Predicting the quality of surgical exposure using spatial and procedural features from laparoscopic videos

Autor: Sandrine Voros, Bernard Gibaud, Arthur Derathé, Fabian Reche, Alexandre Moreau-Gaudry, Pierre Jannin
Přispěvatelé: Gestes Medico-chirurgicaux Assistés par Ordinateur (TIMC-GMCAO), Translational Innovation in Medicine and Complexity / Recherche Translationnelle et Innovation en Médecine et Complexité - UMR 5525 (TIMC ), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre Hospitalier Universitaire [Grenoble] (CHU), Centre d'Investigation Clinique - Innovation Technologique - INSERM - CHU de Grenoble (CIC-IT Grenoble (CIT803)), CHU Grenoble-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM), ANR-11-LABX-0004, Agence Nationale de la Recherche, ANR-11-LABX-0004,CAMI,Gestes Médico-Chirurgicaux Assistés par Ordinateur(2011), ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Voros, Sandrine, Gestes Médico-Chirurgicaux Assistés par Ordinateur - - CAMI2011 - ANR-11-LABX-0004 - LABX - VALID, MIAI @ Grenoble Alpes - - MIAI2019 - ANR-19-P3IA-0003 - P3IA - VALID
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Laparoscopic surgery
Sleeve gastrectomy
Support Vector Machine
[SDV.BIO]Life Sciences [q-bio]/Biotechnology
[SDV.MHEP.CHI] Life Sciences [q-bio]/Human health and pathology/Surgery
Computer science
medicine.medical_treatment
0206 medical engineering
[INFO.INFO-IM] Computer Science [cs]/Medical Imaging
Video Recording
Biomedical Engineering
Health Informatics
[SDV.CAN]Life Sciences [q-bio]/Cancer
02 engineering and technology
[SDV.MHEP.CHI]Life Sciences [q-bio]/Human health and pathology/Surgery
[SDV.MHEP.UN]Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
[SDV.CAN] Life Sciences [q-bio]/Cancer
Gastrectomy
Video-based analysis
medicine
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Humans
Radiology
Nuclear Medicine and imaging
[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
business.industry
Pattern recognition
Surgical expertise
General Medicine
Surgical procedures
Linear discriminant analysis
[SDV.MHEP.UN] Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology
020601 biomedical engineering
Computer Graphics and Computer-Aided Design
[SDV.BIO] Life Sciences [q-bio]/Biotechnology
Computer Science Applications
Support vector machine
Surgical exposure
Laparoscopy
Surgery
Computer Vision and Pattern Recognition
Artificial intelligence
business
Classifier (UML)
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Algorithms
Zdroj: International Journal of Computer Assisted Radiology and Surgery
International Journal of Computer Assisted Radiology and Surgery, Springer Verlag, 2020, 15 (1), pp.59-67. ⟨10.1007/s11548-019-02072-3⟩
International Journal of Computer Assisted Radiology and Surgery, 2020, 15 (1), pp.59-67. ⟨10.1007/s11548-019-02072-3⟩
ISSN: 1861-6410
1861-6429
Popis: PURPOSE : Evaluating the quality of surgical procedures is a major concern in minimally invasive surgeries. We propose a bottom-up approach based on the study of Sleeve Gastrectomy procedures, for which we analyze what we assume to be an important indicator of the surgical expertise: the exposure of the surgical scene. We first aim at predicting this indicator with features extracted from the laparoscopic video feed, and second to analyze how the extracted features describing the surgical practice influence this indicator. METHOD : Twenty-nine patients underwent Sleeve Gastrectomy performed by two confirmed surgeons in a monocentric study. Features were extracted from spatial and procedural annotations of the videos, and an expert surgeon evaluated the quality of the surgical exposure at specific instants. The features were used as input of a classifier (linear discriminant analysis followed by a support vector machine) to predict the expertise indicator. Features selected in different configurations of the algorithm were compared to understand their relationships with the surgical exposure and the surgeon's practice. RESULTS : The optimized algorithm giving the best performance used spatial features as input ([Formula: see text]). It also predicted equally the two classes of the indicator, despite their strong imbalance. Analyzing the selection of input features in the algorithm allowed a comparison of different configurations of the algorithm and showed a link between the surgical exposure and the surgeon's practice. CONCLUSION : This preliminary study validates that a prediction of the surgical exposure from spatial features is possible. The analysis of the clusters of feature selected by the algorithm also shows encouraging results and potential clinical interpretations.
Databáze: OpenAIRE
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