Xu Yuan, Li Fukai, Liu Bo, Ren Tiezhu, Sun Jiachen, Li Yufeng, Liu Hong, Liu Jianli, Zhou Junlin
Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China.
Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China.
BMC Med Imaging. 2025 Mar 3;25(1):69. doi: 10.1186/s12880-025-01600-9.
Acute-on-chronic liver failure (ACLF) is a life-threatening hepatic syndrome. Therefore, this study aimed to develop a comprehensive model combining extracellular liver volume derived from spectral CT (ECV) and sarcopenia, for the early prediction of short-term (90-day) disease progression in ACLF.
A retrospective cohort of 126 ACLF patients who underwent hepatic spectral CT scans was included. According to the Asia-Pacific Association for the Study of the Liver (APASL) criteria, patients were divided into the progression group (n = 70) and the stable group (n = 56). ECV was measured on the equilibrium period (EP) images of spectral CT, and L3-SMI was measured on unenhanced CT images, with sarcopenia assessed. A comprehensive model was developed by combining independent predictors. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA).
In the univariate analysis, BMI, WBC, PLT, PTA, L3-SMI, IC-EP, Z-EP, K-EP, NIC-EP, ECV, and Sarcopenia demonstrated associations with disease progression status at 90 days in ACLF patients. In multivariate logistic regression, white blood cell count (WBC) (OR = 1.19, 95% CI: 1.02-1.40; P = 0.026), ECV (OR = 1.27, 95% CI: 1.15-1.40; P < 0.001), sarcopenia (OR = 4.15, 95% CI: 1.43-12.01; P = 0.009), MELD-Na score (OR = 1.06, 95%CI: 1.01-1.13;P = 0.042), and CLIF-SOFA score (OR = 1.37, 95%CI:1.15-1.64; P<0.001) emerged as independent risk factors for ACLF progression. The combined model exhibited superior predictive performance (AUCs = 0.910, sensitivity = 80.4%, specificity = 90.0%, PPV = 0.865, NPV = 0.851) compared to CLIF-SOFA, MELD-Na, MELD and CTP scores(both P < 0.001). Calibration curves and DCA confirmed the high clinical utility of the combined model.
Patients without sarcopenia and/or with a lower ECV have a better prognosis, and the integration of WBC, ECV, Sarcopenia, CLIF-SOFA and MELD-Na scores in a composite model offers a concise and effective tool for predicting disease progression in ACLF patients.
Not Applicable.
慢加急性肝衰竭（ACLF）是一种危及生命的肝脏综合征。因此，本研究旨在建立一种综合模型，将基于光谱CT的细胞外肝体积（ECV）与肌肉减少症相结合，用于早期预测ACLF患者短期（90天）疾病进展。
纳入126例行肝脏光谱CT扫描的ACLF患者的回顾性队列。根据亚太肝脏研究协会（APASL）标准，将患者分为进展组（n = 70）和稳定组（n = 56）。在光谱CT的平衡期（EP）图像上测量ECV，在平扫CT图像上测量L3肌少肌指数（L3-SMI），并评估肌肉减少症。通过合并独立预测因子建立综合模型。使用受试者工作特征（ROC）曲线分析、校准曲线和决策曲线分析（DCA）评估模型性能。
单因素分析中，BMI、白细胞（WBC）、血小板（PLT）、凝血酶原活动度（PTA）L3-SMI、IC-EP、Z-EP、K-EP、NIC-EP、ECV和肌肉减少症与ACLF患者90天疾病进展状态相关。多因素逻辑回归分析显示，白细胞计数（WBC）（比值比[OR]=1.19，95%置信区间[CI]：1.02-1.40；P=0.026）、ECV（OR=1.27，95%CI：1.15-1.40；P<0.001）、肌肉减少症（OR=4.15，95%CI：1.43-12.01；P=0.009）、终末期肝病模型钠（MELD-Na）评分（OR=1.06，95%CI：1.01-1.13；P=0.042）和慢性肝衰竭序贯器官衰竭评估（CLIF-SOFA）评分（OR=1.37，95%CI：1.15-1.64；P<0.001）是ACLF进展的独立危险因素。与CLIF-SOFA、MELD-Na、MELD和CTP评分相比，联合模型表现出更好的预测性能（曲线下面积[AUCs]=0.910，敏感性=80.4%，特异性=90.0%，阳性预测值[PPV]=0.865，阴性预测值[NPV]=0.851）（均P<0.001）。校准曲线和DCA证实了联合模型的高临床实用性。
无肌肉减少症和/或ECV较低的患者预后较好，将WBC、ECV、肌肉减少症、CLIF-SOFA和MELD-Na评分整合到一个综合模型中，为预测ACLF患者疾病进展提供了一个简洁有效的工具。
不适用。
