Influence of Different Segmentations on the Diagnostic Performance of Pericoronary Adipose Tissue.

Didi Wen,Shushen Lin,Yuyang Jia,Rui An,Wangwei Yang,Minwen Zheng

doi:10.3389/fcvm.2022.773524

Abstract

ObjectiveTo investigate the influence of different segmentations on the diagnostic performance of pericoronary adipose tissue (PCAT) CT attenuation and radiomics features for the prediction of ischemic coronary artery stenosis.MethodsFrom June 2016 to December 2018, 108 patients with 135 vessels were retrospectively analyzed in the present study. Vessel-based PCAT was segmented along the 40 mm-long proximal segments of three major epicardial coronary arteries, while lesion-based PCAT was defined around coronary lesions. CT attenuation and radiomics features derived from two segmentations were calculated and extracted. The diagnostic performance of PCAT CT attenuation or radiomics models in predicting ischemic coronary stenosis were also compared between vessel-based and lesion-based segmentations.ResultsThe mean PCAT CT attenuation was −75.7 ± 9.1 HU and −76.1 ± 8.1 HU (p = 0.395) for lesion-based and vessel-based segmentations, respectively. A strong correlation was found between vessel-based and lesion-based PCAT CT attenuation for all cohort and subgroup analyses (all p < 0.01). A good agreement for all cohort and subgroup analyses was also detected between two segmentations. The diagnostic performance was comparable between vessel-based and lesion based PCAT CT attenuation in predicting ischemic stenosis. The radiomics features of PCAT based on vessel or lesion segmentation can both adequately identify the ischemic stenosis. However, no significant difference was detected between the two segmentations.ConclusionsThe quantitative evaluation of PCAT can be reliably measured both from vessel-based and lesion-based segmentation. Furthermore, the radiomics analysis of PCAT may potentially help predict hemodynamically significant coronary artery stenosis.

Highlights

Vascular inflammation is a driver of coronary atherosclerotic plaque formation and a typical feature of atherosclerotic plaque rupture [1]
103 (76.3%) lesions with stenosis ≥50% were detected, and 63 (46.7%) lesions were considered ischemic stenosis according to fractional flow reserve (FFR) (FFR ≤ 0.80) (Table 2)
According to receiver operating characteristic (ROC) curve analysis, the area under the curves (AUCs) of pericoronary adipose tissue (PCAT) CT attenuation in vessel-based segmentation was 0.524, which had similar diagnostic performance compared to lesion-based PCAT CT attenuation (0.547, 95% CI: 0.459–0.633, p = 0.814) (Figure 4)

Summary

Introduction

Vascular inflammation is a driver of coronary atherosclerotic plaque formation and a typical feature of atherosclerotic plaque rupture [1]. Recent research demonstrated that signals released from the inflamed coronary artery diffuse to the perivascular adipose tissue, inhibiting local adipogenesis Such an inflammatory response changes the composition of perivascular adipose tissue around inflamed arteries, shifting its attenuation on CCTA from the lipid [more negative Hounsfield unit (HU) values (e.g., closer to −190 HU)] to the aqueous phase [less negative HU values (e.g., closer to −30 HU)]. The changes in pericoronary adipose tissue (PCAT) attenuation can be non-invasively measured using routine CCTA, and enable early detection of vascular inflammation in coronary arteries. Some studies suggested that a lesion-specific assessment of PCAT might provide greater insight into atherosclerotic biology than the proximal segments of the major arteries alone [6, 17]. Our secondary objective was to compare the diagnostic performance of PCAT CT attenuation and radiomics features between two segmentations for the prediction of hemodynamically significant coronary artery stenosis

Methods

Results

Discussion

Conclusion