OBJECTIVE To evaluate the ability of volumetric quantitative apparent diffusion coefficient (ADC) histogram parameters and LI-RADS categorization to distinguish hepatocellular carcinoma (HCC) from other primary liver cancers [intrahepatic cholangiocarcinoma (ICC) and combined HCC-ICC]. METHODS Sixty-three consecutive patients (44 M/19F; mean age 62 years) with primary liver cancers and pre-treatment MRI including diffusion-weighted imaging (DWI) were included in this IRB-approved single-center retrospective study. Tumor type was categorized pathologically. Qualitative tumor features and LI-RADS categorization were assessed by 2 independent observers. Lesion volume of interest measurements (VOIs) were placed on ADC maps to extract first-order radiomics (histogram) features. ADC histogram metrics and qualitative findings were compared. Binary logistic regression and AUROC were used to assess performance for distinction of HCC from ICC and combined tumors. RESULTS Sixty-five lesions (HCC, n = 36; ICC, n = 17; and combined tumor, n = 12) were assessed. Only enhancement pattern (p < 0.015) and capsule were useful for tumor diagnosis (p < 0.014). ADC 5th/10th/95th percentiles were significant for discrimination between each tumor types (all p values < 0.05). Accuracy of LI-RADS for HCC diagnosis was 76.9% (p < 0.0001) and 69.2% (p = 0.001) for both observers. The combination of male gender, LI-RADS, and ADC 5th percentile yielded an AUROC/sensitivity/specificity/accuracy of 0.90/79.3%/88.9%/81.5% and 0.89/86.2%/77.8%/80.0% (all p values < 0.027) for the diagnosis of HCC compared to ICC and combined tumors for both observers, respectively. CONCLUSION The combination of quantitative ADC histogram parameters and LI-RADS categorization yielded the best prediction accuracy for distinction of HCC compared to ICC and combined HCC-ICC.

中文翻译：

---

体积定量直方图分析，使用扩散加权磁共振成像将HCC与其他原发性肝癌区分开来。

目的评估容积表观弥散系数（ADC）直方图参数和LI-RADS分类以区分肝细胞癌（HCC）与其他原发性肝癌[肝内胆管癌（ICC）和合并的HCC-ICC]的能力。方法该IRB批准的单中心回顾性研究纳入了63例连续原发性肝癌患者（44 M / 19F；平均年龄62岁），并进行了包括弥散加权成像（DWI）在内的治疗前MRI。肿瘤类型按病理分类。定性肿瘤特征和LI-RADS分类由2位独立观察员评估。病变体积感兴趣的测量值（VOI）被放置在ADC图上，以提取一阶放射学（直方图）特征。比较ADC直方图指标和定性结果。二元逻辑回归和AUROC用于评估区分ICC和合并肿瘤的HCC的性能。结果评估了65个病变（HCC，n = 36； ICC，n = 17；合并肿瘤，n = 12）。仅增强模式（p <0.015）和胶囊可用于肿瘤诊断（p <0.014）。ADC的第5/10/95％百分位数对于区分每种肿瘤类型均具有显着意义（所有p值<0.05）。两位观察者的LI-RADS诊断HCC的准确性分别为76.9％（p <0.0001）和69.2％（p = 0.001）。男性，LI-RADS和ADC的第5个百分点的组合得出的AUROC /敏感性/特异性/准确性为0.90 / 79.3％/ 88.9％/ 81.5％和0.89 / 86.2％/ 77.8％/ 80.0％（所有p值<与两位观察者相比，ICC和合并肿瘤的诊断率分别为0.027）。