Early Operative Difficulty Assessment in Laparoscopic Cholecystectomy via Snapshot-Centric Video Analysis
Journal:
arXiv
Published Date:
Feb 10, 2025
Abstract
Purpose: Laparoscopic cholecystectomy (LC) operative difficulty (LCOD) is
highly variable and influences outcomes. Despite extensive LC studies in
surgical workflow analysis, limited efforts explore LCOD using intraoperative
video data. Early recognition of LCOD could allow prompt review by expert
surgeons, enhance operating room (OR) planning, and improve surgical outcomes.
Methods: We propose the clinical task of early LCOD assessment using limited
video observations. We design SurgPrOD, a deep learning model to assess LCOD by
analyzing features from global and local temporal resolutions (snapshots) of
the observed LC video. Also, we propose a novel snapshot-centric attention
(SCA) module, acting across snapshots, to enhance LCOD prediction. We introduce
the CholeScore dataset, featuring video-level LCOD labels to validate our
method.
Results: We evaluate SurgPrOD on 3 LCOD assessment scales in the CholeScore
dataset. On our new metric assessing early and stable correct predictions,
SurgPrOD surpasses baselines by at least 0.22 points. SurgPrOD improves over
baselines by at least 9 and 5 percentage points in F1 score and top1-accuracy,
respectively, demonstrating its effectiveness in correct predictions.
Conclusion: We propose a new task for early LCOD assessment and a novel
model, SurgPrOD analyzing surgical video from global and local perspectives.
Our results on the CholeScore dataset establishes a new benchmark to study LCOD
using intraoperative video data.
