Sack Jordan, Nitsch Jennifer, Meine Hans, Kikinis Ron, Halle Michael, Rutherford Anna
Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Boston, MA 02115, USA.
Harvard Medical School, Boston, MA 02115, USA.
J Imaging. 2022 Oct 9;8(10):277. doi: 10.3390/jimaging8100277.
Radiomics extracts quantitative image features to identify biomarkers for characterizing disease. Our aim was to characterize the ability of radiomic features extracted from magnetic resonance (MR) imaging of the liver and spleen to detect cirrhosis by comparing features from patients with cirrhosis to those without cirrhosis.
This retrospective study compared MR-derived radiomic features between patients with cirrhosis undergoing hepatocellular carcinoma screening and patients without cirrhosis undergoing intraductal papillary mucinous neoplasm surveillance between 2015 and 2018 using the same imaging protocol. Secondary analyses stratified the cirrhosis cohort by liver disease severity using clinical compensation/decompensation and Model for End-Stage Liver Disease (MELD).
Of 167 patients, 90 had cirrhosis with 68.9% compensated and median MELD 8. Combined liver and spleen radiomic features generated an AUC 0.94 for detecting cirrhosis, with shape and texture components contributing more than size. Discrimination of cirrhosis remained high after stratification by liver disease severity.
MR-based liver and spleen radiomic features had high accuracy in identifying cirrhosis, after stratification by clinical compensation/decompensation and MELD. Shape and texture features performed better than size features. These findings will inform radiomic-based applications for cirrhosis diagnosis and severity.
放射组学提取定量图像特征以识别用于疾病特征描述的生物标志物。我们的目的是通过比较肝硬化患者与非肝硬化患者的特征，来描述从肝脏和脾脏的磁共振（MR）成像中提取的放射组学特征检测肝硬化的能力。
这项回顾性研究使用相同的成像方案，比较了2015年至2018年间接受肝细胞癌筛查的肝硬化患者与接受导管内乳头状黏液性肿瘤监测的非肝硬化患者的MR衍生放射组学特征。二次分析使用临床代偿/失代偿和终末期肝病模型（MELD）按肝病严重程度对肝硬化队列进行分层。
在167例患者中，90例患有肝硬化，其中68.9%为代偿期，MELD中位数为8。肝脏和脾脏的联合放射组学特征检测肝硬化的AUC为0.94，形状和纹理成分的贡献大于大小成分。按肝病严重程度分层后，对肝硬化的鉴别能力仍然很高。
基于MR的肝脏和脾脏放射组学特征在通过临床代偿/失代偿和MELD分层后，对肝硬化的识别具有很高的准确性。形状和纹理特征的表现优于大小特征。这些发现将为基于放射组学的肝硬化诊断和严重程度评估应用提供依据。
