Logo image
Back
Spectral segmentation and radiomic features predict carotid stenosis and ipsilateral ischemic burden from DECT angiography
Journal article   Open access   Peer reviewed

Spectral segmentation and radiomic features predict carotid stenosis and ipsilateral ischemic burden from DECT angiography

Shadi Ebrahimian, Fatemeh Homayounieh, Ramandeep Singh, Andrew Primak, Mannudeep K. Kalra and Javier M. Romero
Diagnostic and interventional radiology (Ankara, Turkey), Vol.28(3), pp.264-274
05/01/2022
DOI: 10.5152/dir.2022.20842
PMCID: PMC9634936
PMID: 35748211
url
https://doi.org/10.5152/dir.2022.20842View
Published (Version of record) Open Access

Abstract

PURPOSE The purpose of this study is to compare spectral segmentation, spectral radiomic, and single-energy radiomic features in the assessment of internal and common carotid artery (ICA/CCA) stenosis and prediction of surgical outcome. METHODS Our ethical committee-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant study included 85 patients (mean age, 73 +/- 10 years; male : female, 56 : 29) who underwent contrast- enhanced, dual-source dual-energy CT angiography (DECTA) (Siemens Definition Flash) of the neck for assessing ICA/CCA stenosis. Patients with a prior surgical or interventional treatment of carotid stenosis were excluded. Two radiologists graded the severity of carotid stenosis on DECTA images as mild (<50% luminal narrowing), moderate (50%-69%), and severe (>70%) stenosis. Thin-section, low- and high-kV DICOM images from the arterial phase acquisition were processed with a dual-energy CT prototype (DTA, eXamine, Siemens Healthineers) to generate spectral segmentation and radiomic features over regions of interest along the entire length (volume) and separately at a single-section with maximum stenosis. Multiple logistic regressions and area under the receiver operating characteristic curve (AUC) were used for data analysis. RESULTS Among 85 patients, 22 ICA/CCAs had normal luminal dimensions and 148 ICA/CCAs had luminal stenosis (mild stenosis: 51, moderate: 38, severe: 59). For differentiating non-severe and severe ICA/CCA stenosis, radiomic features (volume: AUC = 0.94, 95% CI 0.88-0.96; section: AUC = 0.92, 95% CI 0.86-0.93) were significantly better than spectral segmentation features (volume: AUC = 0.86, 95% CI 0.74-0.87; section: AUC = 0.68, 95% CI 0.66-0.78) (P <.001). Spectral radiomic features predicted revascularization procedure (AUC = 0.77) and the presence of ipsilateral intracranial ischemic changes (AUC = 0.76). CONCLUSION Spectral segmentation and radiomic features from DECTA can differentiate patients with different luminal ICA/CCA stenosis grades.
 Life Sciences & Biomedicine Radiology, Nuclear Medicine & Medical Imaging Science & Technology

Details

Metrics

3 Record Views
7 Times Cited - Web of Science
Logo image