Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid–structure interaction models and machine learning methods with patient follow-up data: a feasibility study

Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid–structure interaction models and machine learning methods with patient follow-up data: a feasibility study

Abstract Background Coronary plaque vulnerability prediction is difficult because plaque vulnerability is non-trivial to quantify, clinically available medical image modality is not enough to quantify thin cap thickness, prediction methods with high accuracies still need to be developed, and gold-st...

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Bibliographic Details
Main Authors: Xiaoya Guo, Akiko Maehara, Mitsuaki Matsumura, Liang Wang, Jie Zheng, Habib Samady, Gary S. Mintz, Don P. Giddens, Dalin Tang
Format: Article
Language:English
Published: BMC 2021-04-01
Series:BioMedical Engineering OnLine
Subjects:
Vulnerable plaque
OCT
IVUS
Morphological index
Patient-specific model
FSI
Online Access:https://doi.org/10.1186/s12938-021-00868-6

Internet

https://doi.org/10.1186/s12938-021-00868-6

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