Ultrasound Radiomics Nomogram Integrating Three-Dimensional Features Based on Carotid Plaques to Evaluate Coronary Artery Disease.
Ultrasound Radiomics Nomogram Integrating Three-Dimensional Features Based on Carotid Plaques to Evaluate Coronary Artery Disease.
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基于颈动脉斑块整合三维特征的超声放射组学列线图评估冠状动脉疾病
DOI：
10.3390/diagnostics12020256
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发表时间：
2022-01-20
期刊：
影响因子：
--
通讯作者：
Ren J
中科院分区：
文献类型：
--
作者：
Wang X;Luo P;Du H;Li S;Wang Y;Guo X;Wan L;Zhao B;Ren J
本研究旨在探讨有创冠状动脉造影术(ICA)前超声放射组学分析用于评价冠状动脉病变(CAD)严重程度的可行性。本研究包括10 5例患者的10 5个颈动脉斑块(低SS患者，41例中高SS患者)。评估ICA前的临床特征和三维超声(3D-US)表现。颈动脉斑块的超声图像用于放射组学分析。最小绝对收缩和选择算子(LASSO)回归产生多个非零系数，用来选择能够预测中高SS的特征。根据这些系数，计算放射组学评分(Rad-Score)。选定的临床特征、3D-US特征和Rad-Score最终被整合到放射组学诺模图中。在临床特征和3D-US特征中，高密度脂蛋白(HDL)、载脂蛋白B(ApoB)和斑块体积被确定为区分低SS和中高SS的预测指标。在放射组学过程中，从851个候选放射组学特征中选出了8个最能识别中高SS的最佳放射组学特征。训练组和验证组之间的RAD得分差异显著(p=0.016和0.006)。结合高密度脂蛋白、载脂蛋白B、斑块体积和Rad-Score的放射组学诺模图在训练集(AUC，0.741(95%可信区间：0.646-0.835))和验证集(AUC，0.939(95%CI：0.860-1.000))中显示出优异的结果，具有良好的校准性(训练集和验证集的平均绝对误差分别为0.028和0.059)。决策曲线分析表明，放射组学诺模图可以识别出哪些患者可以获得最大的利益。结论：基于颈动脉斑块超声的放射组学诺模图对中高度SS的无创性预测具有良好的应用价值。该放射组学正常图对ICA前冠心病的风险分层具有潜在价值，并为临床医生提供了一种非侵入性诊断工具。
This study aimed to explore the feasibility of ultrasound radiomics analysis before invasive coronary angiography (ICA) for evaluating the severity of coronary artery disease (CAD) quantified by the SYNTAX score (SS). This study included 105 carotid plaques from 105 patients (64 low-SS patients, 41 intermediate-high-SS patients). The clinical characteristics and three-dimensional ultrasound (3D-US) features before ICA were assessed. Ultrasound images of carotid plaques were used for radiomics analysis. Least absolute shrinkage and selection operator (LASSO) regression, which generated several nonzero coefficients, was used to select features that could predict intermediate-high SS. Based on those coefficients, the radiomics score (Rad-score) was calculated. The selected clinical characteristics, 3D-US features, and Rad-score were finally integrated into a radiomics nomogram. Among the clinical characteristics and 3D-US features, high-density lipoprotein (HDL), apolipoprotein B (Apo B), and plaque volume were identified as predictors for distinguishing between low SS and intermediate-high SS. During the radiomics process, 8 optimal radiomics features most capable of identifying intermediate-high SS were selected from 851 candidate radiomics features. The differences in Rad-score between the training and the validation set were significant (p = 0.016 and 0.006). The radiomics nomogram integrating HDL, Apo B, plaque volume, and Rad-score showed excellent results in the training set (AUC, 0.741 (95% confidence interval (CI): 0.646–0.835)) and validation set (AUC, 0.939 (95% CI: 0.860–1.000)), with good calibration (mean absolute errors of 0.028 and 0.059 in training and validation sets, respectively). Decision curve analysis showed that the radiomics nomogram could identify patients who could obtain the most benefit. We concluded that the radiomics nomogram based on carotid plaque ultrasound has favorable value for the noninvasive prediction of intermediate-high SS. This radiomics nomogram has potential value for the risk stratification of CAD before ICA and provides clinicians with a noninvasive diagnostic tool.
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影响因子：
5.9
作者：
Zhang, Ranying;Zhang, Qingwei;Lin, Jiang
通讯作者：
Lin, Jiang
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影响因子：
24.5
作者：
Wang K;Lu X;Zhou H;Gao Y;Zheng J;Tong M;Wu C;Liu C;Huang L;Jiang T;Meng F;Lu Y;Ai H;Xie XY;Yin LP;Liang P;Tian J;Zheng R
通讯作者：
Zheng R
影响因子：
39.3
作者：
Ikeda, Nobutaka;Kogame, Norihiro;Sugi, Kaoru
通讯作者：
Sugi, Kaoru
影响因子：
14
作者：
Sillesen, Henrik;Muntendam, Pieter;Fuster, Valentin
通讯作者：
Fuster, Valentin
DOI：
10.1111/echo.14543
发表时间：
2019-11-19
影响因子：
1.5
作者：
Song, Shinjeong;Heo, Ran;Chang, Hyuk-Jae
通讯作者：
Chang, Hyuk-Jae