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Automated diagnosis of optical coherence tomography imaging on plaque vulnerability and its relation to clinical outcomes in coronary artery disease.

ABSTRACT: This study sought to develop a deep learning-based diagnostic algorithm for plaque vulnerability by analyzing intravascular optical coherence tomography (OCT) images and to investigate the relation between AI-plaque vulnerability and clinical outcomes in patients with coronary artery disease (CAD). A total of 1791 study patients who underwent OCT examinations were recruited from a multicenter clinical database, and the OCT images were first labeled as either normal, a stable plaque, or a vulnerable plaque by expert cardiologists. A DenseNet-121-based deep learning algorithm for plaque characterization was developed by training with 44,947 prelabeled OCT images, and demonstrated excellent differentiation among normal, stable plaques, and vulnerable plaques. Patients who were diagnosed with vulnerable plaques by the algorithm had a significantly higher rate of both events from the OCT-observed segments and clinical events than the patients with normal and stable plaque (log-rank p < 0.001). On the multivariate logistic regression analyses, the OCT diagnosis of a vulnerable plaque by the algorithm was independently associated with both types of events (p = 0.047 and p < 0.001, respectively). The AI analysis of intracoronary OCT imaging can assist cardiologists in diagnosing plaque vulnerability and identifying CAD patients with a high probability of occurrence of future clinical events.

SUBMITTER: Niioka H

PROVIDER: S-EPMC9388661 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Automated diagnosis of optical coherence tomography imaging on plaque vulnerability and its relation to clinical outcomes in coronary artery disease.

Niioka Hirohiko H Kume Teruyoshi T Kubo Takashi T Soeda Tsunenari T Watanabe Makoto M Yamada Ryotaro R Sakata Yasushi Y Miyamoto Yoshihiro Y Wang Bowen B Nagahara Hajime H Miyake Jun J Akasaka Takashi T Saito Yoshihiko Y Uemura Shiro S

Scientific reports 20220818 1

This study sought to develop a deep learning-based diagnostic algorithm for plaque vulnerability by analyzing intravascular optical coherence tomography (OCT) images and to investigate the relation between AI-plaque vulnerability and clinical outcomes in patients with coronary artery disease (CAD). A total of 1791 study patients who underwent OCT examinations were recruited from a multicenter clinical database, and the OCT images were first labeled as either normal, a stable plaque, or a vulnera ...[more]

PMID: 35982217

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Project description:Optical coherence tomography (OCT) is slowly but surely gaining a foothold in the hands of interventional cardiologists. Intraluminal and transmural contents of the coronary arteries are no longer elusive to the cardiologist's probing eye. Although the graduation of an interventionalist in imaging techniques right from naked eye angiographies to ultrasound-based coronary sonographies to the modern light-based OCT has been slow, with the increasing regularity of complex coronary cases in practice, such a transition is inevitable. Although intravascular ultrasound (IVUS) due to its robust clinical data has been the preferred imaging modality in recent years, OCT provides a distinct upgrade over it in many imaging and procedural aspects. Better image resolution, accurate estimation of the calcified lesion, and better evaluation of acute and chronic stent failure are the distinct advantages of OCT over IVUS. Despite the obvious imaging advantages of OCT, its clinical impact remains subdued. However, upcoming newer trials and data have been encouraging for expanding the use of OCT to wider indications in clinical utility. During percutaneous coronary intervention (PCI), OCT provides the detailed information (dissection, tissue prolapse, thrombi, and incomplete stent apposition) required for optimal stent deployment, which is the key to successfully reducing the major adverse cardiovascular event (MACE) and stent-related morbidities. The increasing use of OCT in complex bifurcation stenting involving the left main (LM) is being studied. Also, the traditional pitfalls of OCT, such as additional contrast load for image acquisition and stenting involving the ostial and proximal LM, have also been overcome recently. In this review, we discuss the interpretation of OCT images and its clinical impact on the outcome of procedures along with current barriers to its use and newer paradigms in which OCT is starting to become a promising tool for the interventionalist and what can be expected for the immediate future in the imaging world.

Dataset Information

Automated diagnosis of optical coherence tomography imaging on plaque vulnerability and its relation to clinical outcomes in coronary artery disease.

Publications

Automated diagnosis of optical coherence tomography imaging on plaque vulnerability and its relation to clinical outcomes in coronary artery disease.

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