Impact of three-dimensional prostate models during robot-assisted radical prostatectomy on surgical margins and functional outcomes.

Background: Robot-assisted radical prostatectomy (RARP) is the standard surgical procedure for the treatment of prostate cancer. RARP requires a trade-off between performing a wider resection in order to reduce the risk of positive surgical margins (PSMs) and performing minimal resection of the nerve bundles that determine functional outcomes, such as incontinence and potency, which affect patients' quality of life. In order to achieve favourable outcomes, a precise understanding of the three-dimensional (3D) anatomy of the prostate, nerve bundles and tumour lesion is needed.

SWAG: long-term surgical workflow prediction with generative-based anticipation.

Purpose: While existing approaches excel at recognising current surgical phases, they provide limited foresight and intraoperative guidance into future procedural steps. Similarly, current anticipation methods are constrained to predicting short-term and single events, neglecting the dense, repetitive, and long sequential nature of surgical workflows. To address these needs and limitations, we propose SWAG (surgical workflow anticipative generation), a framework that combines phase recognition and anticipation using a generative approach.

Mental well-being in prostate cancer: A multi-institutional prospective cohort study.

Objective: To investigate the patient, treatment and oncological prognostic factors for multiple mental well-being outcomes in prostate cancer.

Patient And Methods: The MIND-P study was a multi-institutional prospective cohort study recruiting newly diagnosed prostate cancer patients for 12 months post-diagnosis across eight centres. Periodic data collection evaluated mental, physical and social well-being measures incorporating five mental well-being outcomes selected based on prior research as important measures in patients with prostate cancer.

A registry-based modified IDEAL stage 2b evaluation of urological procedures performed using the versius robotic surgical system.

The IDEAL stage 1/2a study demonstrated feasibility of the use of the Versius robotic platform at a single institution. This multi-center collaborative modified stage 2b study adds wider exploration assessing surgical, oncologic and functional outcomes in patients undergoing urological procedures with the Versius. Data were collected from a prospective registry.

Early clinical evaluation of the Hugo robotic-assisted surgery (RAS) for performing radical prostatectomy: an IDEAL stage 2 study.

Objectives: To assess the feasibility and safety of the new Hugo robotic-assisted surgery (RAS) system for robotic-assisted radical prostatectomy (RARP), describing iterative changes in our operative technique-IDEAL stage 2.

Design: Prospective, single-centre series.

Setting: Tertiary urological unit in London, UK.

Ethical aspects of artificial intelligence: what urologists need to know.

Purpose Of Review: The integration of artificial intelligence in urology presents both transformative opportunities and ethical dilemmas. As artificial intelligence driven tools become more prevalent in diagnostics, robotic-assisted surgeries, and patient monitoring, it is crucial for urologists to understand the ethical implications of these technologies. This review examines key ethical concerns surrounding artificial intelligence in urology, including bias, transparency, accountability, and data privacy.

Impact of low-pressure pneumoperitoneum on post-operative pain in robotic urological surgery: a systematic review.

Robotic technology has revolutionised minimally invasive urological surgery, enhancing precision and minimising surgical complications. Recent evidence suggests that utilising lower pneumoperitoneum pressures improves clinical outcomes but the comparative impact on post-operative pain remains uncertain. This systematic review analyses the literature on low-pressure pneumoperitoneum to investigate its impact on pain and recovery following robotic-assisted urological surgeries, including prostatectomy, partial ephrectomy, and cystectomy.

MUTUAL: Towards Holistic Sensing and Inference in the Operating Room.

Embodied AI (E-AI) in the form of intelligent surgical robotics and other agents is calling for data platforms to facilitate its development and deployment. In this work, we present a cross-platform multimodal data recording and streaming software, MUTUAL, successfully deployed on two clinical studies, along with its ROS 2 distributed adaptation, MUTUAL-ROS 2. We describe and compare the two implementations of MUTUAL through their recording performance under different settings.

A Systematic Review of Simulation-Based Training Tools in Plastic Surgery.

Objectives: The recent shift from traditional surgical teaching to the incorporation of simulation training in plastic surgery has resulted in the development of a variety of simulation models and tools. We aimed to assess the validity and establish the effectiveness of all currently available simulators and tools for plastic surgery.

Design: Systematic review.

Indian consensus statements on the management of small renal masses, non-muscle invasive bladder cancer and high-risk/locally advanced prostate cancer.

No pan-India-specific guidelines exist for the management of urological cancers. Although western guidelines are useful for informing management strategies, they do not account for the nuances of management in the Indian context. A modified Delphi method was used to provide a framework for the systematic development of India-centric guidelines for the management of three uro-oncology disease states: small renal masses, non-muscle invasive bladder cancer and high-risk/locally advanced prostate cancer.

AI solutions for overcoming delays in telesurgery and telementoring to enhance surgical practice and education.

Artificial intelligence (AI) has emerged as a transformative tool in surgery, particularly in telesurgery and telementoring. However, its potential to enhance data transmission efficiency and reliability in these fields remains unclear. While previous reviews have explored the general applications of telesurgery and telementoring in specific surgical contexts, this review uniquely focuses on AI models designed to optimise data transmission and mitigate delays.

LoViT: Long Video Transformer for surgical phase recognition.

Online surgical phase recognition plays a significant role towards building contextual tools that could quantify performance and oversee the execution of surgical workflows. Current approaches are limited since they train spatial feature extractors using frame-level supervision that could lead to incorrect predictions due to similar frames appearing at different phases, and poorly fuse local and global features due to computational constraints which can affect the analysis of long videos commonly encountered in surgical interventions. In this paper, we present a two-stage method, called Long Video Transformer (LoViT), emphasizing the development of a temporally-rich spatial feature extractor and a phase transition map.

Development of a Bladder Injury Classification System for Endoscopic Procedures: A Mixed-methods Study Involving Expert Consensus and Validation.

Background And Objective: The widespread adoption and rapid integration of new technologies and techniques in endoscopic and laser bladder interventions, particularly endoscopic enucleation, have led to new types of bladder injuries. This underscores the need for an intraoperative injury classification system. This study aims to develop and validate the Bladder Injury Classification System for Endoscopic Procedures (BICEP), which standardizes the classification of complications and intervention requirements.

Optimising prostate biopsies and imaging for the future-a review.

Conventionally, transrectal ultrasound guided prostate biopsy (TRUS-Bx) was the main technique used for the diagnosis of prostate cancer since it was first described in 1989 [1]. However, the PROMIS trial showed that this random, nontargeted approach could miss up to 18% of clinically significant cancer (csPCa) [2]. Furthermore, risk of sepsis post TRUS-Bx can be as high as 2.