Exploring the Use of Artificial Intelligence in the Management of Prostate Cancer.

PURPOSE OF REVIEW: This review aims to explore the current state of research on the use of artificial intelligence (AI) in the management of prostate cancer. We examine the various applications of AI in prostate cancer, including image analysis, prediction of treatment outcomes, and patient stratification. Additionally, the review will evaluate the current limitations and challenges faced in the implementation of AI in prostate cancer management. RECENT FINDINGS: Recent literature has focused particularly on the use of AI in radiomics, pathomics, the evaluation of surgical skills, and patient outcomes. AI has the potential to revolutionize the future of prostate cancer management by improving diagnostic accuracy, treatment planning, and patient outcomes. Studies have shown improved accuracy and efficiency of AI models in the detection and treatment of prostate cancer, but further research is needed to understand its full potential as well as limitations.

SCiPad: evaluating telemedicine via iPad facetime for general spinal cord injury care.

STUDY DESIGN: Uncontrolled clinical pilot study. OBJECTIVES: To assess usage, perceived impact, and satisfaction with a telemedicine program among individuals with spinal cord injury (tele-SCI). SETTING: Community-based. METHODS: Participants (N = 83) were recruited from acute SCI inpatient rehabilitation and outpatient SCI care at a community hospital to participate in a 6-month tele-SCI intervention administered by SCI subspecialty board-certified physiatrists via iPad FaceTime. In addition to monthly follow up interview calls, psychosocial and Quality of Life (QoL) measures were collected at baseline and post-intervention. A program satisfaction survey was also collected post-intervention. RESULTS: Seventy-five percent of participants engaged in tele-SCI visits (Median [IQR]: 2.5 [2.0, 4.0]) for a total of 198 tele-SCI visits. Bladder and bowel concerns were the leading topics discussed during tele-SCI visits, followed by neurological, pain, and functional concerns. Tele-SCI users resided further away (Median miles [IQR] - 114[73-177] vs. 81[46-116], p = 0.023) and reported seeking more clinical advice (Median [IQR] - 1.5[0-4.0] vs. 0[0-1.0], p = 0.002) compared to non-tele-SCI users. All other clinical utilization, baseline characteristics, psychosocial measures, and QoL did not differ among those who used tele-SCI and those who did not. The satisfaction survey suggested satisfaction with the tele-SCI intervention (89%), study equipment (89%), staff responsiveness (100%), and improved motivation for self-monitoring of health (71%). CONCLUSION: Study findings suggest that tele-SCI is a feasible modality for providing general SCI care. Further research is required to examine longer-term efficacy of remotely-provided care among individuals living with SCI.

Surgical gestures to evaluate apical dissection of robot-assisted radical prostatectomy.

Previously, our group established a surgical gesture classification system that deconstructs robotic tissue dissection into basic surgical maneuvers. Here, we evaluate gestures by correlating the metric with surgeon experience and technical skill assessment scores in the apical dissection (AD) of robotic-assisted radical prostatectomy (RARP). Additionally, we explore the association between AD performance and early continence recovery following RARP. 78 AD surgical videos from 2016 to 2018 across two international institutions were included. Surgeons were grouped by median robotic caseload (range 80-5,800 cases): less experienced group (< 475 cases) and more experienced (≥ 475 cases). Videos were decoded with gestures and assessed using Dissection Assessment for Robotic Technique (DART). Statistical findings revealed more experienced surgeons (n = 10) used greater proportions of cold cut (p = 0.008) and smaller proportions of peel/push, spread, and two-hand spread (p < 0.05) than less experienced surgeons (n = 10). Correlations between gestures and technical skills assessments ranged from - 0.397 to 0.316 (p < 0.05). Surgeons utilizing more retraction gestures had lower total DART scores (p < 0.01), suggesting less dissection proficiency. Those who used more gestures and spent more time per gesture had lower efficiency scores (p < 0.01). More coagulation and hook gestures were found in cases of patients with continence recovery compared to those with ongoing incontinence (p < 0.04). Gestures performed during AD vary based on surgeon experience level and patient continence recovery duration. Significant correlations were demonstrated between gestures and dissection technical skills. Gestures can serve as a novel method to objectively evaluate dissection performance and anticipate outcomes.

Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study.

Introduction: Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of artificial intelligence (AI)-based feedback on a robotic suturing task. Materials and Methods: Forty-two participants with no robotic surgical experience were randomized to a control or feedback group and video-recorded while completing two rounds (R1 and R2) of suturing tasks on a da Vinci surgical robot. Participants were assessed on needle handling and needle driving, and feedback was provided via a visual interface after R1. For feedback group, participants were informed of their AI-based skill assessment and presented with specific video clips from R1. For control group, participants were presented with randomly selected video clips from R1 as a placebo. Participants from each group were further labeled as underperformers or innate-performers based on a median split of their technical skill scores from R1. Results: Demographic features were similar between the control (n = 20) and feedback group (n = 22) (p > 0.05). Observing the improvement from R1 to R2, the feedback group had a significantly larger improvement in needle handling score (0.30 vs -0.02, p = 0.018) when compared with the control group, although the improvement of needle driving score was not significant when compared with the control group (0.17 vs -0.40, p = 0.074). All innate-performers exhibited similar improvements across rounds, regardless of feedback (p > 0.05). In contrast, underperformers in the feedback group improved more than the control group in needle handling (p = 0.02). Conclusion: AI-based feedback facilitates surgical trainees' acquisition of robotic technical skills, especially underperformers. Future research will extend AI-based feedback to additional suturing skills, surgical tasks, and experience groups.

Development of a Classification System for Live Surgical Feedback.

Importance: Live feedback in the operating room is essential in surgical training. Despite the role this feedback plays in developing surgical skills, an accepted methodology to characterize the salient features of feedback has not been defined. Objective: To quantify the intraoperative feedback provided to trainees during live surgical cases and propose a standardized deconstruction for feedback. Design, Setting, and Participants: In this qualitative study using a mixed methods analysis, surgeons at a single academic tertiary care hospital were audio and video recorded in the operating room from April to October 2022. Urological residents, fellows, and faculty attending surgeons involved in robotic teaching cases during which trainees had active control of the robotic console for at least some portion of a surgery were eligible to voluntarily participate. Feedback was time stamped and transcribed verbatim. An iterative coding process was performed using recordings and transcript data until recurring themes emerged. Exposure: Feedback in audiovisual recorded surgery. Main Outcomes and Measures: The primary outcomes were the reliability and generalizability of a feedback classification system in characterizing surgical feedback. Secondary outcomes included assessing the utility of our system. Results: In 29 surgical procedures that were recorded and analyzed, 4 attending surgeons, 6 minimally invasive surgery fellows, and 5 residents (postgraduate years, 3-5) were involved. For the reliability of the system, 3 trained raters achieved moderate to substantial interrater reliability in coding cases using 5 types of triggers, 6 types of feedback, and 9 types of responses (prevalence-adjusted and bias-adjusted κ range: a 0.56 [95% CI, 0.45-0.68] minimum for triggers to a 0.99 [95% CI, 0.97-1.00] maximum for feedback and responses). For the generalizability of the system, 6 types of surgical procedures and 3711 instances of feedback were analyzed and coded with types of triggers, feedback, and responses. Significant differences in triggers, feedback, and responses reflected surgeon experience level and surgical task being performed. For example, as a response, attending surgeons took over for safety concerns more often for fellows than residents (prevalence rate ratio [RR], 3.97 [95% CI, 3.12-4.82]; P = .002), and suturing involved more errors that triggered feedback than dissection (RR, 1.65 [95% CI, 1.03-3.33]; P = .007). For the utility of the system, different combinations of trainer feedback had associations with rates of different trainee responses. For example, technical feedback with a visual component was associated with an increased rate of trainee behavioral change or verbal acknowledgment responses (RR, 1.11 [95% CI, 1.03-1.20]; P = .02). Conclusions and Relevance: These findings suggest that identifying different types of triggers, feedback, and responses may be a feasible and reliable method for classifying surgical feedback across several robotic procedures. Outcomes suggest that a system that can be generalized across surgical specialties and for trainees of different experience levels may help galvanize novel surgical education strategies.

A Multi-institution Study on the Association of Virtual Reality Skills with Continence Recovery after Robot-assisted Radical Prostatectomy.

BACKGROUND: Virtual reality (VR) simulators are increasingly being used for surgical skills training. It is unclear what skills are best improved via VR, translate to live surgical skills, and influence patient outcomes. OBJECTIVE: To assess surgeons in VR and live surgery using a suturing assessment tool and evaluate the association between technical skills and a clinical outcome. DESIGN, SETTING, AND PARTICIPANTS: This prospective five-center study enrolled participants who completed VR suturing exercises and provided live surgical video. Graders provided skill assessments using the validated End-To-End Assessment of Suturing Expertise (EASE) suturing evaluation tool. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A hierarchical Poisson model was used to compare skill scores among cohorts and evaluate the association of scores with clinical outcomes. Spearman's method was used to assess correlation between VR and live skills. RESULTS AND LIMITATIONS: Ten novices, ten surgeons with intermediate expertise (median 64 cases, interquartile range [IQR] 6-80), and 26 expert surgeons (median 850 cases, IQR 375-3000) participated in this study. Intermediate and expert surgeons were significantly more likely to have ideal scores in comparison to novices for the subskills needle hold angle, wrist rotation, and wrist rotation needle withdrawal (p < 0.01). For both intermediate and expert surgeons, there was positive correlation between VR and live skills for needle hold angle (p < 0.05). For expert surgeons, there was a positive association between ideal scores for VR needle hold angle and driving smoothness subskills and 3-mo continence recovery (p < 0.05). Limitations include the size of the intermediate surgeon sample and clinical data limited to expert surgeons. CONCLUSIONS: EASE can be used in VR to identify skills to improve for trainee surgeons. Technical skills that influence postoperative outcomes may be assessable in VR. PATIENT SUMMARY: This study provides insights into surgical skills that translate from virtual simulation to live surgery and that have an impact on urinary continence after robot-assisted removal of the prostate. We also highlight the usefulness of virtual reality in surgical education.

Using Real-time Feedback To Improve Surgical Performance on a Robotic Tissue Dissection Task.

Background: There is no standard for the feedback that an attending surgeon provides to a training surgeon, which may lead to variable outcomes in teaching cases. Objective: To create and administer standardized feedback to medical students in an attempt to improve performance and learning. Design setting and participants: A cohort of 45 medical students was recruited from a single medical school. Participants were randomly assigned to two groups. Both completed two rounds of a robotic surgical dissection task on a da Vinci Xi surgical system. The first round was the baseline assessment. In the second round, one group received feedback and the other served as the control (no feedback). Outcome measurements and statistical analysis: Video from each round was retrospectively reviewed by four blinded raters and given a total error tally (primary outcome) and a technical skills score (Global Evaluative Assessment of Robotic Surgery [GEARS]). Generalized linear models were used for statistical modeling. According to their initial performance, each participant was categorized as either an innate performer or an underperformer, depending on whether their error tally was above or below the median. Results and limitations: In round 2, the intervention group had a larger decrease in error rate than the control group, with a risk ratio (RR) of 1.51 (95% confidence interval [CI] 1.07-2.14; p = 0.02). The intervention group also had a greater increase in GEARS score in comparison to the control group, with a mean group difference of 2.15 (95% CI 0.81-3.49; p < 0.01). The interaction effect between innate performers versus underperformers and the intervention was statistically significant for the error rates, at F(1,38) = 5.16 (p = 0.03). Specifically, the intervention had a statistically significant effect on the error rate for underperformers (RR 2.23, 95% CI 1.37-3.62; p < 0.01) but not for innate performers (RR 1.03, 95% CI 0.63-1.68; p = 0.91). Conclusions: Real-time feedback improved performance globally compared to the control. The benefit of real-time feedback was stronger for underperformers than for trainees with innate skill. Patient summary: We found that real-time feedback during a training task using a surgical robot improved the performance of trainees when the task was repeated. This feedback approach could help in training doctors in robotic surgery.

Surgical gestures as a method to quantify surgical performance and predict patient outcomes.

How well a surgery is performed impacts a patient's outcomes; however, objective quantification of performance remains an unsolved challenge. Deconstructing a procedure into discrete instrument-tissue "gestures" is a emerging way to understand surgery. To establish this paradigm in a procedure where performance is the most important factor for patient outcomes, we identify 34,323 individual gestures performed in 80 nerve-sparing robot-assisted radical prostatectomies from two international medical centers. Gestures are classified into nine distinct dissection gestures (e.g., hot cut) and four supporting gestures (e.g., retraction). Our primary outcome is to identify factors impacting a patient's 1-year erectile function (EF) recovery after radical prostatectomy. We find that less use of hot cut and more use of peel/push are statistically associated with better chance of 1-year EF recovery. Our results also show interactions between surgeon experience and gesture types-similar gesture selection resulted in different EF recovery rates dependent on surgeon experience. To further validate this framework, two teams independently constructe distinct machine learning models using gesture sequences vs. traditional clinical features to predict 1-year EF. In both models, gesture sequences are able to better predict 1-year EF (Team 1: AUC 0.77, 95% CI 0.73-0.81; Team 2: AUC 0.68, 95% CI 0.66-0.70) than traditional clinical features (Team 1: AUC 0.69, 95% CI 0.65-0.73; Team 2: AUC 0.65, 95% CI 0.62-0.68). Our results suggest that gestures provide a granular method to objectively indicate surgical performance and outcomes. Application of this methodology to other surgeries may lead to discoveries on methods to improve surgery.

Inter-eye genomic heterogeneity in bilateral retinoblastoma via aqueous humor liquid biopsy.

Germline alterations in the RB1 tumor suppressor gene predispose patients to develop retinoblastoma (RB) in both eyes. While similar treatment is given for each eye, there is often a variable therapeutic response between the eyes. Herein, we use the aqueous humor (AH) liquid biopsy to evaluate the cell-free tumor DNA (ctDNA) from each eye in a patient with bilateral RB. Despite the same predisposing germline RB1 mutation, AH analysis identified a different somatic RB1 mutation as well as separate and distinct chromosomal alterations in each eye. The longitudinal alterations in tumor fraction (TFx) corresponded to therapeutic responses in each eye. This case demonstrates that bilateral RB tumors develop separate genomic alterations, which may play a role in tumorigenesis and prognosis for eye salvage. Identifying these inter-eye differences without the need for enucleated tumor tissue may help direct active management of RB, with particular usefulness in bilateral cases.