Generative artificial intelligence in surgery

Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first surgical applications of generative artificial intelligence are applied, this perspective paper aims to provide a comprehensive overview of current applications and future perspectives for the application of generative artificial intelligence in surgery, from preoperative planning to training. Generative artificial intelligence can be used before surgery for planning and decision support by extracting patient information and providing patients with information and simulation regarding the procedure. Intraoperatively, generative artificial intelligence can document data that is normally not captured as intraoperative adverse events or provide information to help decision-making. Postoperatively, GAIs can help with patient discharge and follow-up. The ability to provide real-time feedback and store it for later review is an important capability of GAIs. GAI applications are emerging as highly specialized, task-specific tools for tasks such as data extraction, synthesis, presentation, and communication within the realm of surgery. GAIs have the potential to play a pivotal role in facilitating interaction between surgeons and artificial intelligence.

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

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

Privacy-proof Live Surgery Streaming: Development and Validation of a low-cost, Real-time Robotic Surgery Anonymization Algorithm

OBJECTIVE

Develop a pioneer surgical anonymization algorithm for reliable and accurate real-time removal of out-of-body images, validated across various robotic platforms.

SUMMARY BACKGROUND DATA / BACKGROUND

The use of surgical video data has become common practice in enhancing research and training. Video sharing requires complete anonymization, which, in the case of endoscopic surgery, entails the removal of all nonsurgical video frames where the endoscope can record the patient or operating room staff. To date, no openly available algorithmic solution for surgical anonymization offers reliable real-time anonymization for video streaming, which is also robotic-platform- and procedure-independent.

METHODS

A dataset of 63 surgical videos of 6 procedures performed on four robotic systems was annotated for out-of-body sequences. The resulting 496.828 images were used to develop a deep learning algorithm that automatically detected out-of-body frames. Our solution was subsequently benchmarked against existing anonymization methods. In addition, we offer a post-processing step to enhance the performance and test a low-cost setup for real-time anonymization during live surgery streaming.

RESULTS

Framewise anonymization yielded an ROC AUC-score of 99.46% on unseen procedures, increasing to 99.89% after post-processing. Our Robotic Anonymization Network (ROBAN) outperforms previous state-of-the-art algorithms, even on unseen procedural types, despite the fact that alternative solutions are explicitly trained using these procedures.

CONCLUSIONS

Our deep learning model ROBAN offers reliable, accurate, and safe real-time anonymization during complex and lengthy surgical procedures regardless of the robotic platform. The model can be used in real-time for surgical live streaming and is openly available.

Robot-assisted Radical Prostatectomy Performed with Different Robotic Platforms: First Comparative Evidence Between Da Vinci and HUGO Robot-assisted Surgery Robots

BACKGROUND

In the field of robotic surgery, there is a lack of comparative evidence on surgical and functional outcomes of different robotic platforms.

OBJECTIVE

To assess the outcomes of patients receiving robot-assisted radical prostatectomy (RARP) at a high-volume robotic center with daVinci and HUGO robot-assisted surgery (RAS) surgical systems.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed the data of 542 patients undergoing RARP ± extended pelvic lymph node dissection at OLV hospital (Aalst, Belgium) between 2021 and 2023. All procedures were performed by six surgeons using daVinci or HUGO RAS robots; the use of one platform rather than the other did not follow any specific preference and/or indication.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Multivariable analyses investigated the association between robotic system (daVinci vs HUGO RAS) and surgical outcomes after adjustment for patient- and tumor-related factors. Urinary continence recovery was defined as the use of no/one safety pad.

RESULTS AND LIMITATIONS

A total of 378 (70%) and 164 (30%) patients underwent RARP with daVinci and HUGO RAS surgical systems, respectively. Despite a higher rate of palpable disease in the HUGO RAS group (34% vs 25%), baseline characteristics did not differ between the groups (all p > 0.05). After adjusting for confounders, we did not find evidence of a difference between the groups with respect to operative time (estimate: 16.71; 95% confidence interval [CI]: -6.35, 39.78; p = 0.12), estimated blood loss (estimate: 3.12; 95% CI: -67.03, 73.27; p = 0.9), and postoperative Clavien-Dindo ≥2 complications (odds ratio [OR]: 1.66; 95% CI: 0.34, 8.15; p = 0.5). On final pathology, 55 (15%) and 20 (12%) men in, respectively, the daVinci and the HUGO RAS group had positive surgical margins (PSMs; p = 0.5). On multivariable analyses, we did not find evidence of an association between a robotic system and PSMs (OR: 1.08; 95% CI: 0.56, 2.07; p = 0.8). Similarly, the odds of recovering continence did not differ between daVinci and HUGO RAS cases after both 1 mo (OR: 0.78; 95% CI: 0.45, 1.38; p = 0.4) and 3 mo (OR: 1.17; 95% CI: 0.49, 2.79; p = 0.7).

CONCLUSIONS

Among patients receiving RARP with daVinci or HUGO RAS surgical platforms, we did not find differences in surgical and functional outcomes between the robots. This may be a result of a standardized surgical technique that allowed surgeons to transfer their skills between robotic systems. Awaiting future investigations with longer follow-up, these results have important implications for patients, surgeons, and health care policymakers.

PATIENT SUMMARY

We compared surgical and functional outcomes of patients receiving robot-assisted radical prostatectomy with daVinci versus HUGO robot-assisted surgery (RAS) robots. The two platforms were able to achieve similar outcomes, suggesting that the introduction of HUGO RAS is safe and allows for optimal outcomes after radical prostatectomy.

Transitioning from Da Vinci Si to Xi: assessing surgical outcomes at a high-volume robotic center

PURPOSE

In the emerging field of robotics, only few studies investigated the transition between different robotic platforms in terms of surgical outcomes. We aimed at assessing surgical outcomes of patients receiving robot-assisted radical prostatectomy (RARP) and robot-assisted partial nephrectomy (RAPN) at a high-volume robotic center during the transition from Si to Xi Da Vinci surgical systems.

METHODS

We analyzed data of 1884 patients undergoing RARP (n = 1437, 76%) and RAPN (n = 447, 24%) at OLV hospital (Aalst, Belgium) between 2011 and 2021. For both procedures, we assessed operative time, estimated blood loss, length of stay, and positive surgical margins. For RARP, we investigated length of catheterization and PSA persistence after surgery, whereas warm ischemia time, clampless surgery, and acute kidney injury (AKI) were assessed for RAPN. Multivariable analyses (MVA) investigated the association between robotic platform (Si vs. Xi) and surgical outcomes after adjustment for patient- and tumor-related factors.

RESULTS

A total of 975 (68%) and 462 (32%) patients underwent RARP performed with the Si vs. Xi surgical system, respectively. Baseline characteristics did not differ between the groups. On MVA, we did not find evidence of a difference between the groups with respect to operative time (estimate: 1.07) or estimated blood loss (estimate: 32.39; both p > 0.05). Median (interquartile range [IQR]) length of stay was 6 (3, 6) and 4 (3, 5) days in the Si vs. Xi group, respectively (p < 0.0001). On MVA, men treated with the Xi vs. Si robot had lower odds of PSM (Odds ratio [OR]: 0.58; p = 0.014). A total of 184 (41%) and 263 (59%) patients received RAPN with the Si and Xi robotic system, respectively. Baseline characteristics, including demographics, functional data, and tumor-related features did not differ between the groups. On MVA, operative time was longer in the Xi vs. Si group (estimate: 30.54; p = 0.006). Patients treated with the Xi vs. Si system had higher probability of undergoing a clampless procedure (OR: 2.56; p = 0.001), whereas the risk of AKI did not differ between the groups (OR: 1.25; p = 0.4). On MVA, patients operated with the Xi robot had shorter length of stay as compared to the Si group (estimate: - 0.86; p = 0.003), whereas we did not find evidence of an association between robotic system and PSM (OR: 1.55; p = 0.3).

CONCLUSION

We found that the Xi robot allowed for improvements in peri-operative outcomes as compared to the Si platform, with lower rate of positive margins for RARP and higher rate of off-clamp procedures for RAPN. Hospital stay was also shorter for patients operated with the Xi vs. Si robot, especially after robot-assisted partial nephrectomy. Awaiting future investigations-in particular, cost analyses-these results have important implications for patients, surgeons, and healthcare policymakers.

Robot-assisted Partial Nephrectomy Using Intra-arterial Renal Hypothermia for Highly Complex Endophytic or Hilar Tumors: Case Series and Description of Surgical Technique

Background

In partial nephrectomy for highly complex tumors with expected long ischemia time, renal hypothermia can be used to minimize ischemic parenchymal damage.

Objective

To describe our case series, surgical technique, and early outcomes for robot-assisted partial nephrectomy (RAPN) using intra-arterial cold perfusion through arteriotomy.

Design setting and participants

A retrospective analysis was conducted of ten patients with renal tumors (PADUA score 9-13) undergoing RAPN between March 2020 and March 2023 with intra-arterial cooling because of expected arterial clamping times longer than 25 min.

Surgical procedure

Multiport transperitoneal RAPN with full renal mobilization and arterial, venous, and ureteral clamping was performed. After arteriotomy and venotomy, 4°C heparinized saline is administered intravascular through a Fogarty catheter to maintain renal hypothermia while performing RAPN.

Measurements

Demographic data, renal function, console and ischemia times, surgical margin status, hospital stay, estimated blood loss, and complications were analyzed.

Results and limitations

The median warm and cold ischemia times were 4 min (interquartile range [IQR] 3-7 min) and 60 min (IQR 33-75 min), respectively. The median rewarming ischemia time was 10.5 min (IQR 6.5-23.75 min). The median pre- and postoperative estimated glomerular filtration rate values at least 1 mo after surgery were 90 ml/min (IQR 78.35-90 ml/min) and 86.9 ml/min (IQR 62.08-90 ml/min), respectively. Limitations include small cohort size and short median follow-up (13 [IQR 9.1-32.4] mo).

Conclusions

We demonstrate the feasibility and first case series for RAPN using intra-arterial renal hypothermia through arteriotomy. This approach broadens the scope for minimal invasive nephron-sparing surgery in highly complex renal masses.

Patient summary

We demonstrate a minimally invasive surgical technique that reduces kidney infarction during complex kidney tumor removal where surrounding healthy kidney tissue is spared. The technique entails arterial cold fluid irrigation, which temporarily decreases renal metabolism and allows more kidneys to be salvaged.

Surgical Phase Duration in Robot-Assisted Partial Nephrectomy: A Surgical Data Science Exploration for Clinical Relevance

(1) Background: Surgical phases form the basic building blocks for surgical skill assessment, feedback, and teaching. The phase duration itself and its correlation with clinical parameters at diagnosis have not yet been investigated. Novel commercial platforms provide phase indications but have not been assessed for accuracy yet. (2) Methods: We assessed 100 robot-assisted partial nephrectomy videos for phase durations based on previously defined proficiency metrics. We developed an annotation framework and subsequently compared our annotations to an existing commercial solution (Touch Surgery, Medtronic™). We subsequently explored clinical correlations between phase durations and parameters derived from diagnosis and treatment. (3) Results: An objective and uniform phase assessment requires precise definitions derived from an iterative revision process. A comparison to a commercial solution shows large differences in definitions across phases. BMI and the duration of renal tumor identification are positively correlated, as are tumor complexity and both tumor excision and renorrhaphy duration. (4) Conclusions: The surgical phase duration can be correlated with certain clinical outcomes. Further research should investigate whether the retrieved correlations are also clinically meaningful. This requires an increase in dataset sizes and facilitation through intelligent computer vision algorithms. Commercial platforms can facilitate this dataset expansion and help unlock the full potential, provided that the phase annotation details are disclosed.

Can the Abdominal Aortic Atherosclerotic Plaque Index Predict Functional Outcomes after Robot-Assisted Partial Nephrectomy?

This study aims to evaluate the abdominal aortic atherosclerotic plaque index (API)'s predictive role in patients with pre-operatively or post-operatively developed chronic kidney disease (CKD) treated with robot-assisted partial nephrectomy (RAPN) for renal cell carcinoma (RCC). One hundred and eighty-three patients (134 with no pre- and post-operative CKD (no CKD) and 49 with persistent or post-operative CKD development (post-op CKD)) who underwent RAPN between January 2019 and January 2022 were deemed eligible for the analysis. The API was calculated using dedicated software by assessing the ratio between the CT scan atherosclerotic plaque volume and the abdominal aortic volume. The ROC regression model demonstrated the influence of API on CKD development, with an increasing effect according to its value (coefficient 0.13; 95% CI 0.04-0.23; p = 0.006). The Model 1 multivariable analysis of the predictors of post-op CKD found that the following are independently associated with post-op CKD: Charlson Comorbidity Index (OR 1.31; p = 0.01), last follow-up (FU) Δ%eGFR (OR 0.95; p < 0.01), and API ≥ 10 (OR 25.4; p = 0.01). Model 2 showed API ≥ 10 as the only factor associated with CKD development (OR 25.2; p = 0.04). The median follow-up was 22 months. Our results demonstrate API to be a strong predictor of post-operative CKD, allowing the surgeon to tailor the best treatment for each patient, especially in those who might be at higher risk of CKD.

Robot-assisted adrenalectomy: Step-by-step technique and surgical outcomes at a high-volume robotic center

Objective

In the last years, robotic surgery was introduced in several different settings with good perioperative results. However, its role in the management of adrenal masses is still debated. In order to provide a contribution to this field, we described our step-by-step technique for robotic adrenalectomy (RA) and related modifications according to the type of adrenal mass treated.

Methods

We retrospectively analyzed 27 consecutive patients who underwent RA at Onze-Lieve-Vrouw hospital (Aalst, Belgium) between January 2009 and October 2022. Demographic, intra- and post-operative, and pathological data were retrieved from our prospectively maintained institutional database. Continuous variables are summarized as median and interquartile range (IQR). Categorical variables are reported as frequencies (percentages).

Results

Twenty-seven patients underwent RA were included in the study. Median age, body mass index, and Charlson's comorbidity index were 61 (IQR: 49-71) years, 26 (IQR: 24-29) kg/m2, and 2 (IQR: 0-3), respectively, and 16 (59.3%) patients were male. Median tumor size at computed tomography scan was 6.0 (IQR: 3.5-8.0) cm. Median operative time and blood loss were 105 (IQR: 82-120) min and 175 (IQR: 94-250) mL, respectively. No intraoperative complications were recorded. Overall postoperative complications rate was 11.1%, with a postoperative transfusion rate of 3.7%. A total of 10 (37.0%) patients harbored malignant adrenal masses. Among them, 3 (11.1%) had adrenocortical carcinoma, 6 (22.2%) secondary metastasis, and 1 (3.7%) malignant pheochromocytoma on final pathological exam. Only 1 (10.0%) patient had positive surgical margins.

Conclusion

We described our step-by-step technique for RA, which can be safely performed even in case of high challenging settings as malignant tumors, pheochromocytoma, and large masses. The standardization of perioperative protocol should be encouraged to maximize the outcomes of this complex surgical procedure.

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

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

Outcomes of Robot-assisted Radical Prostatectomy with the Hugo RAS Surgical System: Initial Experience at a High-volume Robotic Center

Clinical data on robot-assisted radical prostatectomy (RARP) performed with the new Hugo robot-assisted surgery (RAS) system are scarce. We described surgical outcomes of 112 consecutive patients who underwent RARP ± extended pelvic lymph-node dissection (ePLND) at OLV Hospital (Aalst, Belgium) between February and November 2022. The median age was 65 yr (interquartile range [IQR] 60-70) and median preoperative prostate-specific antigen (PSA) was 7.9 ng/ml (5.8-10.7). Thirty-eight patients (34%) had International Society of Urological Pathology grade group ≥3 tumor on prostate biopsy. On preoperative magnetic resonance imaging, 26 (23%) patients had a suspicion of extraprostatic disease. The median operative time was 180 min (IQR 145-200) and 27 men (24%) underwent ePLND. On final pathology, 34 patients (31%) had extraprostatic disease and ten (9%) had positive surgical margins. The median number of nodes removed was 15 (IQR 9-19). Among men with data available on the first PSA after surgery, 88% (60/68) had undetectable PSA (<0.1 ng/ml). The probability of urinary continence (UC) recovery was 36% (95% confidence interval [CI] 28-47%) at 1 mo and 81% (95% CI 72-89%) at 3 mo. The median time to UC recovery was 36 d (95% CI 34-44). This is the first report of data on UC recovery and surgical pathology for patients undergoing RARP for prostate cancer performed with the Hugo RAS robotic system. Future investigations with longer follow-up are awaited. PATIENT SUMMARY: We describe surgical outcomes of patients undergoing robot-assisted surgical removal of the prostate for cancer performed with the Hugo RAS robotic system at our institution. In our experience this platform provided adequate results in terms of surgical results and early recovery of urinary continence. Studies with longer follow-up are awaited.

Different approaches for bladder neck dissection during robot-assisted radical prostatectomy: the Aalst technique

INTRODUCTION

Bladder neck dissection is one of the most delicate surgical steps of robotic-assisted radical prostatectomy (RARP) [1, 2], and it may affect surgical margins rate and functional outcomes [3, 4]. Given the relationship between outcomes and surgical experience [5-7], it is crucial to implement a step-by-step approach for each surgical step of the procedure, especially in the most challenging part of the intervention. In this video compilation, we described the techniques for bladder neck dissection utilized at OLV Hospital (Aalst, Belgium).

SURGICAL TECHNIQUE

We illustrated five different techniques for bladder neck dissection during RARP. The anterior technique tackles the bladder neck from above until the urethral catheter is visualized, and then the dissection is completed posteriorly. The lateral and postero-lateral approaches involve the identification of a weakness point at the prostate-vesical junction and aim to develop the posterior plane - virtually until the seminal vesicles - prior to the opening of the urethra anteriorly. Finally, we described our techniques for bladder neck dissection in more challenging cases such as in patients with bulky middle lobes and prior surgery for benign prostatic hyperplasia. All approaches follow anatomic landmarks to minimize positive surgical margins and aim to preserve the bladder neck in order to promote optimal functional recovery. All procedures were performed with DaVinci robotic platforms using a 3-instruments configuration (scissors, fenestrated bipolar, and needle driver). As standard protocol at our Institution, urinary catheter was removed on postoperative day two [8].

CONCLUSIONS

Five different approaches for bladder neck dissection during RARP were described in this video compilation. We believe that the technical details provided here might be of help for clinicians who are starting their practice with this surgical intervention.

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

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

A Novel Three-dimensional Planning Tool for Selective Clamping During Partial Nephrectomy: Validation of a Perfusion Zone Algorithm

BACKGROUND

Selective clamping during robot-assisted partial nephrectomy (RAPN) requires extensive knowledge on patient-specific renal vasculature, obtained through imaging.

OBJECTIVE

To validate an in-house developed perfusion zone algorithm that provides patient-specific three-dimensional (3D) renal perfusion information.

DESIGN, SETTING, AND PARTICIPANTS

Between October 2020 and June 2022, 25 patients undergoing RAPN at Ghent University Hospital were included. Three-dimensional models, based on preoperative computed tomography (CT) scans, showed the clamped artery's ischemic zone, as calculated by the algorithm.

SURGICAL PROCEDURE

All patients underwent selective clamping during RAPN. Indocyanine green (ICG) was administered to visualize the true ischemic zone perioperatively. Surgery was recorded for a postoperative analysis.

MEASUREMENTS

The true ischemic zone of the clamped artery was compared with the ischemic zone predicted by the algorithm through two metrics: (1) total ischemic zone overlap and (2) tumor ischemic zone overlap. Six urologists assessed metric 1; metric 2 was assessed objectively by the authors.

RESULTS AND LIMITATIONS

In 92% of the cases, the algorithm was sufficiently accurate to plan a selective clamping strategy. Metric 1 showed an average score of 4.28 out of 5. Metric 2 showed an average score of 4.14 out of 5. A first limitation is that ICG can be evaluated only at the kidney surface. A second limitation is that mainly patients with impaired renal function are expected to benefit from this technology, but contrast-enhanced CT is required at present.

CONCLUSIONS

The proposed new tool demonstrated high accuracy when planning selective clamping for RAPN. A follow-up prospective study is needed to determine the tool's clinical added value.

PATIENT SUMMARY

In partial nephrectomy, the surgeon has no information on which specific arterial branches perfuse the kidney tumor. We developed a surgeon support system that visualizes the perfusion zones of all arteries on a three-dimensional model and indicates the correct arteries to clamp. In this study, we validate this tool.

Robot-assisted sutureless partial nephrectomy for the treatment of fifteen bilateral renal masses in a patient with Von Hippel-Lindau syndrome: a case report from a high-volume robotic center

Renal cell carcinoma is among major causes of death in patients with Von Hippel-Lindau (VHL) syndrome, and it usually presents with multiple and bilateral lesions that may require multiple renal surgeries. This, in turn, may compromise renal function, resulting in end-stage renal disease. To minimize renal function impairment in these patients, great importance is given to the preservation of functional parenchyma with the use of nephron-sparing techniques. Furthermore, new techniques such as off-clamp surgery, selective suturing or sutureless techniques may improve long-term functional outcomes. We described the case of a 27-year-old male patient with a family history of VHL disease affected by multiple, bilateral renal masses. He received bilateral, metachronous robot-assisted partial nephrectomies (RAPN) for a total of 15 renal lesions. No intra- or post-operative complications occurred, and the patient was discharged on the second postoperative day after both procedures. Serum creatinine after the second RAPN was 0.99 mg/dl (baseline value was 1.11 mg/dl). In patients with VHL syndrome and multiple renal lesions, robot-assisted partial nephrectomy, especially with the use of clampless and sutureless techniques, helps minimizing renal function impairment and should be performed when anatomically and technically feasible.

Robot-Assisted Sacropexy with the Novel HUGO Robot-Assisted Surgery System: Initial Experience and Surgical Setup at a Tertiary Referral Robotic Center

Introduction and Hypothesis: Robotic sacropexy (RSC) emerged in the last years as a valid alternative to the laparoscopic technique. However, the robotic approach is still limited by platform availability and concerns about cost-effectiveness. Recently, new robotic platforms joined the market, lowering the costs and offering the possibility to expand the robotic approach. The aim of our study was to demonstrate the technical feasibility and safety of the procedure with this new platform along with the description of our surgical setting. Materials and Methods: We reported data on the first five consecutive patients who underwent RSC at Onze Lieve Vrouw Hospital (Aalst, Belgium), performed with the novel HUGO™ Robot-Assisted Surgery (RAS) System. The platform consists of four fully independent carts, an open console, and a system tower equipped for both laparoscopic and robotic surgery. We collected patients' characteristics, intraoperative data, intraoperative complications, and clashes of instruments. Results: All procedures were completed according to the same surgical setting and technique. No need for conversion to open/laparoscopic surgery and/or for additional port placement was required. No intraoperative complications, instrument clashes, or system failure that compromised the surgery's completion were recorded. Median interquartile range docking, operative, and console time were 8 (6-9), 130 (115-165), and 80 (80-115) minutes, respectively. Conclusion: This series represents the first worldwide report of a robot-assisted sacropexy executed with the novel HUGO RAS System. Awaiting future investigation, this preliminary experience provides relevant data in terms of operative room settings and perioperative outcomes that might be helpful for future adopters of this platform.

Will Renorrhaphy Become Obsolete? Evaluation of a New Hemostatic Sealant

Background: In robot-assisted partial nephrectomy (RAPN) renorrhaphy is used to achieve hemostatic control of the tumoral resection bed, with detrimental impact on renal function. Hemostatic agents are used to achieve rapid and optimal hemostasis. GATT-Patch is a new hemostatic sealant that has already demonstrated promising results. Objective: Compare GATT-Patch and standard renorrhaphy in terms of hemostatic capacity, ischemia time, and prevention of urinary leakage after RAPN in a porcine model. Design, Setting, and Participants: In this preclinical randomized controlled trial, four pigs underwent 32 RAPNs. After resection, GATT-Patch application and performance of classic renorrhaphy were randomized. After the procedure, the resection bed was reinspected. A necropsy study evaluated the adhesiveness of the patch, and retrograde pyelography was performed to determine the leakage burst pressure. Intervention: Application of GATT-Patch and performance of classic renorrhaphy were randomized and surgeons blinded to the hemostatic technique to be performed. Outcome Measurements and Statistical Analysis: Warm ischemia, hemostatic control, active bleeding during hemostatic control, total procedure time, bleeding at reinspection, and presence of urinary leakage on retrograde pyelography were recorded. Continuous variables were compared using the Student t-test. Categorical variables were compared using the Chi-square or Fisher's exact test. Results and Limitations: GATT-Patch reduced warm ischemia time (WIT), time to achieve hemostatic control, active bleeding time, and total procedure time, achieving hemostasis in 100% of the cases. Rebleeding at reinspection occurred in 0% of the GATT-Patch group. Renal parenchyma damage was observed in 100% of renorrhaphy cases and in 0% of GATT-Patch cases. Conclusions: GATT-Patch guaranteed optimal hemostasis and urine sealant effect after RAPN in porcine models. Compared to renorrhaphy, we observed a reduction in WIT, total procedure time, and potential reduction in healthy parenchyma loss. Patient Summary: GATT-Patch stops bleeding and provides hemostasis faster than suturing after resection of portions of the kidney in pigs. It might be tested in patients undergoing partial nephrectomy for kidney cancer.

Multicentric exploration of tool annotation in robotic surgery: lessons learned when starting a surgical artificial intelligence project

BACKGROUND

Artificial intelligence (AI) holds tremendous potential to reduce surgical risks and improve surgical assessment. Machine learning, a subfield of AI, can be used to analyze surgical video and imaging data. Manual annotations provide veracity about the desired target features. Yet, methodological annotation explorations are limited to date. Here, we provide an exploratory analysis of the requirements and methods of instrument annotation in a multi-institutional team from two specialized AI centers and compile our lessons learned.

METHODS

We developed a bottom-up approach for team annotation of robotic instruments in robot-assisted partial nephrectomy (RAPN), which was subsequently validated in robot-assisted minimally invasive esophagectomy (RAMIE). Furthermore, instrument annotation methods were evaluated for their use in Machine Learning algorithms. Overall, we evaluated the efficiency and transferability of the proposed team approach and quantified performance metrics (e.g., time per frame required for each annotation modality) between RAPN and RAMIE.

RESULTS

We found a 0.05 Hz image sampling frequency to be adequate for instrument annotation. The bottom-up approach in annotation training and management resulted in accurate annotations and demonstrated efficiency in annotating large datasets. The proposed annotation methodology was transferrable between both RAPN and RAMIE. The average annotation time for RAPN pixel annotation ranged from 4.49 to 12.6 min per image; for vector annotation, we denote 2.92 min per image. Similar annotation times were found for RAMIE. Lastly, we elaborate on common pitfalls encountered throughout the annotation process.

CONCLUSIONS

We propose a successful bottom-up approach for annotator team composition, applicable to any surgical annotation project. Our results set the foundation to start AI projects for instrument detection, segmentation, and pose estimation. Due to the immense annotation burden resulting from spatial instrumental annotation, further analysis into sampling frequency and annotation detail needs to be conducted.

Peritoneal tuberculosis caused by intravesical instillation with Bacillus Calmette-Guérin (BCG) following nephroureterectomy in a patient with bladder and upper tract urothelial cancer: a case report

BACKGROUND

The standard treatment for high-risk non-muscle-invasive bladder cancer (NMIBC) is trans-urethral resection of the bladder (TURB) followed by instillation of Bacillus Calmette-Guérin (BCG). The occurrence of peritoneal tuberculosis after intravesical BCG instillation is extremely rare and difficult to diagnose.

METHODS

We report the case of a 79-year-old man with urothelial cell carcinoma (UCC) of the kidney and bladder who developed peritoneal tuberculosis after consecutive TURB and nephroureterectomy followed by intravesical BCG instillation. Further investigation revealed an undiagnosed bladder leak.

CONCLUSION

This case serves as a reminder for urologists to be suspicious for urothelium discontinuity when administering BCG shortly after bladder surgery.

Robot-assisted Radical Prostatectomy with the Novel Hugo Robotic System: Initial Experience and Optimal Surgical Set-up at a Tertiary Referral Robotic Center

We describe the first five robot-assisted radical prostatectomies (RARPs) performed with the new Hugo RAS system (Medtronic, Minneapolis, MN, USA) in Europe. The five patients underwent RARP ± lymph node dissection at OLV Hospital (Aalst, Belgium). All procedures were completed, with no need for conversion or for placement of additional ports. No intraoperative complication or technical failure of the system was recorded. The median operative time was 170 min (interquartile range [IQR]: 140-180) and the median console time was 120 min (IQR: 110-150). Median length of stay was 3 d (IQR: 2-4). System start-up and docking of the robotic arms were straightforward and rapid processes for a properly trained surgical team. Awaiting future investigations in larger series, this study proves the safety and feasibility of RARP with the Hugo RAS system and provides relevant data that may be of help to early adopters of this surgical platform.

Assessing pentafecta achievement after robot-assisted radical cystectomy and its association with surgical experience: Results from a high-volume institution

OBJECTIVES

Radical cystectomy (RC) represents the gold standard treatment for high-risk bladder cancer. Despite evidence suggesting that surgical experience correlates with perioperative and oncologic outcomes of robot-assisted RC (RARC), validated tools to assess its quality objectively are lacking. We aimed to evaluate the impact of RC-Pentafecta (absence of early major complications, absence of urinary diversion related sequelae at ≤12 months, absence of soft tissue surgical margins, ≥16 lymph nodes at final pathology and absence of clinical recurrence at ≤12 months) on oncological outcomes and the role of surgical experience on its achievement.

MATERIALS AND METHODS

We retrospectively evaluated 366 patients undergoing RARC with intracorporeal urinary diversion in a single tertiary centre with a minimum of 1 year follow-up. Surgeries were performed using the DaVinci Xi system according to a previously described technique. Kaplan-Meier curves were used to investigate 5-years overall survival and cancer specific mortality-free survival (CSS) according to RC-Pentafecta achievement. Multivariable Cox's regressions were performed to evaluate the impact of RC-Pentafecta on overall mortality. Multivariable logistic regressions were performed to explore the effect of surgical experience on RC-pentafecta achievement. Locally weighted scatterplot smoother function was used to graphically explore this relationship.

RESULTS

Patients achieving RC-Pentafecta showed higher 5-year overall survival (71.8% vs. 59.6%, P < 0.001) and CSS (84% vs. 71%, P < 0.001) when compared with patients not achieving it. At multivariable Cox's regression, RC-Pentafecta achievement (HR 0.57, P = 0.03), positive surgical margins (HR 2.48, P = 0.002), pN+ (HR 2.23, P = 0.002), pT≥3 (HR 1.71, P = 0.04) and current smoking status (HR 2.4, P = 0.006) were significant predictors of overall mortality. At multivariable logistic regression surgical experience (OR 1.2, P < 0.001), age (OR 0.93, P = 0.04), previous prostate surgery (OR 0.7, P = 0.02) and pT≥3 (OR 0.8, P = 0.03) were independent predictors of RC-Pentafecta achievement. A linear relationship between surgical experience and RC-Pentafecta achievement, without reaching a plateau, was observed.

CONCLUSIONS

RC-Pentafecta is a valuable tool to assess surgical quality of RARC and the experience of the center where the surgery is performed and may be used to identify "referral" centers for treatment of high-risk bladder cancer.

Point-of-care 3D printing: a low-cost approach to teaching carotid artery stenting

BACKGROUND

Carotid Artery Stenting (CAS) is increasingly being used in selected patients as a minimal invasive approach to carotid endarterectomy. Despite the long standing tradition of endovascular treatments, visual feedback during stent-deployment is impossible to obtain as deployment is performed under fluoroscopic imaging. Furthermore, the concept of stent-placement is often still unclear to patients. 3D Printing allows to replicate patient-specific anatomies and deploy stents inside them to simulate procedures. As such these models are being used for endovascular training as well as patient education.

PURPOSE

To our knowledge, this study reports the first use of a low-cost patient-specific 3D printed model for teaching CAS deployment under direct visualization, without fluoroscopy.

METHODOLOGY

A CT-angiogram was segmented and converted to STL format using Mimics inPrint™ software. The carotid arteries were bilaterally truncated to fit the whole model on a Formlabs 2 printer without omitting the internal vessel diameter. Next, this model was offset using a 1 mm margin. A ridge was modelled on the original vessel anatomy which was subsequently subtracted from the offset model in order to obtain a deroofed 3D model. All vessels were truncated to facilitate post-processing, flow and guide wire placement.

RESULTS

Carotid artery stents were successfully deployed inside the vessel. The deroofing allows for clear visualization of the bottlenecks and characteristics of CAS deployment and positioning, including stent foreshortening, tapering and recoil. This low-cost 3D model provides visual insights in stent deployment and positioning, and can allow for patient-specific procedure planning.

CONCLUSIONS

The presented approach demonstrates the use of low-cost 3D Printed CAS models in teaching complex stent behavior as observed during deployment. Two main findings are illustrated. On one hand, the feasibility of low-cost in-hospital model production is shown. On the other hand, the teaching of CAS deployment bottlenecks at the carotid level without the need for fluoroscopic guidance, is illustrated. The observed stent characteristics as shown during deployment are difficult to assess in radiologic models. Furthermore, printing patient-specific 3D models preoperatively could possibly assist in accurate patient selection, preoperative planning, case-specific training and patient education.

Kinematic boundary conditions substantially impact in silico ventricular function

Computational cardiac mechanical models, individualized to the patient, have the potential to elucidate the fundamentals of cardiac (patho-)physiology, enable non-invasive quantification of clinically significant metrics (eg, stiffness, active contraction, work), and anticipate the potential efficacy of therapeutic cardiovascular intervention. In a clinical setting, however, the available imaging resolution is often limited, which limits cardiac models to focus on the ventricles, without including the atria, valves, and proximal arteries and veins. In such models, the absence of surrounding structures needs to be accounted for by imposing realistic kinematic boundary conditions, which, for prognostic purposes, are preferably generic and thus non-image derived. Unfortunately, the literature on cardiac models shows no consistent approach to kinematically constrain the myocardium. The impact of different approaches (eg, fully constrained base, constrained epi-ring) on the predictive capacity of cardiac mechanical models has not been thoroughly studied. For that reason, this study first gives an overview of current approaches to kinematically constrain (bi) ventricular models. Next, we developed a patient-specific in silico biventricular model that compares well with literature and in vivo recorded strains. Alternative constraints were introduced to assess the influence of commonly used mechanical boundary conditions on both the predicted global functional behavior of the in-silico heart (cavity volumes, stroke volume, ejection fraction) and local strain distributions. Meaningful differences in global functioning were found between different kinematic anchoring strategies, which brought forward the importance of selecting appropriate boundary conditions for biventricular models that, in the near future, may inform clinical intervention. However, whilst statistically significant differences were also found in local strain distributions, these differences were minor and mostly confined to the region close to the applied boundary conditions.

Determination of gentamicin in swine and calf tissues by high-performance liquid chromatography combined with electrospray ionization mass spectrometry

Gentamicin is a broad-spectrum aminoglycoside antibiotic widely used in veterinary medicine for the treatment of serious infections. The purpose of this study was to develop and validate a method to determine gentamicin residues in edible tissues of swine and calf. Extraction of gentamicin was performed using a liquid extraction with phosphate buffer containing trichloroacetic acid, followed by a solid-phase clean-up procedure on a CBA weak cation-exchange column. Tobramycin was used as the internal standard. After drying of the eluate, the residue was redissolved and further analyzed by reversed-phase liquid chromatography/electrospray ionization tandem mass spectrometry (MS/MS). Chromatographic separation of the internal standard tobramycin and the gentamicin components was achieved on a Nucleosil (5 microm) column using a mixture of 10 mM pentafluoropropionic acid in water and acetonitrile as the mobile phase. The gentamicin components C1a, C2 + C2a and C1 could be identified with the MS/MS detection, and subsequently quantified. The method was validated according to the requirements of the EC at the maximum residue limit (MRL) (100 ng g(-1) for muscle and fat, 200 ng g(-1) for liver and 1000 ng g(-1) for kidney), half the MRL and double the MRL levels. Calibration graphs were prepared for all tissues and good linearity was achieved over the concentration ranges tested (r > 0.99 and goodness of fit <10%). Limits of quantification of 25.0 ng g(-1) were obtained for the determination of gentamicin in muscle, fat, liver and kidney tissues of swine and calf, which correspond in all cases to at least half the MRLs. Limits of detection ranged between 0.5 and 2.5 ng g(-1) for the tissues. The within-day and between-day precisions (RSD) and the results for accuracy fell within the ranges specified. The method was successfully used for the determination of gentamicin in tissue samples of swines and calves medicated with gentamicin by intramuscular injection.