Virtual MR Elastography and Multi-b-value DWI Models for Predicting Microvascular Invasion in Solitary BCLC Stage A Hepatocellular Carcinoma

Zhaowei Chen; Yongjian Zhu; Leyao Wang; Rong Cong; Bing Feng; Wei Cai; Meng Liang; Dengfeng Li; Shuang Wang; Mancang Hu; Yongtao Mi; Sicong Wang; Xiaohong Ma; Xinming Zhao

doi:10.1016/j.acra.2024.11.027

Virtual MR Elastography and Multi-b-value DWI Models for Predicting Microvascular Invasion in Solitary BCLC Stage A Hepatocellular Carcinoma

Acad Radiol. 2024 Dec 5:S1076-6332(24)00871-7. doi: 10.1016/j.acra.2024.11.027. Online ahead of print.

Authors

Zhaowei Chen¹, Yongjian Zhu², Leyao Wang³, Rong Cong⁴, Bing Feng⁵, Wei Cai⁶, Meng Liang⁷, Dengfeng Li⁸, Shuang Wang⁹, Mancang Hu¹⁰, Yongtao Mi¹¹, Sicong Wang¹², Xiaohong Ma¹³, Xinming Zhao¹⁴

Affiliations

¹ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
² Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
³ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
⁴ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
⁵ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
⁶ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
⁷ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
⁸ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
⁹ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
¹⁰ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
¹¹ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
¹² Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing 100176, China (S.W.). Electronic address: [email protected].
¹³ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].
¹⁴ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China (Z.C., Y.Z., L.W., R.C., B.F., W.C., M.L., D.L., S.W., M.H., Y.M., X.M., X.Z.). Electronic address: [email protected].

PMID: 39643466
DOI: 10.1016/j.acra.2024.11.027

Abstract

Rationale and objectives: To evaluate the performance of virtual MR elastography (vMRE) for predicting microvascular invasion (MVI) in Barcelona Clinic Liver Cancer (BCLC) stage A (≤ 5.0 cm) hepatocellular carcinoma (HCC) and to construct a combined nomogram based on vMRE, multi-b-value DWI models, and clinical-radiological (CR) features.

Methods: Consecutive patients with suspected HCC who underwent multi-b-value DWI examinations were prospectively collected. Quantitative parameters from vMRE, mono-exponential, intravoxel incoherent motion, and diffusion kurtosis imaging models were obtained. Multivariate logistic regression was used to identify independent MVI predictors and build prediction models. A combined MRI_Score was constructed using independent quantitative parameters. A visualized nomogram was built based on significant CR features and MRI_Score. The predictive performance of quantitative parameters and models was evaluated.

Results: The study included 103 patients (median age: 56 years; range: 35-70 years; 87 males and 16 females). Diffusion-based shear modulus (μ_Diff) exhibited a predictive performance for MVI with area under the curve (AUC) of 0.735. The MRI_Score was developed employing true diffusion coefficient (D), mean kurtosis (MK), and μ_Diff. CR model and MRI_Score achieved AUCs of 0.787 and 0.840, respectively. The combined nomogram based on AFP, corona enhancement, tumor capsule, TTPVI, and MRI_Score significantly improved the predictive performance to an AUC of 0.931 (Delong test p < 0.05).

Conclusion: vMRE exhibited great potential for predicting MVI in BCLC stage A HCC. The combined nomogram integrating CR features, vMRE, and quantitative diffusion parameters significantly improved the predictive accuracy and could potentially assist clinicians in identifying appropriate treatment options.

Keywords: Diffusion-weighted imaging; Hepatocellular carcinoma; Magnetic Resonance elastography; Magnetic resonance imaging; Microvascular invasion.