Key result
PCAT texture analysis identifies coronary artery plaques with an AUC of 0.78.
Why the study?
Peri-coronary adipose tissue is an indicator of coronary inflammation, but its characteristics around the right coronary artery with or without plaque needed evaluation using CCTA texture analysis.
Does PCAT texture analysis by CCTA differentiate between the presence or absence of RCA plaques in patients with coronary artery disease?
Case-Control (n=67)
No
Does PCAT texture analysis by CCTA differentiate between the presence or absence of RCA plaques in patients with coronary artery disease?
Effect estimate: AUC 0.78
PCAT texture analysis using CCTA can identify the presence of coronary artery plaques, offering a potential new non-invasive diagnostic method for coronary artery disease.
May aid noninvasive coronary inflammation detection on CCTA; leaves open incremental prognostic value beyond plaque assessment.
Peri-Coronary Adipose Tissue (PCAT) was an indicator to detect the coronary inflammation. We aimed to analyze the PCAT characteristics of Right Coronary Artery (RCA) with or without plaque using texture analysis by Coronary Computed Tomography Angiography (CCTA). This article was a retrospective case-control study. In total, 67 patients with coronary artery disease were enrolled from December 2018 to September 2019. The patients were divided into two groups according to whether there are plaques existing at the RCA vessels. The radiomic features of RCA vessels calculated on the PCAT regions between groups were compared using Mann-Whitney U test. Receiver Operating Characteristic Curve (ROC) analysis was performed to evaluate the performance of each significant features to differentiate the group with or without plaques. 43 patients without RCA plaque and 24 patients with RCA plaque were included in the study. 1218 radiomic features were finally calculated, among which wavelet-based texture features were more significantly different between RCA plaque group and RCA non-plaque group. Furthermore, wavelet_LLL_ firstorder_Maximum had the highest Area Under Curve (AUC) 0.78. Therefore, PCAT texture analysis is expected to be used as a new detection method to determine the existence of coronary artery disease.
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Rl et al. (2021) conducted a case-control in Coronary artery disease (n=67). Pericoronary Adipose Tissue (PCAT) texture analysis vs. Patients without right coronary artery plaques was evaluated on Differentiation of right coronary artery with or without plaques using radiomic features (AUC 0.78). Pericoronary adipose tissue texture analysis identified the presence of coronary artery plaques, with the wavelet_LLL_firstorder_Maximum feature achieving an area under the curve of 0.78.
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