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Influence of Different Segmentations on the Diagnostic Performance of Pericoronary Adipose Tissue
Didi Wen1, Rui An1, Shushen Lin2
1Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Insights
Both vessel-based and lesion-based segmentation reliably quantify pericoronary adipose tissue (PCAT) CT attenuation and radiomics for predicting coronary artery stenosis. The methods show comparable diagnostic performance for identifying ischemic stenosis.
Area of Science:
- Cardiovascular Imaging
- Radiology
- Biomedical Engineering
Background:
- Pericoronary adipose tissue (PCAT) CT attenuation and radiomics are emerging biomarkers for predicting ischemic coronary artery stenosis.
- Different segmentation methods for PCAT may influence diagnostic performance.
Purpose of the Study:
- To investigate the impact of vessel-based versus lesion-based PCAT segmentation on diagnostic performance for predicting ischemic coronary artery stenosis.
- To compare CT attenuation and radiomics features derived from these two segmentation approaches.
Main Methods:
- Retrospective analysis of 108 patients (135 vessels) with coronary artery disease.
- Segmentation of PCAT using vessel-based (40 mm proximal segment) and lesion-based approaches.
- Extraction and comparison of CT attenuation and radiomics features between the two segmentation methods.
Main Results:
- No significant difference in mean PCAT CT attenuation between lesion-based and vessel-based segmentations.
- Strong correlation and good agreement in PCAT CT attenuation between the two segmentation methods.
- Comparable diagnostic performance of both segmentation approaches for predicting ischemic stenosis using CT attenuation and radiomics features.
Conclusions:
- Quantitative evaluation of PCAT is reliable using either vessel-based or lesion-based segmentation.
- Radiomics analysis of PCAT shows potential for predicting hemodynamically significant coronary artery stenosis, irrespective of segmentation method.
Objective:
To 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.
Methods:
From 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.
Results:
The 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.
Conclusions:
The 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.
