Song Junjie, Yu Xiangling, Song Wenlong, Guo Dajing, Li Chuanming, Liu Huan, Zhang Haiping, Zhou Jun, Liu Yangyang
Department of Radiology, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
GE Healthcare, Shanghai, China.
J Magn Reson Imaging. 2020 Dec;52(6):1668-1678. doi: 10.1002/jmri.27197. Epub 2020 May 23.
The noninvasive assessment of hepatic inflammatory activity (HIA) is crucial for making clinical decisions and monitoring therapeutic efficacy in chronic liver disease (CLD).
To develop MRI-based radiomics models by extracting features from the whole liver and localized regions of the right liver lobe, compare the efficiency of two radiomics models, and further develop a radiomics nomogram for the assessment of HIA in CLD.
Retrospective.
In all, 137 consecutive patients.
FIELD STRENGTH/SEQUENCE: 1.5T/T -weighted imaging.
All patients (nonsignificant HIA, n = 98; significant HIA, n = 39) were randomly divided into a training (n = 95) and a test cohort (n = 42). Radiomics features were extracted from the regions covering the whole liver (ROI-w) and localized regions of the right liver lobe (ROI-r). Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analyses were used to select features and develop radiomics models. A combined model fusing the valuable radiomics features with clinical-radiological predictors was developed. Finally, a radiomics nomogram derived from the combined model was developed.
Synthetic minority oversampling technique algorithm, LASSO, receiver operator characteristic curve, and calibration curve analysis were performed.
The area under the curve (AUC), sensitivity, and specificity of the ROI-w radiomics model in assessing HIA were 0.858, 0.800, and 0.733, respectively. The ROI-r model were 0.844, 0.733, and 0.867, respectively. No differences were detected between the two radiomics models (P = 0.8329). The combined model fusing valuable ROI-w radiomics features, albumin, and periportal edema exhibited a promising performance (AUC, 0.911). The calibration curves showed good agreement between the actual observations and nomogram predictions.
The MRI-based radiomics models had a powerful ability to evaluate HIA and the ROI-w radiomics model was comparable to the ROI-r model. Moreover, the radiomics nomogram could be a favorable method to individually estimate HIA in CLD. J. MAGN. RESON. IMAGING 2020;52:1668-1678.
肝炎症活动（HIA）的无创评估对于慢性肝病（CLD）的临床决策制定和治疗效果监测至关重要。
通过从全肝和右肝叶局部区域提取特征来开发基于MRI的放射组学模型，比较两种放射组学模型的效率，并进一步开发用于评估CLD中HIA的放射组学列线图。
回顾性研究。
共137例连续患者。
场强/序列：1.5T/T加权成像。
所有患者（轻度HIA，n = 98；重度HIA，n = 39）被随机分为训练组（n = 95）和测试组（n = 42）。从覆盖全肝的区域（ROI-w）和右肝叶局部区域（ROI-r）提取放射组学特征。使用最小绝对收缩和选择算子（LASSO）和多变量逻辑回归分析来选择特征并开发放射组学模型。开发了一个将有价值的放射组学特征与临床放射学预测指标相结合的联合模型。最后，从联合模型中得出放射组学列线图。
进行合成少数过采样技术算法、LASSO、受试者工作特征曲线和校准曲线分析。
ROI-w放射组学模型评估HIA的曲线下面积（AUC）、敏感性和特异性分别为0.858、0.800和0.733。ROI-r模型的分别为0.844、0.733和0.867。两种放射组学模型之间未检测到差异（P = 0.8329）。融合了有价值的ROI-w放射组学特征、白蛋白和门静脉周围水肿的联合模型表现出良好的性能（AUC，0.911）。校准曲线显示实际观察结果与列线图预测之间具有良好一致性。
基于MRI的放射组学模型具有强大的评估HIA的能力，ROI-w放射组学模型与ROI-r模型相当。此外，放射组学列线图可能是个体评估CLD中HIA的一种良好方法。《磁共振成像杂志》2020年；52：1668 - 1678。
