Elkassem Asser Abou, Allen Brian C, Lirette Seth T, Cox Kelly L, Remer Erick M, Pickhardt Perry J, Lubner Meghan G, Sirlin Claude B, Dondlinger Timothy, Schmainda Michael, Jacobus Robert B, Severino Paige E, Smith Andrew D
Department of Radiology, The University of Alabama at Birmingham, JTN 452, 619 19th St S, Birmingham, AL 35249.
Department of Radiology, Duke University Medical Center, Durham, NC.
AJR Am J Roentgenol. 2022 May;218(5):833-845. doi: 10.2214/AJR.21.27062. Epub 2021 Dec 22.
In single-institution multireader studies, the liver surface nodularity (LSN) score accurately detects advanced liver fibrosis and cirrhosis and predicts liver decompensation in patients with chronic liver disease (CLD) from hepatitis C virus (HCV). The purpose of this study was to assess the diagnostic performance of the LSN score alone and in combination with the (FIB-4; fibrosis index based on four factors) to detect advanced fibrosis and cirrhosis and to predict future liver-related events in a multiinstitutional cohort of patients with CLD from HCV. This retrospective study included 40 consecutive patients, from each of five academic medical centers, with CLD from HCV who underwent nontargeted liver biopsy within 6 months before or after abdominal CT. Clinical data were recorded in a secure web-based database. A single central reader measured LSN scores using software. Diagnostic performance for detecting liver fibrosis stage was determined. Multivariable models were constructed to predict baseline liver decompensation and future liver-related events. After exclusions, the study included 191 patients (67 women, 124 men; mean age, 54 years) with fibrosis stages of F0-F1 ( = 37), F2 ( = 44), F3 ( = 46), and F4 ( = 64). Mean LSN score increased with higher stages (F0-F1, 2.26 ± 0.44; F2, 2.35 ± 0.37; F3, 2.42 ± 0.38; F4, 3.19 ± 0.89; < .001). The AUC of LSN score alone was 0.87 for detecting advanced fibrosis (≥ F3) and 0.89 for detecting cirrhosis (F4), increasing to 0.92 and 0.94, respectively, when combined with FIB-4 scores (both = .005). Combined scores at optimal cutoff points yielded sensitivity of 75% and specificity of 82% for advanced fibrosis, and sensitivity of 84% and specificity of 85% for cirrhosis. In multivariable models, LSN score was the strongest predictor of baseline liver decompensation (odds ratio, 14.28 per 1-unit increase; < .001) and future liver-related events (hazard ratio, 2.87 per 1-unit increase; = .03). In a multiinstitutional cohort of patients with CLD from HCV, LSN score alone and in combination with FIB-4 score exhibited strong diagnostic performance in detecting advanced fibrosis and cirrhosis. LSN score also predicted future liver-related events. The LSN score warrants a role in clinical practice as a quantitative marker for detecting advanced liver fibrosis, compensated cirrhosis, and decompensated cirrhosis and for predicting future liver-related events in patients with CLD from HCV.
在单机构多阅片者研究中,肝脏表面结节性(LSN)评分能准确检测晚期肝纤维化和肝硬化,并预测丙型肝炎病毒(HCV)所致慢性肝病(CLD)患者的肝失代偿情况。本研究的目的是评估单独使用LSN评分以及联合(FIB-4;基于四个因素的纤维化指数)检测晚期纤维化和肝硬化,并预测来自HCV的CLD患者多机构队列中未来肝脏相关事件的诊断性能。这项回顾性研究纳入了来自五个学术医疗中心的40例连续的HCV所致CLD患者,这些患者在腹部CT检查前或后6个月内接受了非靶向肝脏活检。临床数据记录在一个安全的基于网络的数据库中。由一名中央阅片者使用软件测量LSN评分。确定检测肝纤维化分期的诊断性能。构建多变量模型以预测基线肝失代偿和未来肝脏相关事件。排除后,研究纳入了191例患者(67例女性,124例男性;平均年龄54岁),纤维化分期为F0-F1(n = 37)、F2(n = 44)、F3(n = 46)和F4(n = 64)。平均LSN评分随着分期升高而增加(F0-F1,2.26±0.44;F2,2.35±0.37;F3,2.42±0.38;F4,3.19±0.89;P <.001)。单独使用LSN评分检测晚期纤维化(≥F3)的AUC为0.87,检测肝硬化(F4)的AUC为0.89,与FIB-4评分联合时分别增至0.92和0.94(P均 = 0.005)。最佳截断点的联合评分对晚期纤维化的敏感性为75%,特异性为82%,对肝硬化的敏感性为84%,特异性为85%。在多变量模型中,LSN评分是基线肝失代偿(优势比,每增加1个单位为14.28;P <.001)和未来肝脏相关事件(风险比,每增加1个单位为2.87;P = 0.03)的最强预测因子。在来自HCV的CLD患者多机构队列中,单独使用LSN评分以及联合FIB-4评分在检测晚期纤维化和肝硬化方面表现出强大的诊断性能。LSN评分还能预测未来肝脏相关事件。LSN评分作为检测晚期肝纤维化、代偿期肝硬化和失代偿期肝硬化以及预测来自HCV的CLD患者未来肝脏相关事件的定量标志物,在临床实践中值得发挥作用。