AIMS: The aim of this paper is to report a method of atherosclerotic plaque tissue characterisation based on pattern recognition and assess its accuracy under conditions of potential clinical relevance. METHODS AND RESULTS: Excised saline infused human arteries were imaged using IVUS with RF acquisition. 40% of the vessels were re-imaged with human blood infusion. A database of approximately 12000 image regions-of-interest (ROIs) of histologically established types was used to design a pattern recognition algorithm to predict the tissue type of a given ROI by comparing its RF-spectrum against the database, and also to estimate the confidence of prediction. Ex vivo validation demonstrated accuracies at the highest level of confidence as: 97%, 98%, 95%, and 98% for necrotic, lipidic, fibrotic and calcified regions respectively. Good agreement with histology was shown in an in vivo swine animal model. CONCLUSIONS: Ex vivo validation demonstrated the ability to characterise plaque tissue using an IVUS+RF system and a method incorporating (1) full spectral information (2) spectral similarity (3) estimating confidence of characterisation and, (4) ability to characterise plaque imaged through blood. Promising results were demonstrated in a live animal model. This approach may have potential for accurate and reproducible plaque characterisation in vivo.
AIMS: The aim of this paper is to report a method of atherosclerotic plaque tissue characterisation based on pattern recognition and assess its accuracy under conditions of potential clinical relevance. METHODS AND RESULTS: Excised saline infused human arteries were imaged using IVUS with RF acquisition. 40% of the vessels were re-imaged with human blood infusion. A database of approximately 12000 image regions-of-interest (ROIs) of histologically established types was used to design a pattern recognition algorithm to predict the tissue type of a given ROI by comparing its RF-spectrum against the database, and also to estimate the confidence of prediction. Ex vivo validation demonstrated accuracies at the highest level of confidence as: 97%, 98%, 95%, and 98% for necrotic, lipidic, fibrotic and calcified regions respectively. Good agreement with histology was shown in an in vivo swine animal model. CONCLUSIONS: Ex vivo validation demonstrated the ability to characterise plaque tissue using an IVUS+RF system and a method incorporating (1) full spectral information (2) spectral similarity (3) estimating confidence of characterisation and, (4) ability to characterise plaque imaged through blood. Promising results were demonstrated in a live animal model. This approach may have potential for accurate and reproducible plaque characterisation in vivo.
Authors: Yang Sun; Abhijit J Chaudhari; Matthew Lam; Hongtao Xie; Diego R Yankelevich; Jennifer Phipps; Jing Liu; Michael C Fishbein; Jonathan M Cannata; K Kirk Shung; Laura Marcu Journal: Biomed Opt Express Date: 2011-07-19 Impact factor: 3.732
Authors: Julien Bec; Hongtao Xie; Diego R Yankelevich; Feifei Zhou; Yang Sun; Narugopal Ghata; Ralph Aldredge; Laura Marcu Journal: J Biomed Opt Date: 2012-10 Impact factor: 3.170