Open AccessAssessment of Inter-Expert Variability and of an Automated Segmentation Method of 40 and 60 MHz IVUS Images of Coronary Arteries
Author(s) -
François Destrempes,
MarieHélène Roy Cardinal,
Yoshifumi Saijo,
Gérard Finet,
JeanClaude Tardif,
Guy Cloutier
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0168332
Subject(s) - segmentation , coronary arteries , intravascular ultrasound , atheroma , lumen (anatomy) , computer science , medicine , artificial intelligence , gold standard (test) , cardiology , pattern recognition (psychology) , biomedical engineering , radiology , artery
The objectives were to compare the performance of a segmentation algorithm, based on the minimization of an uncertainty function, to delineate contours of external elastic membrane and lumen of human coronary arteries imaged with 40 and 60 MHz IVUS, and to use values of this function to delineate portions of contours with highest uncertainty. For 8 patients, 40 and 60 MHz IVUS coronary data acquired pre- and post-interventions were used, for a total of 68,516 images. Manual segmentations of contours (on 2312 images) performed by experts at three core laboratories were the gold-standards. Inter-expert variability was highest on contour points with largest values of the uncertainty function ( p < 0.001). Inter-expert variability was lower at 60 than 40 MHz for external elastic membrane ( p = 0.013) and lumen ( p = 0.024). Average differences in plaque (and atheroma) burden between algorithmic contours and experts’ contours were within inter-expert variability ( p < 0.001).