Michael Kim1, Shawna L Boyle2, Alfonso Fernandez2, Edward D Matsumoto3, Kenneth T Pace4, Maurice Anidjar5, Gregory N Kozak6, Sumit Davé7, Blayne K Welk2, Marjorie I Johnson1, Stephen E Pautler8. 1. Division of Clinical Anatomy, Department of Anatomy & Cell Biology, Western University, London, ON; 2. Division of Urology, Department of Surgery, Western University, London, ON; 3. Division of Urology, Department of Surgery, McMaster University, Hamilton, ON; 4. Division of Urology, Department of Surgery, University of Toronto, Toronto, ON; 5. Division of Urology, Department of Surgery, McGill University, Montreal, QC; 6. Division of Urology, Department of Surgery, University of Calgary, Calgary, AB; 7. Division of Urology, Department of Surgery, Western University, London, ON; ; Division of Urology, Department of Pediatrics, Western University, London, ON; 8. Division of Urology, Department of Surgery, Western University, London, ON; ; Division of Surgical Oncology, Department of Oncology, Western University, London, ON.
Abstract
INTRODUCTION: We propose a novel classification system with a validation study to help clinicians identify and typify commonly seen variants of the puboprostatic ligaments (PPL). METHODS: A preliminary dissection of 6 male cadavers and a prospective dataset of over 300 robotic-assisted laparoscopic radical prostatectomies (RARP) recorded on video were used to identify 4 distinct ligament types. Then the prospectively collected database of surgical videos was used to isolate images of the PPL from RARP. Over 300 surgical videos were reviewed and classified with 1 to 5 pictures saved for reference of the type of PPL. To validate the new classification system, we selected 5 independent, blinded expert robotic surgeons to classify 100 ligaments based on morphology into a 4-type system: parallel, V-shaped, inverted V-shape, and fused. One week later, a subset of 25 photographs was sent to the same experts and classified. Statistical analyses were performed to determine both the intra-rater and inter-rater reliability of the proposed system. RESULTS: Inverted V-shaped ligaments were noted most frequently (29.97%), parallel and V-shaped ligaments were found at 19.19% and 11.11%, respectively and fused ligaments were noted less frequently (6.06%). There was good intra-rater agreement (κ = 0.66) and inter-rater agreement (κ = 0.67) for the classification system. CONCLUSIONS: This classification system provided standardized descriptions of ligament variations that could be adopted universally to help clinicians categorize the variants. The system, validated by several blinded expert surgeons, demonstrated that surgeons were able to learn and correctly classify the variants. The system may be useful in helping to predict peri- and postoperative outcomes; however, this will require further study.
INTRODUCTION: We propose a novel classification system with a validation study to help clinicians identify and typify commonly seen variants of the puboprostatic ligaments (PPL). METHODS: A preliminary dissection of 6 male cadavers and a prospective dataset of over 300 robotic-assisted laparoscopic radical prostatectomies (RARP) recorded on video were used to identify 4 distinct ligament types. Then the prospectively collected database of surgical videos was used to isolate images of the PPL from RARP. Over 300 surgical videos were reviewed and classified with 1 to 5 pictures saved for reference of the type of PPL. To validate the new classification system, we selected 5 independent, blinded expert robotic surgeons to classify 100 ligaments based on morphology into a 4-type system: parallel, V-shaped, inverted V-shape, and fused. One week later, a subset of 25 photographs was sent to the same experts and classified. Statistical analyses were performed to determine both the intra-rater and inter-rater reliability of the proposed system. RESULTS: Inverted V-shaped ligaments were noted most frequently (29.97%), parallel and V-shaped ligaments were found at 19.19% and 11.11%, respectively and fused ligaments were noted less frequently (6.06%). There was good intra-rater agreement (κ = 0.66) and inter-rater agreement (κ = 0.67) for the classification system. CONCLUSIONS: This classification system provided standardized descriptions of ligament variations that could be adopted universally to help clinicians categorize the variants. The system, validated by several blinded expert surgeons, demonstrated that surgeons were able to learn and correctly classify the variants. The system may be useful in helping to predict peri- and postoperative outcomes; however, this will require further study.
Authors: Ran Katz; Laurent Salomon; Andras Hoznek; Alexandre de la Taille; Patrick Antiphon; Clement Claude Abbou Journal: J Urol Date: 2003-06 Impact factor: 7.450