Nomograms predicting extraprostatic tumor‐growth are probably most helpful.

The Role of 3D Models Obtained from Multiparametric Prostate MRI in Performing Robotic Prostatectomy

BACKGROUND

mpMRI can provide important information for surgical planning, yet its interpretation is not immediate and imaging consultation at the time of surgery can result in interruptions and delay. The use of 3D models based on mpMRI, might obviate these issues. We aimed to evaluate the role of the prospective integration of 3D models from mpMRI in the robotic console in reducing the rate of PSMs.

MATERIAL AND METHODS

PSMs at our center are evaluated intraoperatively using the NeuroSAFE method. Based on the rate of PSMs on frozen section during the year prior to the implementation of 3D models during surgery (22.5%), we estimated that 151 subjects were needed to detect a statistically significant difference of at least 40%. Patients with biopsy-proven PCa who received a 3T mpMRI at our institution and had a PIRADS≥3 on mpMRI were included.

RESULTS

151 patients were included. Overall, 17(11.3%) patients had a PSM, 6(35%) of them had PSM in an area where the mpMRI did not demonstrate any lesions. The rates of PSMs on both frozen (22.5 vs. 11.3%) and permanent section (13.1 vs. 6.6%) were significantly lower (p≤0.03) compared to the cohort of patients operated during 2018(n=358). No significant differences among clinical characteristics were found between the study cohort and the 2018 cohort (all p>0.05).

CONCLUSIONS

The use of 3D models at the time of surgery was shown to reduce the PSM rate on both frozen and permanent section. Integrating 3D models in the robotic console could lead to improved PCa outcomes.

The evolution of image guidance in robotic-assisted laparoscopic prostatectomy (RALP): a glimpse into the future

OBJECTIVES

To describe the innovative intraoperative technologies emerging to aid surgeons during minimally invasive robotic-assisted laparoscopic prostatectomy.

METHODS

We searched multiple electronic databases reporting on intraoperative imaging and navigation technologies, robotic surgery in combination with 3D modeling and 3D printing used during laparoscopic or robotic-assisted laparoscopic prostatectomy. Additional searches were conducted for articles that considered the role of artificial intelligence and machine learning and their application to robotic surgery. We excluded studies using intraoperative navigation technologies during open radical prostatectomy and studies considering technology to visualize lymph nodes. Intraoperative imaging using either transrectal ultrasonography or augmented reality was associated with a potential decrease in positive surgical margins rates. Improvements in detecting capsular involvement may be seen with augmented reality. The benefit, feasibility and applications of other imaging modalities such as 3D-printed models and optical imaging are discussed.

CONCLUSION

The application of image-guided surgery and robotics has led to the development of promising new intraoperative imaging technologies such as augmented reality, fluorescence imaging, optical coherence tomography, confocal laser endomicroscopy and 3D printing. Currently challenges regarding tissue deformation and automatic tracking of prostate movements remain and there is a paucity in the literature supporting the use of these technologies. Urologic surgeons are encouraged to improve and test these advanced technologies in the clinical arena, preferably with comparative, randomized, trials.

Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance

Purpose

The current study aimed to propose a Deep Learning (DL) and Augmented Reality (AR) based solution for a in-vivo robot-assisted radical prostatectomy (RARP), to improve the precision of a published work from our group. We implemented a two-steps automatic system to align a 3D virtual ad-hoc model of a patient’s organ with its 2D endoscopic image, to assist surgeons during the procedure.

Methods

This approach was carried out using a Convolutional Neural Network (CNN) based structure for semantic segmentation and a subsequent elaboration of the obtained output, which produced the needed parameters for attaching the 3D model. We used a dataset obtained from 5 endoscopic videos (A, B, C, D, E), selected and tagged by our team’s specialists. We then evaluated the most performing couple of segmentation architecture and neural network and tested the overlay performances.

Results

U-Net stood out as the most effecting architectures for segmentation. ResNet and MobileNet obtained similar Intersection over Unit (IoU) results but MobileNet was able to elaborate almost twice operations per seconds. This segmentation technique outperformed the results from the former work, obtaining an average IoU for the catheter of 0.894 (σ = 0.076) compared to 0.339 (σ = 0.195). This modifications lead to an improvement also in the 3D overlay performances, in particular in the Euclidean Distance between the predicted and actual model’s anchor point, from 12.569 (σ= 4.456) to 4.160 (σ = 1.448) and in the Geodesic Distance between the predicted and actual model’s rotations, from 0.266 (σ = 0.131) to 0.169 (σ = 0.073).

Conclusion

This work is a further step through the adoption of DL and AR in the surgery domain. In future works, we will overcome the limits of this approach and finally improve every step of the surgical procedure.

PET- and SPECT-based navigation strategies to advance procedural accuracy in interventional radiology and image-guided surgery

INTRODUCTION

Nuclear medicine has a crucial role in interventional strategies where a combination between the increasing use of targeted radiotracers and intraprocedural detection modalities enable novel, but often complex, targeted procedures in both the fields of interventional radiology and surgery. 3D navigation approaches could assist the interventional radiologist or surgeon in such complex procedures.

EVIDENCE ACQUISITION

This review aimed to provide a comprehensive overview of the current application of computer-assisted navigation strategies based on nuclear imaging to assist in interventional radiology and image-guided surgery. This work starts with a brief overview of the typical navigation workflow from a technical perspective, which is followed by the different clinical applications organized based on their anatomical organ of interest.

EVIDENCE SYNTHESIS

Although many studies have proven the feasibility of PET- and SPECT-based navigation strategies for various clinical applications in both interventional radiology and surgery, the strategies are spread widely in both navigation workflows and clinical indications, evaluated in small patient groups. Hence, no golden standard has yet been established.

CONCLUSIONS

Despite that the clinical outcome is yet to be determined in large patient cohorts, navigation seems to be a promising technology to translate nuclear medicine findings, provided by PET- and SPECT-based molecular imaging, to the intervention and operating room. Interventional Nuclear Medicine (iNM) has an exciting future to come using both PET- and SPECT-based navigation.

NeuroSAFE frozen section during robot-assisted radical prostatectomy: peri-operative and histopathological outcomes from the NeuroSAFE PROOF feasibility randomized controlled trial

OBJECTIVES

To report on the methods, peri-operative outcomes and histopathological concordance between frozen and final section from the NeuroSAFE PROOF feasibility study (NCT03317990).

PATIENTS AND METHODS

Between May 2018 and March 2019, 49 patients at two UK centres underwent robot-assisted radical prostatectomy (RARP). Twenty-five patient were randomized to NeuroSAFE RARP (intervention arm) and 24 to standard RARP (control arm). Frozen section was compared to final paraffin section margin assessment in the 25 patients in the NeuroSAFE arm. Operation timings and complications were collected prospectively in both arms.

RESULTS

Fifty neurovascular bundles (NVBs) from 25 patients in the NeuroSAFE arm were analysed. When analysed by each pathological section (n = 250, average five per side), we noted a sensitivity of 100%, a specificity of 99.2%, and an area under the curve (AUC) of 0.994 (95% confidence interval [CI] 0.985 to 1; P ≤0.001). On an NVB basis (n = 50), sensitivity was 100%, specificity was 92.7%, and the AUC was 0.963 (95% CI 0.914 to 1; P ≤0.001). NeuroSAFE RARP lasted a mean of 3 h 16 min (knife to skin to off table, 95% CI 3 h 2 min-3 h 30 min) compared to 2 h 4 min (95% CI 2 h 2 min-2 h 25 min; P ≤0.001) for standard RARP. There was no morbidity associated with the additional length of operating time on in the NeuroSAFE arm.

CONCLUSION

This feasibility study demonstrates the safety, reproducibility and excellent histopathological concordance of the NeuroSAFE technique in the NeuroSAFE PROOF trial. Although the technique increases the duration of RARP, this does not cause short-term harm. Confirmation of feasibility has led to the opening of the fully powered NeuroSAFE PROOF randomized controlled trial, which is currently under way at four sites in the UK.

Applications of neural networks in urology: a systematic review

PURPOSE OF REVIEW

Over the last decade, major advancements in artificial intelligence technology have emerged and revolutionized the extent to which physicians are able to personalize treatment modalities and care for their patients. Artificial intelligence technology aimed at mimicking/simulating human mental processes, such as deep learning artificial neural networks (ANNs), are composed of a collection of individual units known as 'artificial neurons'. These 'neurons', when arranged and interconnected in complex architectural layers, are capable of analyzing the most complex patterns. The aim of this systematic review is to give a comprehensive summary of the contemporary applications of deep learning ANNs in urological medicine.

RECENT FINDINGS

Fifty-five articles were included in this systematic review and each article was assigned an 'intermediate' score based on its overall quality. Of these 55 articles, nine studies were prospective, but no nonrandomized control trials were identified.

SUMMARY

In urological medicine, the application of novel artificial intelligence technologies, particularly ANNs, have been considered to be a promising step in improving physicians' diagnostic capabilities, especially with regards to predicting the aggressiveness and recurrence of various disorders. For benign urological disorders, for example, the use of highly predictive and reliable algorithms could be helpful for the improving diagnoses of male infertility, urinary tract infections, and pediatric malformations. In addition, articles with anecdotal experiences shed light on the potential of artificial intelligence-assisted surgeries, such as with the aid of virtual reality or augmented reality.

3D imaging technologies in minimally-invasive kidney and prostate cancer surgery: which is the urologists' perception?

BACKGROUND

Many specific 3D imaging technologies are currently available for the practising urologists. Aim of the study was to assess their perception about different 3D imaging tools in the field of prostate and kidney cancer surgery.

METHODS

All the attendees of the 8th Techno-Urology-Meeting were asked to fill a questionnaire regarding the role of 3D virtual reconstruction PDFs, 3D printing models, Augmented-Reality (AR) and mixed reality technology in the setting of surgical planning, patient counselling, intraoperative guidance and training for kidney and prostate cancer surgery; Moreover the different materials used for 3D printing were compared to assess the most suitable in reproducing the organ and tumor features, as well as their estimated cost and production time.

RESULTS

The population consisted of 180 attendees. Overall, AR was the preferred option for intraoperative guidance and training, in both prostate (55% and 38.3%) and kidney cancer surgery (58.3% and 40%). HoloLens was perceived as the best imaging technology for the surgical planning (50% for prostate and 60% for kidney), whereas printed models for patients counselling (66.7% for prostate and 61.7% for kidney). Fused deposition models were deemed as the best printing technology in representing kidney anatomy and renal tumor location (40%), while silicon (46.7%) and Polyjet (36.7%) models for prostate anatomy and cancer location. Finally, attendees demonstrated poor knowledge of 3D printing costs and production times.

CONCLUSIONS

Our study shows the perceptions of a heterogeneous surrogate of practising urologists about the role and potential applications of 3D imaging technologies in daily surgical practice.

Real-time navigation by three-dimensional virtual reconstruction models in robot-assisted laparoscopic pyeloplasty for ureteropelvic junction obstruction: our initial experience

Background

The aim of this study was to evaluate the effectiveness and safety of real-time surgical navigation by three-dimensional (3D) virtual reconstruction models in robot-assisted laparoscopic pyeloplasty (RALP).

Methods

Between November 2018 and January 2020, 38 patients with ureteropelvic junction obstruction (UPJO) who underwent RALP were retrospectively enrolled. The operations were assisted in real time by 3D models in 16 patients, while 22 patients underwent surgery without navigation. Based on whether patients had a prior intervention history, crossing vessels or congenital deformities, we further divided them into the “complicated UPJO” cohort and the “regular UPJO” cohort for subgroup analysis. The demographic characteristics, intraoperative parameters, perioperative data and follow-up data were recorded and compared between the groups.

Results

All of the procedures were successfully performed without open or laparoscopic conversion. The mean dissection time to the UPJ was shorter in the navigation group than in the non-navigation group, both in the whole cohort (15.3 vs. 24.8 min, P=0.011) and in the complicated cohort (15.4 vs. 27.5 min, P=0.004), while there was no significant difference in the regular cohort. The overall operative time and estimated blood loss in the navigation group tended to be less, although the difference was not statistically significant. No difference in anastomosis time, postoperative hospital stay or complications was noted between the two groups in either cohort. At a mean follow-up of 11.2 months, the overall success rate was 94.7% (36/38), and there was no significant difference between the two groups.

Conclusions

Real-time navigation by 3D virtual reconstruction models might be helpful to improve surgical efficiency and safety of RALP by facilitating the dissection around the UPJ, especially for cases of complicated UPJO. However, the prospective study with larger sample size is further needed to confirm the results.

Machine learning in the optimization of robotics in the operative field

PURPOSE OF REVIEW

The increasing use of robotics in urologic surgery facilitates collection of 'big data'. Machine learning enables computers to infer patterns from large datasets. This review aims to highlight recent findings and applications of machine learning in robotic-assisted urologic surgery.

RECENT FINDINGS

Machine learning has been used in surgical performance assessment and skill training, surgical candidate selection, and autonomous surgery. Autonomous segmentation and classification of surgical data have been explored, which serves as the stepping-stone for providing real-time surgical assessment and ultimately, improve surgical safety and quality. Predictive machine learning models have been created to guide appropriate surgical candidate selection, whereas intraoperative machine learning algorithms have been designed to provide 3-D augmented reality and real-time surgical margin checks. Reinforcement-learning strategies have been utilized in autonomous robotic surgery, and the combination of expert demonstrations and trial-and-error learning by the robot itself is a promising approach towards autonomy.

SUMMARY

Robot-assisted urologic surgery coupled with machine learning is a burgeoning area of study that demonstrates exciting potential. However, further validation and clinical trials are required to ensure the safety and efficacy of incorporating machine learning into surgical practice.