Effect of High-Intensity Statin Therapy on Atherosclerosis (IBIS-4): Manual Versus Automated Methods of IVUS Analysis.
Coronary artery disease
Intravascular ultrasound
Lumen segmentation
Machine learning
Vessel segmentation
Journal
Cardiovascular revascularization medicine : including molecular interventions
ISSN: 1878-0938
Titre abrégé: Cardiovasc Revasc Med
Pays: United States
ID NLM: 101238551
Informations de publication
Date de publication:
09 2023
09 2023
Historique:
received:
13
02
2023
revised:
27
03
2023
accepted:
10
04
2023
medline:
23
10
2023
pubmed:
23
4
2023
entrez:
22
04
2023
Statut:
ppublish
Résumé
Standard manual analysis of IVUS to study the impact of anti-atherosclerotic therapies on the coronary vessel wall is done by a core laboratory (CL), the ground truth (GT). Automatic segmentation of IVUS with a machine learning (ML) algorithm has the potential to replace manual readings with an unbiased and reproducible method. The aim is to determine if results from a CL can be replicated with ML methods. This is a post-hoc, comparative analysis of the IBIS-4 (Integrated Biomarkers and Imaging Study-4) study (NCT00962416). The GT baseline and 13-month follow-up measurements of lumen and vessel area and percent atheroma volume (PAV) after statin induction were repeated by the ML algorithm. The primary endpoint was change in PAV. PAV as measured by GT was 43.95 % at baseline and 43.02 % at follow-up with a change of -0.90 % (p = 0.007) while the ML algorithm measured 43.69 % and 42.41 % for baseline and follow-up, respectively, with a change of -1.28 % (p < 0.001). Along the most diseased 10 mm segments, GT-PAV was 52.31 % at baseline and 49.42 % at follow-up, with a change of -2.94 % (p < 0.001). The same segments measured by the ML algorithm resulted in PAV of 51.55 % at baseline and 47.81 % at follow-up with a change of -3.74 % (p < 0.001). PAV, the most used endpoint in clinical trials, analyzed by the CL is closely replicated by the ML algorithm. ML automatic segmentation of lumen, vessel and plaque effectively reproduces GT and may be used in future clinical trials as the standard.
Identifiants
pubmed: 37087308
pii: S1553-8389(23)00148-3
doi: 10.1016/j.carrev.2023.04.007
pii:
doi:
Substances chimiques
Hydroxymethylglutaryl-CoA Reductase Inhibitors
0
Banques de données
ClinicalTrials.gov
['NCT00962416']
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
33-38Commentaires et corrections
Type : CommentIn
Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest Héctor M. García-García reports the following Institutional grant support: Biotronik, Boston Scientific, Medtronic, Abbott, Neovasc, Shockwave, Phillips and Corflow; Speaker's fee from Boston Scientific and Amgen. Lorenz Räber reports institutional grant support: Abbott, Biotronik, Boston Scientific, Sanofi, Regeneron, Infraredx and consultation fees by Abbott, Amgen, AstraZeneca, Occlutec, Medtronic, Sanofi, Vifor. Marco Roffi reports institutional research grants from Terumo, Biotronik, Medtronic and Cordis/Cardinal Health.