Radiomics Based on Contrast-Enhanced MRI in Differentiation Between Fat-Poor Angiomyolipoma and Hepatocellular Carcinoma in Noncirrhotic Liver: A Multicenter Analysis

Abstract

ObjectiveThis study aims to develop and externally validate a contrast-enhanced magnetic resonance imaging (CE-MRI) radiomics-based model for preoperative differentiation between fat-poor angiomyolipoma (fp-AML) and hepatocellular carcinoma (HCC) in patients with noncirrhotic livers and to compare the diagnostic performance with that of two radiologists.MethodsThis retrospective study was performed with 165 patients with noncirrhotic livers from three medical centers. The dataset was divided into a training cohort (n = 99), a time-independent internal validation cohort (n = 24) from one center, and an external validation cohort (n = 42) from the remaining two centers. The volumes of interest were contoured on the arterial phase (AP) images and then registered to the venous phase (VP) and delayed phase (DP), and a total of 3,396 radiomics features were extracted from the three phases. After the joint mutual information maximization feature selection procedure, four radiomics logistic regression classifiers, including the AP model, VP model, DP model, and combined model, were built. The area under the receiver operating characteristic curve (AUC), diagnostic accuracy, sensitivity, and specificity of each radiomics model and those of two radiologists were evaluated and compared.ResultsThe AUCs of the combined model reached 0.789 (95%CI, 0.579–0.999) in the internal validation cohort and 0.730 (95%CI, 0.563–0.896) in the external validation cohort, higher than the AP model (AUCs, 0.711 and 0.638) and significantly higher than the VP model (AUCs, 0.594 and 0.610) and the DP model (AUCs, 0.547 and 0.538). The diagnostic accuracy, sensitivity, and specificity of the combined model were 0.708, 0.625, and 0.750 in the internal validation cohort and 0.619, 0.786, and 0.536 in the external validation cohort, respectively. The AUCs for the two radiologists were 0.656 and 0.594 in the internal validation cohort and 0.643 and 0.500 in the external validation cohort. The AUCs of the combined model surpassed those of the two radiologists and were significantly higher than that of the junior one in both validation cohorts.ConclusionsThe proposed radiomics model based on triple-phase CE-MRI images was proven to be useful for differentiating between fp-AML and HCC and yielded comparable or better performance than two radiologists in different centers, with different scanners and different scanning parameters.

Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses

“…All included papers have been published since 2015, with an increase from 2019. The most studied organs are the prostate [3] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] (S-Table I), female pelvis [4] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] (S-Table II), and rectum [5] , [53] , [54] , [55] , [56] , [57] , [58] , [59] , [60] , [61] , [62] , [63] , [64] , [65] , [66] , [67] , [68] , [69] (S-Table III), while a lower number of publications were related to the liver [6] , [70] , [71] , [72] , [73] , [74] , [75] (S-Table IV), and a miscellaneous group of organs including kidney [76] , [77] , …”

“…This paradigmatic shift was made possible by the development of radiomics, which allows the extraction, from medical images, of quantitative features providing useful information on diagnosis and prognosis [1] , [2] . Despite the encouraging results provided by recent studies [3] , [5] , [6] , there is still no radiomics-based systems used in clinical practice for abdominal imaging. This is mainly due to the lack of multi-center clinical trials for both system development and validation [7] .…”

A T2 Weighted Imaging-based Radiomics Nomogram for the Classification of Hepatic Blood-rich Lesions: Hepatocellular Carcinoma and Benign Liver Lesions

“…Formerly, many studies have supplied several methods to discriminate against HCC from various BLLs, such as fp-AMLs, FNH, HH and so on [23,24]. It is obvious that most of them analyzed HCC and another benign lesion with rich blood supply by CE-CT/MRI.…”

MRI Radiomics in Imaging of Focal Hepatic Lesions: A Narrative Review

“…It was discovered that the fusion models were very good at differentiating HEAML from FNH and HCC, which suggests that they could be used as diagnostic tools for customized treatment plans [ 17 ]. The purpose of the study by Zhao et al was to create and verify a radiomics-based model for the preoperative distinction between HCC and fat-poor angiomyolipoma (fp-AML) in noncirrhotic livers using contrast-enhanced MRI (CE-MRI) [ 18 ]. A dataset including three cohorts - a training cohort, an internal validation cohort, and an external validation cohort - was used to evaluate the model on 165 patients from three different medical centers [ 18 ].…”