使用来自双能 CT (DECT) 的定量数据（不含造影剂）创建预测模型 (PM)，以区分良性和恶性肝脏病变。这项回顾性研究包括接受 DECT（包括非对比增强扫描）的肝脏病变患者。良性病变包括肝血管瘤，恶性病变包括肝细胞癌、转移性肝癌和肝内胆管细胞癌。患者被分为推导组和验证组。在推导组中，两名放射科医生使用单变量和多元逻辑回归计算了 10 个多参数数据以生成 PM。在验证组中，另外两名放射科医生测量了参数以评估 PM 的诊断性能。该研究包括 121 名连续患者（平均年龄 67.4±13.8 岁，80 名男性），其中 97 名属于衍生组（25 名良性，72 名恶性）验证组 24 例（7 例良性，17 例恶性）。过采样将良性病变样本增加到 75 个，平衡了构建 PM 的恶性组。所有参数在单变量分析中均具有统计显着性（所有 p< 0.05），导致在多变量分析中创建了 5 个 PM。两名观察者的 5 个 PM 的曲线下面积如下： PM1（斜率 K，血液） = 0.76、0.74； PM2（斜率K，脂肪） = 0.55，0.51； PM3（有效-Z差值，血液） = 0.75，0.72； PM4（斜率K、血液、脂肪） = 0.82、0.78； PM5（斜率 K、有效 Z 差、血液） = 0.90、0.87。 PM5 的诊断性能最好。多参数非增强 DECT 是区分肝脏病变的高效方法。非增强 DECT 对于区分良恶性肝脏病变非常有用。这种方法使医生能够规划更好的治疗策略，减轻与对比剂过敏、对比剂诱发肾病、辐射暴露和过度医疗费用相关的担忧。通过非对比增强 CT 区分良性和恶性肝脏病变将是可取的。该模型结合了斜率 K、有效 Z 和血液定量，区分良性和恶性肝脏病变。非对比增强 DECT 有好处，特别是对于碘过敏、肾衰竭或哮喘患者。© 2024。作者。

To create prediction models (PMs) for distinguishing between benign and malignant liver lesions using quantitative data from dual-energy CT (DECT) without contrast agents.This retrospective study included patients with liver lesions who underwent DECT, including non-contrast-enhanced scans. Benign lesions included hepatic hemangioma, whereas malignant lesions included hepatocellular carcinoma, metastatic liver cancer, and intrahepatic cholangiocellular carcinoma. Patients were divided into derivation and validation groups. In the derivation group, two radiologists calculated ten multiparametric data using univariate and multivariate logistic regression to generate PMs. In the validation group, two additional radiologists measured the parameters to assess the diagnostic performance of PMs.The study included 121 consecutive patients (mean age 67.4 ± 13.8 years, 80 males), with 97 in the derivation group (25 benign and 72 malignant) and 24 in the validation group (7 benign and 17 malignant). Oversampling increased the benign lesion sample to 75, equalizing the malignant group for building PMs. All parameters were statistically significant in univariate analysis (all p < 0.05), leading to the creation of five PMs in multivariate analysis. The area under the curve for the five PMs of two observers was as follows: PM1 (slope K, blood) = 0.76, 0.74; PM2 (slope K, fat) = 0.55, 0.51; PM3 (effective-Z difference, blood) = 0.75, 0.72; PM4 (slope K, blood, fat) = 0.82, 0.78; and PM5 (slope K, effective-Z difference, blood) = 0.90, 0.87. PM5 yielded the best diagnostic performance.Multiparametric non-contrast-enhanced DECT is a highly effective method for distinguishing between liver lesions.The utilization of non-contrast-enhanced DECT is extremely useful for distinguishing between benign and malignant liver lesions. This approach enables physicians to plan better treatment strategies, alleviating concerns associated with contrast allergy, contrast-induced nephropathy, radiation exposure, and excessive medical expenses.Distinguishing benign from malignant liver lesions with non-contrast-enhanced CT would be desirable. This model, incorporating slope K, effective Z, and blood quantification, distinguished benign from malignant liver lesions. Non-contrast-enhanced DECT has benefits, particularly in patients with an iodine allergy, renal failure, or asthma.© 2024. The Author(s).