The goal is to have a small spectrometer (pocket size) , reliable and rapid tool that can be used during liver harvesting, which enables macrosteatosis to be evaluated reproducibly and selectively, at any time. This tool must be minimally invasive, inexpensive and without significantly impacting the general organization of multi-organ harvesting. In the operating room, the surgeon will perform an intraoperative spectrometer scan (five scans on the left lobe) before clamping the aorta. The surgeon will not be informed of the results of the spectrometer, and will carry out (or not) the biopsy. The spectrometers' results will be compared with definitive histological findings.
Study Type
OBSERVATIONAL
Enrollment
240
intraoperative spectrometer scan (five scans on the left lobe) before clamping the aorta
Centre Hépato Biliaire de l'hopital Paul Brousse
Villejuif, France
RECRUITINGHôpital Beaujon
Clichy, Île-de-France Region, France
RECRUITINGHôpital Pitié-Salpetriere
Paris, Île-de-France Region, France
RECRUITINGEvaluate the concordance between the macrosteatosis quantified by the pocket spectrometer and the macrosteatosis content evaluated by the standard pathological analysis
Agreement (intra-class correlation coefficient) between the% of macrosteatosis estimated by the pocket spectrometer and that quantified by the pathologist on biopsy (final results only)
Time frame: J0 = intraoperative
Evaluation of the spectrometer performance for diagnosis to detect macrosteatosis> 30% and> 60% taking the pathology as a reference standard
Area under the ROC curve (AUC), sensitivity, specificity, likelihood ratio and predictive values of the spectrometer to detect macrosteatosis\> 30% and\> 60%
Time frame: J0 = intraoperative
Assessment of the technical feasibility of using the spectrometer in daily practice, analysis of the causes and incidence of failures (technical or organizational)
Number of time where the measurement by the pocket spectrometer was successful, ie where it was possible to perform the scans and obtain an estimate of the macrosteatosis, and description of the causes for failure.
Time frame: J0 = intraoperative
Estimation of the concordance between the macrosteatosis values provided by the frozen section analysis, if performed, and the definitive pathology and comparison with the concordance of the pocket spectrometer estimated for the primary objective
Agreement (intra-class correlation coefficient) between the% of macrosteatosis estimated by the pathologist extemporaneously when performed and te one quantified by the pathologist on biopsy (final results only).
Time frame: J0 = intraoperative
Assessment of the concordance between the macrosteatosis visually assessed by the harvesting surgeon and the definitive pathological data
Agreement (kappa coefficient) between the% of macrosteatosis macroscopically estimated by the pathologist (in 3 categories: 0-30%, 31-60%,\> 60%) and that quantified by the pathologist on biopsy (final results only )
Time frame: J0 = intraoperative
Evaluation of the potential impact of spectrometer results on the surgeon's decision to accept the graft using simulated results
Percentage of acquisitions where the operator would have modified his decision (accept / reject the graft) if the spectrometer estimate had been communicated (scenarios simulated in the questionnaires)
Time frame: J0 = intraoperative
Modification and improvement of the current algorithm based on the spectra of the entire cohort in order to assess the gain in "spectrometer - anatomopathology"
Agreement (intra-class correlation coefficient) between the percentage of macrosteatosis estimated by the spectrometer using the second version of the algorithm and the macrosteatosis quantified by pathology
Time frame: J0 = intraoperative
Attempt to create a microsteatosis prediction algorithm (version 3) using data from the global cohort
Agreement (intra-class correlation coefficient) between the percentage of microsteatosis estimated by the spectrometer and the microsteatosis quantified by the pathology
Time frame: J0 = intraoperative
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