Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT

被引:2
作者
Oh, Hee Sang [1 ,2 ]
Kim, Tae Hoon [1 ,2 ]
Kim, Ji Won [1 ,2 ]
Yang, Juyeon [3 ]
Lee, Hye Sun [3 ]
Lee, Jae-Hoon [4 ]
Park, Chul Hwan [1 ,2 ]
机构
[1] Yonsei Univ, Gangnam Severance Hosp, Dept Radiol, Coll Med, 211 Eonjuro, Seoul 06273, South Korea
[2] Yonsei Univ, Gangnam Severance Hosp, Res Inst Radiol Sci, Coll Med, 211 Eonjuro, Seoul 06273, South Korea
[3] Yonsei Univ, Biostat Collaborat Unit, Coll Med, Seoul, South Korea
[4] Yonsei Univ, Gangnam Severance Hosp, Dept Nucl Med, Coll Med, 211 Eonjuro, Seoul 06273, South Korea
关键词
Deep learning; Coronary artery disease; Vascular calcification; Positron emission tomography-computed tomography; Multidetector computed tomography; RISK;
D O I
10.1007/s00330-023-10390-z
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objective This study aimed to determine the feasibility and limitations of deep learning-based coronary calcium scoring using positron emission tomography-computed tomography (PET-CT) in comparison with coronary calcium scoring using ECG-gated non-contrast-enhanced cardiac computed tomography (CaCT).Materials and methods A total of 215 individuals who underwent both CaCT and PET-CT were enrolled in this retrospective study. The Agatston method was used to calculate the coronary artery calcium scores (CACS) from CaCT, PET-CT(reader), and PET-CT(AI) to analyse the effect of using different modalities and AI-based software on CACS measurement. The total CACS and CACS classified according to the CAC-DRS guidelines were compared between the three sets of CACS. The differences, correlation coefficients, intraclass coefficients (ICC), and concordance rates were analysed. Statistical significance was set at p < 0.05.Results The correlation coefficient of the total CACS from CaCT and PET-CT(reader) was 0.837, PET-CT(reader) and PET-CT(AI) was 0.894, and CaCT and PET-CT(AI) was 0.768. The ICC of CACS from CaCT and PET-CT(reader) was 0.911, PET-CT(reader) and PET-CT(AI) was 0.958, and CaCT and PET-CT(AI) was 0.842. The concordance rate between CaCT and PET-CT(AI) was 73.8%, with a false-negative rate of 37.3% and a false-positive rate of 4.4%. Age and male sex were associated with an increased misclassification rate.Conclusions Artificial intelligence-assisted CACS measurements in PET-CT showed comparable results to CACS in coronary calcium CT. However, the relatively high false-negative results and tendency to underestimate should be of concern.Clinical relevance statement Application of automated calcium scoring to PET-CT studies could potentially select patients at high risk of coronary artery disease from among cancer patients known to be susceptible to coronary artery disease and undergoing routine PET-CT scans.
引用
收藏
页码:4077 / 4088
页数:12
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