CT radiomic features reproducibility of virtual non-contrast series derived from photon-counting CCTA datasets using a novel calcium-preserving reconstruction algorithm compared with standard non-contrast series: focusing on epicardial adipose tissue

• Published in: The international journal of cardiovascular imaging 2024-06, Vol.40 (6), p.1257-1267
• Main Authors: Cui, MengXu, Bao, ShouYu, Li, JiQiang, Dong, HaiPeng, Xu, ZhiHan, Yan, Fuhua, Yang, Wenjie
• Format: Article
• Language: English
• Subjects: Adipose tissue; Algorithms; Angiography; Body fat; Cardiac Imaging; Cardiology; Computed tomography; Correlation coefficient; Correlation coefficients; Datasets; Filters; Image filters; Image reconstruction; Imaging; Medical imaging; Medicine; Medicine & Public Health; Original Paper; Photons; Radiology; Radiomics; Reproducibility; Tomography
• ISSN: 1875-8312; 1569-5794; 1875-8312; 1573-0743
• DOI: 10.1007/s10554-024-03096-w

Purpose We aimed to evaluate the reproducibility of computed tomography (CT) radiomic features (RFs) about Epicardial Adipose Tissue (EAT). The features derived from coronary photon-counting computed tomography (PCCT) angiography datasets using the PureCalcium (VNC PC ) and conventional virtual non-contrast (VNC Conv ) algorithm were compared with true non-contrast (TNC) series. Methods RFs of EAT from 52 patients who underwent PCCT were quantified using VNC PC , VNC Conv , and TNC series. The agreement of EAT volume (EATV) and EAT density (EATD) was evaluated using Pearson’s correlation coefficient and Bland-Altman analysis. A total of 1530 RFs were included. They are divided into 17 feature categories, each containing 90 RFs. The intraclass correlation coefficients (ICCs) and concordance correlation coefficients (CCCs) were calculated to assess the reproducibility of RFs. The cutoff value considered indicative of reproducible features was > 0.75. Results the VNC PC and VNC Conv tended to underestimate EATVs and overestimate EATDs. Both EATV and EATD of VNC PC series showed higher correlation and agreement with TNC than VNC Conv series. All types of RFs from VNC PC series showed greater reproducibility than VNC Conv series. Across all image filters, the Square filter exhibited the highest level of reproducibility (ICC = 67/90, 74.4%; CCC = 67/90, 74.4%). GLDM_GrayLevelNonUniformity feature had the highest reproducibility in the original image (ICC = 0.957, CCC = 0.958), exhibiting a high degree of reproducibility across all image filters. Conclusion The accuracy evaluation of EATV and EATD and the reproducibility of RFs from VNC PC series make it an excellent substitute for TNC series exceeding VNC Conv series.