Stone centers: a national survey on surgical techniques performed in Italy.

BACKGROUND: Recurrent and complex stone disease may be considered a challenging disease. In 2018, the Calculus group of the SIU (Italian Society of Urology) set itself the goal of establishing the minimum requirements for a center that could continuously manage urolithiasis pathology, named a Stone Center. In this study we present the results of a pilot survey carried out in 2019 with the aim of drawing a map of the situation of Italian urological centers dealing with urinary stones. METHODS: A total of 260 national urology departments dealing with urolithiasis surgery were contacted for this study. A survey was issued to each of the centers to determine the number of patients treated for urinary stones and the amount of procedures performed per year: 1) extracorporeal shock wave lithotripsy ESWL; 2) ureterorenoscopy URS; 3) retrograde intrarenal surgery RIRS; 4) percutaneous nephrolithotomy PCNL. RESULTS: Out of 260 centers contacted, 188 fulfilled the survey. Outcomes were quite variable, with approximately 37% of the centers lacking a lithotripter, and 46% of those that did have it performing fewer than 100 treatments per year. In terms of endoscopic procedures, more than 80% of the centers contacted performed URS or RIRS; however, when it came to percutaneous lithotripsy, these numbers dropped significantly; 33% of the centers contacted did not perform PCNL, and of those who did, 18% had less than 5 years of experience as a center. CONCLUSIONS: Our survey shows a very heterogeneous national picture about urolithiasis treatments. Our goal is to create national paradigms to be able to define stone centers where the patient suffering from complex urinary stones can find a network of professionals with an adequate armamentarium suitable for the management of their pathology.

External validation of a nomogram for outcome prediction in management of medium-sized (1-2 cm) kidney stones.

BACKGROUND: Stone nomogram by Micali et al., able topredict treatment failure of shock-wave lithotripsy (SWL), retrograde intrarenal surgery (RIRS) and percutaneous nephrolithotomy (PNL) in the management of single 1-2 cm renal stones, was developed on 2605 patients and showed a high predictive accuracy, with an area under ROC curve of 0.793 at internal validation. The aim of the present study is to externally validate the model to assess whether it displayed a satisfactory predictive performance if applied to different populations. METHODS: External validation was retrospectively performed on 3025 patients who underwent an active stone treatment from December 2010 to June 2021 in 26 centers from four countries (Italy, USA, Spain, Argentina). Collected variables included: age, gender, previous renal surgery, preoperative urine culture, hydronephrosis, stone side, site, density, skin-to-stone distance. Treatment failure was the defined outcome (residual fragments >4 mm at three months CT-scan). RESULTS: Model discrimination in external validation datasets showed an area under ROC curve of 0.66 (95% 0.59-0.68) with adequate calibration. The retrospective fashion of the study and the lack of generalizability of the tool towards populations from Asia, Africa or Oceania represent limitations of the current analysis. CONCLUSIONS: According to the current findings, Micali's nomogram can be used for treatment prediction after SWL, RIRS and PNL; however, a lower discrimination performance than the one at internal validation should be acknowledged, reflecting geographical, temporal and domain limitation of external validation studies. Further prospective evaluation is required to refine and improve the nomogram findings and to validate its clinical value.

Development and validation of metrics for a new RAPN training model.

Robot-assisted partial nephrectomy (RAPN) is a complex and index procedure that urologists need to learn how to perform safely. No validated performance metrics specifically developed for a RAPN training model (TM) exist. A Core Metrics Group specifically adapted human RAPN metrics to be used in a newly developed RAPN TM, explicitly defining phases, steps, errors, and critical errors. A modified Delphi meeting concurred on the face and content validation of the new metrics. One hundred percent consensus was achieved by the Delphi panel on 8 Phases, 32 Steps, 136 Errors and 64 Critical Errors. Two trained assessors evaluated recorded video performances of novice and expert RAPN surgeons executing an emulated RAPN in the newly developed TM. There were no differences in procedure Steps completed by the two groups. Experienced RAPN surgeons made 34% fewer Total Errors than the Novice group. Performance score for both groups was divided at the median score using Total Error scores, into HiError and LoError subgroups. The LowErrs Expert RAPN surgeons group made 118% fewer Total Errors than the Novice HiErrs group. Furthermore, the LowErrs Expert RAPN surgeons made 77% fewer Total Errors than the HiErrs Expert RAPN surgeons. These results established construct and discriminative validity of the metrics. The authors described a novel RAPN TM and its associated performance metrics with evidence supporting their face, content, construct, and discriminative validation. This report and evidence support the implementation of a simulation-based proficiency-based progression (PBP) training program for RAPN.

Applicability and feasibility of robot-assisted cystectomy and intracorporeal urinary diversion in a patient with right renal pelvic ectopia.

BACKGROUND: The ectopic pelvic kidney, a common renal anomaly, is often smaller and malformed, with a shorter and sometimes tortuous ureter (1). Muscle-invasive bladder cancer (MIBC), constituting 15-25% of bladder cancer cases (2), mandates radical cystectomy with a 50% 5-year survival rate (2). Despite the growing use of robot-assisted radical cystectomy (RARC) (3, 4), there is limited data on its application in ectopic kidneys. Only one RARC case has been reported (5), in contrast to numerous open radical cystectomies (1, 6) involving an ectopic kidney. PATIENT AND METHODS: After being diagnosed with T2 high-grade urothelial carcinoma, the 66-year-old patient, previously treated with multiple transurethral resections and adjuvant BCG therapy, received neoadjuvant chemotherapy. Preoperative staging CT revealed a 2.6 x 2.2 cm bladder neoformation and an ectopic right pelvic kidney. RESULTS: Using the da Vinci Surgical System, radical cystectomy with ileal conduit (sec Wallace II) and lymphadenectomy were performed. During the demolition phase, the shorter right ureter was dissected with care to avoid damage to the renal pedicle. The reconstructive phase included intracorporeal urinary diversion (ICUD) and uretero-ileal anastomosis, facilitated by the favorable position of the kidney. The 8-hour console surgery resulted in minimal blood loss. Discharged on day 16 due to COVID-19, the patient exhibited positive outcomes. A 2-month CT follow-up revealed no cancer recurrence, metastasis, hydronephrosis, and complete regression of the lymphocele. Imaging follow-up continues without postoperative adjuvant chemotherapy. CONCLUSION: Robotic surgery with intracorporeal urinary diversion holds potential for right-sided pelvic kidney cases, but additional studies are necessary for validation.

ESRU-ESU-YAU_UROTECH Survey on Urology Residents Surgical Training: Are We Ready for Simulation and a Standardized Program?

Background: Currently, the landscape of surgical training is undergoing rapid evolution, marked by the initial implementation of standardized surgical training programs, which are further facilitated by the emergence of new technologies. However, this proliferation is uneven across various countries and hospitals. Objective: To offer a comprehensive overview of the existing surgical training programs throughout Europe, with a specific focus on the accessibility of simulation resources and standardized surgical programs. Design setting and participants: A dedicated survey was designed and spread in May 2022 via the European Association of Urology (EAU) mail list, to Young Urologist Office (YUO), Junior membership, European Urology Residents Education Program participants between 2014 and 2022, and other urologists under 40 yr, and via the EAU Newsletter. Intervention: A 64-item, online-based survey in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) using the platform of Survey Monkey (Portland, OR, USA) was realized. Outcome measurements and statistical analysis: The study involved an assessment of the demographic characteristics. Additionally, it explored the type of center, availability of various surgical approaches, presence of training infrastructure, participation in courses, organization of training, and participants' satisfaction with the training program. The level of satisfaction was evaluated using a Likert-5 scale. The subsequent sections delved into surgical training within the realms of open, laparoscopic, robotic, and endoscopic surgery, each explored separately. Finally, the investigation encompassed the presence of a structured training course and the availability of a duly validated final evaluation process. Results and limitations: There were 375 responders with a completion rate of 82%. Among them, 75% were identified as male, 50.6% were young urologists, 31.7% were senior residents, and 17.6% were junior residents. A significant majority of participants (69.6%) were affiliated with academic centers. Regarding the presence of dry lab training facilities, only 50.3% of respondents indicated its availability. Among these centers, 46.7% were primarily focused on laparoscopy training. The availability of virtual and wet lab training centers was even more limited, with rates of 31.5% and 16.2%, respectively. Direct patient involvement was reported in 80.5% of cases for open surgery, 58.8% for laparoscopy, 25.0% for robotics, and 78.6% for endourology. It is worth noting that in <25% of instances, training followed a well-defined standardized program comprising both preclinical and clinical modular phases. Finally, the analysis of participant feedback showed that 49.7% of respondents expressed a satisfaction rating of either 4 or 5 points with respect to the training program. The limitations of our study include the low response rate, predominance of participants from academic centers, and absence of responses from individuals not affiliated with the EAU network. Conclusions: The current distribution of surgical training centers falls short of ensuring widespread access to standardized training programs. Although dry lab facilities are relatively well spread, the availability of wet lab resources remains restricted. Additionally, it appears that many trainees' initial exposure to surgery occurs directly with patients. There is a pressing need for continued endeavors to establish uniform training routes and assessment techniques across various surgical methodologies. Patient summary: Nowadays, the surgical training landscape is heterogeneous across different countries. The implementation of a standardized training methodology to enhance the overall quality of surgical training and thereby improving patient outcomes is needed.

Biophotonics-Intraoperative Guidance During Partial Nephrectomy: A Systematic Review and Meta-analysis.

CONTEXT: Partial nephrectomy (PN) with intraoperative guidance by biophotonics has the potential to improve surgical outcomes due to higher precision. However, its value remains unclear since high-level evidence is lacking. OBJECTIVE: To provide a comprehensive analysis of biophotonic techniques used for intraoperative real-time assistance during PN. EVIDENCE ACQUISITION: We performed a comprehensive database search based on the PICO criteria, including studies published before October 2022. Two independent reviewers screened the titles and abstracts followed by full-text screening of eligible studies. For a quantitative analysis, a meta-analysis was conducted. EVIDENCE SYNTHESIS: In total, 35 studies were identified for the qualitative analysis, including 27 studies on near-infrared fluorescence (NIRF) imaging using indocyanine green, four studies on hyperspectral imaging, two studies on folate-targeted molecular imaging, and one study each on optical coherence tomography and 5-aminolevulinic acid. The meta-analysis investigated seven studies on selective arterial clamping using NIRF. There was a significantly shorter warm ischemia time in the NIRF-PN group (mean difference [MD]: -2.9; 95% confidence interval [CI]: -5.6, -0.1; p = 0.04). No differences were noted regarding transfusions (odds ratio [OR]: 0.5; 95% CI: 0.2, 1.7; p = 0.27), positive surgical margins (OR: 0.7; 95% CI: 0.2, 2.0; p = 0.46), or major complications (OR: 0.4; 95% CI: 0.1, 1.2; p = 0.08). In the NIRF-PN group, functional results were favorable at short-term follow-up (MD of glomerular filtration rate decline: 7.6; 95% CI: 4.6, 10.5; p < 0.01), but leveled off at long-term follow-up (MD: 7.0; 95% CI: -2.8, 16.9; p = 0.16). Remarkably, these findings were not confirmed by the included randomized controlled trial. CONCLUSIONS: Biophotonics comprises a heterogeneous group of imaging modalities that serve intraoperative decision-making and guidance. Implementation into clinical practice and cost effectiveness are the limitations that should be addressed by future research. PATIENT SUMMARY: We reviewed the application of biophotonics during partial removal of the kidney in patients with kidney cancer. Our results suggest that these techniques support the surgeon in successfully performing the challenging steps of the procedure.

Awareness and Use of ChatGPT and Large Language Models: A Prospective Cross-sectional Global Survey in Urology.

BACKGROUND: Since its release in November 2022, ChatGPT has captivated society and shown potential for various aspects of health care. OBJECTIVE: To investigate potential use of ChatGPT, a large language model (LLM), in urology by gathering opinions from urologists worldwide. DESIGN, SETTING, AND PARTICIPANTS: An open web-based survey was distributed via social media and e-mail chains to urologists between April 20, 2023 and May 5, 2023. Participants were asked to answer questions related to their knowledge and experience with artificial intelligence, as well as their opinions of potential use of ChatGPT/LLMs in research and clinical practice. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Data are reported as the mean and standard deviation for continuous variables, and the frequency and percentage for categorical variables. Charts and tables are used as appropriate, with descriptions of the chart types and the measures used. The data are reported in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). RESULTS AND LIMITATIONS: A total of 456 individuals completed the survey (64% completion rate). Nearly half (47.7%) reported that they use ChatGPT/LLMs in their academic practice, with fewer using the technology in clinical practice (19.8%). More than half (62.2%) believe there are potential ethical concerns when using ChatGPT for scientific or academic writing, and 53% reported that they have experienced limitations when using ChatGPT in academic practice. CONCLUSIONS: Urologists recognise the potential of ChatGPT/LLMs in research but have concerns regarding ethics and patient acceptance. There is a desire for regulations and guidelines to ensure appropriate use. In addition, measures should be taken to establish rules and guidelines to maximise safety and efficiency when using this novel technology. PATIENT SUMMARY: A survey asked 456 urologists from around the world about using an artificial intelligence tool called ChatGPT in their work. Almost half of them use ChatGPT for research, but not many use it for patients care. The resonders think ChatGPT could be helpful, but they worry about problems like ethics and want rules to make sure it's used safely.

A new era and future of education: the impact of pandemic on online learning - a study from the European School of Urology.

Introduction: In contemporary times, the online learning process has become indispensable for healthcare education. In this direction, the European School of Urology (ESU) has taken the challenge to implement new technologies to bring down knowledge barriers. Web-based seminars (webinars) are one of the tools that help us move towards such inclusivity, and in front-facing COVID-19 pandemic, when face-to-face meetings were forbidden. Material and methods: Data from ESU webinars was collected from 2016 to 2022. We described the trends through years of: a) number of webinars per year; b) number of oncological versus non-oncological webinars per year; c) number of registrations per year; d) attendance rate; e) YouTube visualisations. We also analysed audience demographics and COVID-19 impact. Results: We found a 60% increase in webinars launched per year with a trend towards more non-oncological webinars. A 94% rise in the number of registrations and an 85% increase in the attendance ratio from 2016 to 2022 was observed. The mean YouTube visualisations per webinar decreased over 200%. Among registrations, we had a 3:1 male: female ratio, 53% were older than 40, and a 51% were of European precedence. COVID-19 positively impacted webinars with a remarkable increase on the amount of webinars launched, number of registrations and attendance ratio. Conclusions: Webinars are a powerful tool to spread healthcare knowledge, bridging the gap in medical educational access. COVID-19 was a determinant that reinforced its implantation, but our data show that this new learning tool had a positive uptake, and has come to stay.

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.

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.

Discrimination, Reliability, Sensitivity, and Specificity of Robotic Surgical Proficiency Assessment With Global Evaluative Assessment of Robotic Skills and Binary Scoring Metrics: Results From a Randomized Controlled Trial.

Objective: To compare binary metrics and Global Evaluative Assessment of Robotic Skills (GEARS) evaluations of training outcome assessments for reliability, sensitivity, and specificity. Background: GEARS-Likert-scale skills assessment are a widely accepted tool for robotic surgical training outcome evaluations. Proficiency-based progression (PBP) training is another methodology but uses binary performance metrics for evaluations. Methods: In a prospective, randomized, and blinded study, we compared conventional with PBP training for a robotic suturing, knot-tying anastomosis task. Thirty-six surgical residents from 16 Belgium residency programs were randomized. In the skills laboratory, the PBP group trained until they demonstrated a quantitatively defined proficiency benchmark. The conventional group were yoked to the same training time but without the proficiency requirement. The final trial was video recorded and assessed with binary metrics and GEARS by robotic surgeons blinded to individual, group, and residency program. Sensitivity and specificity of the two assessment methods were evaluated with area under the curve (AUC) and receiver operating characteristics (ROC) curves. Results: The PBP group made 42% fewer objectively assessed performance errors than the conventional group (P < 0.001) and scored 15% better on the GEARS assessment (P = 0.033). The mean interrater reliability for binary metrics and GEARS was 0.87 and 0.38, respectively. Binary total error metrics AUC was 97% and for GEARS 85%. With a sensitivity threshold of 0.8, false positives rates were 3% and 25% for, respectively, the binary and GEARS assessments. Conclusions: Binary metrics for scoring a robotic VUA task demonstrated better psychometric properties than the GEARS assessment.

Digital Therapeutics in Urology: An Innovative Approach to Patient Care and Management.

Digital therapeutics (DTx) are a new class of intervention involving evidence-based software applications and have been used in neurology and psychiatry. To assess the potential of DTx in urology, we conducted a survey to assess the current prevalence of the digital infrastructure required for DTx, areas of support expected by patients, and requirements for uptake. Between November 2022 and January 2023, we conducted an anonymized survey at two German academic centers among patients with urologic conditions. We found that among patients aged <65 yr versus ≥65 yr, digital devices including smartphones (93.6% vs 77.3%; p < 0.001), computers (80.4% vs 70.1%; p < 0.001), tablets (51.7% vs 38.1%; p < 0.001), and smartwatches (24.7% vs 7.7%; p < 0.001) are already widely used, especially in the younger age group. Apps (95.6% vs 74.4%; p < 0.001) and health apps (57.6% vs 30.4%; p < 0.001) are already frequently used, but certified DTx apps are not (7.3% vs 5.4%; p = 0.25). Patients favor solutions that provide access to validated information (49.6%), give medical advice based on data or symptoms captured by the app (43.0%), or replace a physiotherapist (41.7%). Patients feel that optimization of therapy (78.4%), significant positive health outcomes (76.9%), and better patient autonomy (73.4%) are important requirements for DTx in urology. Regulatory and reimbursement changes mean that DTx might play an increasing role in urology. Patient summary: Patients can use digital therapeutics (DTx), which are mainly smartphone apps, to improve their health status or treat medical conditions. We assessed the current and future use of DTx in urology. Patients are already widely using smartphones and frequently use uncertified health apps, but do not use DTx. Patients would like to use DTx to optimize therapy that provides a significant health improvement.

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.

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.

Semen Analysis in "Urology-Naïve" Patients: A Chance of Uroandrological Screening in Young Males.

(1) Background: While females start their gynecological examinations during puberty, only few men decide to be visited by urologists in their youth. Given the participation in the EcoFoodFertility research project, our department had the opportunity to screen young males that were supposedly healthy. (2) Results: from January 2019 to July 2020, we evaluated 157 patients with sperm, blood analysis, and uroandrological examinations. The inclusion criteria were age 18-40 and absence of previous urological disease (urology-naïve). The primary endpoint of the study was to record uroandrological diseases that are occasionally discovered during examination in asymptomatic young men. The average age was 26.9 years (range 18-40); average testicular volume was 15.7 mL (range 12-22 mL); and 45.2% reported abnormal semen analysis: 62 cases of teratozoospermia, 27 asthenozoospermia, 18 oligozoospermia, and 2 azoospermia were discovered respectively; 4/157 patients were diagnosed with hypogonadism; 2 cases with suspicious testicular mass resulted in testicular cancer; and 31 suspected varicoceles and 8 patients with mild sexual dysfunctions were managed. (3) Conclusions: an uroandrological evaluation of young asymptomatic males allowed for the prompt diagnosis of different urological conditions, including cancerous ones, in our series. Despite being debatable, combining urological counselling with physical examination, semen analysis, and a laboratory profile could be useful and cost-effective in order to ameliorate male health.

The Long but Necessary Journey Towards Optimization of the Cause-Effect Relationship Between Input and Output for Accountable Use of ChatGPT for Academic Purposes.

The use of appropriate inputs can significantly improve the outputs obtained from ChatGPT for academic research.

A systematic review and meta-analysis of artificial intelligence diagnostic accuracy in prostate cancer histology identification and grading.

BACKGROUND: Artificial intelligence (AI) is a promising tool in pathology, including cancer diagnosis, subtyping, grading, and prognostic prediction. METHODS: The aim of the study is to assess AI application in prostate cancer (PCa) histology. We carried out a systematic literature search in 3 databases. Primary outcome was AI accuracy in differentiating between PCa and benign hyperplasia. Secondary outcomes were AI accuracy in determining Gleason grade and agreement among AI and pathologists. RESULTS: Our final sample consists of 24 studies conducted from 2007 to 2021. They aggregate data from roughly 8000 cases of prostate biopsy and 458 cases of radical prostatectomy (RP). Sensitivity for PCa diagnostic exceeded 90% and ranged from 87% to 100%, and specificity varied from 68% to 99%. Overall accuracy ranged from 83.7% to 98.3% with AUC reaching 0.99. The meta-analysis using the Mantel-Haenszel method showed pooled sensitivity of 0.96 with I2 = 80.7% and pooled specificity of 0.95 with I2 = 86.1%. Pooled positive likehood ratio was 15.3 with I2 = 87.3% and negative - was 0.04 with I2 = 78.6%. SROC (symmetric receiver operating characteristics) curve represents AUC = 0.99. For grading the accuracy of AI was lower: sensitivity for Gleason grading ranged from 77% to 87%, and specificity from 82% to 90%. CONCLUSIONS: The accuracy of AI for PCa identification and grading is comparable to expert pathologists. This is a promising approach which has several possible clinical applications resulting in expedite and optimize pathology reports. AI introduction into common practice may be limited by difficult and time-consuming convolutional neural network training and tuning.

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.