Ten-year functional and oncological outcomes of a prospective randomized controlled trial comparing laparoscopic versus robot-assisted radical prostatectomy.

BACKGROUND: Among prostate cancer (PCa) treatment options, mini-invasive surgical approaches have gained a wide diffusion in the last decades. The aim of this study was to present oncological, functional, and quality of life data after 10 years of follow-up of a prospective randomized controlled trial (RCT) (ISRCTN11552140) comparing robot-assisted radical prostatectomy (RARP) versus laparoscopic radical prostatectomy (LRP) for the treatment of PCa. METHODS: Patients with localized PCa were randomized to undergo LRP or RARP between January 2010 and January 2011. Functional (continence and potency) and oncological (prostate-specific antigen, biochemical recurrence [BCR] and BCR-free survival [BCRFS]) variables were evaluated. BCRFS curves were estimated by the Kaplan-Meier method and compared using the log-rank test. Machine learning partial least square-discriminant analysis (PLS-DA) was used to identify the variables characterizing more the patients who underwent RARP or LRP. RESULTS: Seventy-five of the originally enrolled 120 patients remained on follow-up for 10 years; 40 (53%) underwent RARP and 35 (47%) LRP. Continence and potency recovery rates did not show significant differences (p = 0.068 and p = 0.56, respectively), despite a Δ12% for continence and Δ8% for potency in favor of the robotic approach. However, the quality of continence (in terms of International Consultation on Incontinence Questionnaire-Short Form [ICIQ-SF] score) and erection (in terms of International Index of Erectile Function-5 [IIEF-5] score) was significantly better after 10 years in the robotic group (p = 0.02 and p < 0.001). PLS-DA revealed that LRP was characterized by the worst functional-related outcomes analyzing the entire follow-up period. Four (10%) and six (17%) patients experienced BCR in RARP and LRP groups, respectively (p = 0.36), with an overall 10-year BCR-free survival of 88% and 78% (p = 0.16). CONCLUSIONS: Comparable continence and potency rates were observed between RARP and LRP after a 10-year follow-up. However, the RARP group exhibited superior totally dry rate and erection quality. No difference in terms of oncological outcomes was found.

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.

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.

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.

Development of Bleeding Artificial Intelligence Detector (BLAIR) System for Robotic Radical Prostatectomy.

BACKGROUND: Addressing intraoperative bleeding remains a significant challenge in the field of robotic surgery. This research endeavors to pioneer a groundbreaking solution utilizing convolutional neural networks (CNNs). The objective is to establish a system capable of forecasting instances of intraoperative bleeding during robot-assisted radical prostatectomy (RARP) and promptly notify the surgeon about bleeding risks. METHODS: To achieve this, a multi-task learning (MTL) CNN was introduced, leveraging a modified version of the U-Net architecture. The aim was to categorize video input as either "absence of blood accumulation" (0) or "presence of blood accumulation" (1). To facilitate seamless interaction with the neural networks, the Bleeding Artificial Intelligence-based Detector (BLAIR) software was created using the Python Keras API and built upon the PyQT framework. A subsequent clinical assessment of BLAIR's efficacy was performed, comparing its bleeding identification performance against that of a urologist. Various perioperative variables were also gathered. For optimal MTL-CNN training parameterization, a multi-task loss function was adopted to enhance the accuracy of event detection by taking advantage of surgical tools' semantic segmentation. Additionally, the Multiple Correspondence Analysis (MCA) approach was employed to assess software performance. RESULTS: The MTL-CNN demonstrated a remarkable event recognition accuracy of 90.63%. When evaluating BLAIR's predictive ability and its capacity to pre-warn surgeons of potential bleeding incidents, the density plot highlighted a striking similarity between BLAIR and human assessments. In fact, BLAIR exhibited a faster response. Notably, the MCA analysis revealed no discernible distinction between the software and human performance in accurately identifying instances of bleeding. CONCLUSION: The BLAIR software proved its competence by achieving over 90% accuracy in predicting bleeding events during RARP. This accomplishment underscores the potential of AI to assist surgeons during interventions. This study exemplifies the positive impact AI applications can have on surgical procedures.

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.

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.

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.

The Impact on Urology Residents' Learning of Social Media and Web Technologies after the Pandemic: A Step Forward through the Sharing of Knowledge.

The COVID-19 pandemic has impacted urology residents and their training. However, several new technologies or knowledge platforms as social media (SoMe) and web-based learning solutions have filled this gap. Therefore, we aimed to analyze resident's learning curves of new learning modalities, identify the evidence that is provided in the literature, and evaluate the possible impact of such solutions in the future. We conducted a non-systematic literature search using Medline, PubMed, and Embase. In addition, online resources of national and international urology resident societies were queried. The identified paper described SoMe, webinars, podcasts, pre-recorded surgical videos, educational platforms, and mobile apps in the field of urology that are used to gain access to information, teach and provide feedback to residents, and were used under the conditions of the pandemic. The application of those technologies harbors the risk of mis- and disinformation, but have the potential to provide access to education and validated knowledge, training, and feedback and thereby might democratize training of residents in urology globally.

Machine-Learning-Based Tool to Predict Target Prostate Biopsy Outcomes: An Internal Validation Study.

The aim of this study is to present a personalized predictive model (PPM) with a machine learning (ML) system that is able to identify and classify patients with suspected prostate cancer (PCa) following mpMRI. We extracted all the patients who underwent fusion biopsy (FB) from March 2014 to December 2019, while patients from August 2020 to April 2021 were included as a validation set. The proposed system was based on the following four ML methods: a fuzzy inference system (FIS), the support vector machine (SVM), k-nearest neighbors (KNN), and self-organizing maps (SOMs). Then, a system based on fuzzy logic (FL) + SVM was compared with logistic regression (LR) and standard diagnostic tools. A total of 1448 patients were included in the training set, while 181 patients were included in the validation set. The area under the curve (AUC) of the proposed FIS + SVM model was comparable with the LR model but outperformed the other diagnostic tools. The FIS + SVM model demonstrated the best performance, in terms of negative predictive value (NPV), on the training set (78.5%); moreover, it outperformed the LR in terms of specificity (92.1% vs. 83%). Considering the validation set, our model outperformed the other methods in terms of NPV (60.7%), sensitivity (90.8%), and accuracy (69.1%). In conclusion, we successfully developed and validated a PPM tool using the FIS + SVM model to calculate the probability of PCa prior to a prostate FB, avoiding useless ones in 15% of the cases.

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.

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.

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 ICON3DTM 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 ICON3DTM 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, ICON3DTM 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, ICON3DTM 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.

A prospective randomized controlled trial comparing target prostate biopsy alone approach vs. target plus standard in naïve patients with positive mpMRI.

BACKGROUND: In the era of mpMRI guided target fusion biopsy (FB), the role of concomitant standard biopsy (SB) in naïve patients still remains under scrutiny. The aim of this study was to compare the detection rate (DR) of clinically significant prostate cancer (csPCa) in biopsy naïve patients with positive mpMRI who underwent FB alone (Arm A) vs FB+SB (Arm B). Secondary objectives were to compare the incidence of complications, the overall PCa DR and the biopsy results with final pathological findings after robotic prostatectomy (RARP). METHODS: This is a single center prospective non-inferiority parallel two arms (1:1) randomized control trial (ISRCTN registry number ISRCTN60263108) which took place at San Luigi Gonzaga University Hospital, Orbassano (Turin, Italy) from 4/2019 to 10/2021. Eligible participants were all adults aged<75 years old, biopsy naïve, with serum PSA<15 ng/mL and positive mpMRI (Pi-Rads V.2>3). FB was performed under ultrasound guidance using the BioJet fusion system; four to six target samples were obtained for each index lesion. SB was performed in accordance with the protocol by Rodríguez-Covarrubias. RARP with total anatomical reconstruction was carried out when indicated. DR of PCa and csPCA (Gleason Score >7) were evaluated. Post-biopsy complications according to Clavien-Dindo were recorded. Concordance between biopsy and RARP pathological findings was evaluated. Fisher's Exact test and Mann-Whitney test were applied; furthermore, Logistic Principal Component Analysis (LogPCA) and Pearson's correlation method, in terms of correlation funnel plots, were performed to explore data in a multivariate way. RESULTS: 201 and 193 patients were enrolled in Arm A and B, respectively. csPCa DR was 60.2% vs. 60.6% in Arm A and B respectively (Δ 0.4%; P=0.93); whilst overall PCa DR was 63.7% vs. 71.0% (Δ 7.3%; P=0.12). However, in a target only setting, the addition of SB homolaterally to the index lesion reaching a non-inferior performance compared to the combined sampling (Δ PCa DR 3%). Although the differences of 7.3% in PCa DR, during RARP were registered similar nerve sparing rate (P=0.89), positive surgical margins (P=0.67) and rate of significant upgrading (P=0.12). LogPCA model showed no distinction between the two cohorts; and Pearson's correlation values turned to be between -0.5 and +0.5. In Arm B, the lesion diameter <10 mm is the only predictive variable of positive SB only for PCa (P=0.04), with an additional value +3% for PCa DR. CONCLUSIONS: In biopsy naïve patients, FB alone is not inferior to FB+SB in detecting csPCa (Δ csPCa DR 0.4%). Δ 7.3% in overall PCa DR was registered between the two Arms, however the addition of further standard samples homolaterally to mp-MRI index lesion improved the overall PCa DR of FB only sampling (Δ PCa DR 3%). The omission of SB did not influence the post-surgical outcomes in terms of NS approach, PSMr and upgrading/downgrading.

Development of a novel nomogram to identify the candidate to extended pelvic lymph node dissection in patients who underwent mpMRI and target biopsy only.

BACKGROUND: Nowadays a tool able to predict the risk of lymph-node invasion (LNI) in patients underwent target biopsy (TB) only before radical prostatectomy (RP) is still lacking. Our aim is to develop a model based on mp-MRI and target biopsy (TB) alone able to predict the risk of LNI. METHODS: We retrospectively extracted data of patients with preoperative positive mp-MRI and TB only who underwent RARP with ePLND from April 2014 to March 2020. A logistic regression model was performed to evaluate the impact of pre- and intra-operative factors on the risk of LNI. Model discrimination was assessed using an area under (AUC) the ROC curve. A nomogram, and its calibration plot, to predict the risk of LNI were generated based on the logistic model. A validation of the model was done using a similar cohort. RESULTS: 461 patients were included, of which 52 (11.27) had LNI. After logistic regression analysis and multivariable model DRE, PI-RADS, seminal vesicle invasion, PSA and worst GS at I and II target lesions were significant predictors of LNI. The AUC was 0.74 [0.67-0.81] 95% CI. The calibration plot shows that our model is very close to the ideal one which is in the 95% CI. After the creation of a visual nomogram, the cut-off to discriminate between the risk or not of LNI was set with Youden index at 60 points that correspond to a risk of LNI of 7%. The model applied on a similar cohort shown a LH+ of 2.58 [2.17-2.98] 95% CI. CONCLUSIONS: Our nomogram for patients undergoing MRI-TB only takes into account clinical stage, SVI at MRI, biopsy Gleason pattern and PSA and it is able to identify patients with risk of LNI when a score higher than 7% is achieved.

MRI/real-time ultrasound image fusion guided high-intensity focused ultrasound: a prospective comparative and functional analysis of different ablative techniques.

BACKGROUND: The aim of this paper was to compare safety and functional outcomes of total, hemi and focal ablation by the latest focal high-intensity focused ultrasound (HIFU) device. METHODS: This is a prospective study including patients with low to intermediate-risk PCa treated with HIFU by Focal One® device from 11/2018 to 3/2020. Before the treatment all patients underwent mp-magnetic resonance imaging (MRI) and subsequent MRI/transrectal ultrasound (TRUS) fusion and standard biopsy. Patients were stratified according to the type of ablation: total, hemi- or focal ablation. Functional data (IPSS, Quality of Life [QoL], IIEF-5, maximum flow [Qmax] and post void residual [PVR] at flowmetry) were assessed preoperatively and at 1, 3, 6 and 12 months after treatment. Moreover, the urinary symptoms reported by patients at IPSS questionnaire were divided in "irritative" and "obstructive" and compared. RESULTS: One hundred patients were enrolled. Median prostate volume and lesion diameter were 46 (IQR 25-75) mL and 10 (IQR 6-13) mm. 15, 50 and 35 patients underwent total, hemi- and focal ablation, respectively. No differences were found between them except for operative time (lower in the focal group, P<0.01). Significant lower incidence of irritative symptoms was identified in the focal group compared to the others (P<0.05 at 1 and 3 months of follow-up). No differences were found among the baseline status and the postoperative assessment in terms of obstructive IPSS items, IIEF-5, QoL, Qmax and PVR (all P value>0.05). CONCLUSIONS: Our study suggests that patients' specific HIFU tailoring with the MRI/real-time TRUS Guidance by Focal One® device is able to minimize the side effects of treatment.

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

CONTEXT: Use of three-dimensional (3D) guidance for nephron-sparing surgery (NSS) has increased in popularity, especially for laparoscopic and robotic approaches. Different 3D visualization modalities have been developed as promising new tools for surgical planning and intraoperative navigation. OBJECTIVES: To summarize and evaluate the impact of 3D models on minimally invasive NSS in terms of perioperative, functional, and oncological outcomes. EVIDENCE ACQUISITION: A systematic literature search was conducted in December 2021 using the Medline (PubMed), Embase (Ovid), Scopus, and Web of Science databases. The protocol was registered on PROSPERO (CRD42022300948). The search strategy used the PICOS (Population, Intervention, Comparison, Outcome, Study design) criteria and article selection was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias and the quality of the articles included were assessed. A dedicated data extraction form was used to collect the data of interest. Meta-analysis was performed using the Mantel-Haenszel method for binary outcomes, with results summarized as the odds ratio (OR), and the inverse variance method for continuous data, with results reported as the mean difference (MD). All effect estimates are reported with the 95% confidence interval (CI) and p ≤ 0.05 was considered statistically significant. All analyses were performed using R software and the meta package. EVIDENCE SYNTHESIS: The initial electronic search identified 450 papers, of which 17 met the inclusion criteria and were included in the analysis. Use of 3D technology led to a significant reduction in the global ischemia rate (OR 0.22, 95% CI 0.07-0.76; p = 0.02) and facilitated more frequent enucleation (OR 2.54, 95% CI 1.36-4.74; p < 0.01) and less frequent opening of the collecting system (OR 0.36, 95% CI 0.15-0.89; p = 0.03) and was associated with less blood loss (MD 23.1 ml, 95% CI 31.8-14.4; p < 0.01). 3D guidance for NSS was associated with a significant reduction in the transfusion rate (OR 0.20, 95% CI 0.07-0.56; p < 0.01). There were no significant differences in rates of conversion to radical nephrectomy, minor and major complications, change in glomerular filtration rate, or surgical margins (all p > 0.05). CONCLUSIONS: 3D guidance for NSS is associated with lower rates of detriment and surgical injury to the kidney. Specifically, a lower amount of nontumor renal parenchyma is exposed to ischemia or sacrificed during resection, and opening of the collecting system is less frequent. However, use of 3D technology does not lead to significant improvements in oncological or functional outcomes. PATIENT SUMMARY: We reviewed the use of three-dimensional tools for minimally invasive surgery for partial removal of the kidney in patients with kidney cancer. The evidence suggests that these tools have benefits during surgery, but do not lead to significant improvements in cancer control or functional outcomes for patients.