» Articles » PMID: 28937853

Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging

Overview
Journal Radiology
Specialty Radiology
Date 2017 Sep 23
PMID 28937853
Citations 74
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose To evaluate the potential role of diffusion kurtosis imaging and conventional magnetic resonance (MR) imaging findings including standard monoexponential model of diffusion-weighted imaging and morphologic features for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Materials and Methods Institutional review board approval and written informed consent were obtained. Between September 2015 and November 2016, 84 patients (median age, 54 years; range, 29-79 years) with 92 histopathologically confirmed HCCs (40 MVI-positive lesions and 52 MVI-negative lesions) were analyzed. Preoperative MR imaging examinations including diffusion kurtosis imaging (b values: 0, 200, 500, 1000, 1500, and 2000 sec/mm) were performed and kurtosis, diffusivity, and apparent diffusion coefficient maps were calculated. Morphologic features of conventional MR images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of these parameters as potential predictors of MVI. Results Features significantly related to MVI of HCC at univariate analysis were increased mean kurtosis value (P < .001), decreased mean diffusivity value (P = .033) and apparent diffusion coefficient value (P = .011), and presence of infiltrative border with irregular shape (P = .005) and irregular circumferential enhancement (P = .026). At multivariate analysis, mean kurtosis value (odds ratio, 6.25; P = .001), as well as irregular circumferential enhancement (odds ratio, 6.92; P = .046), were independent risk factors for MVI of HCC. The mean kurtosis value for MVI of HCC showed an area under the receiver operating characteristic curve of 0.784 (optimal cutoff value was 0.917). Conclusion Higher mean kurtosis values in combination with irregular circumferential enhancement are potential predictive biomarkers for MVI of HCC. RSNA, 2017.

Citing Articles

Advances in multi-omics studies of microvascular invasion in hepatocellular carcinoma.

Wang L, Xu H, Wang R, Zhang F, Deng D, Zhu X Eur J Med Res. 2025; 30(1):165.

PMID: 40075448 PMC: 11905518. DOI: 10.1186/s40001-025-02421-w.


Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study.

Nong H, Cen Y, Lu S, Huang R, Chen Q, Huang L World J Gastrointest Oncol. 2025; 17(1):96439.

PMID: 39817122 PMC: 11664629. DOI: 10.4251/wjgo.v17.i1.96439.


Nomogram based on the neutrophil-to-lymphocyte ratio and MR diffusion quantitative parameters for predicting Ki67 expression in hepatocellular carcinoma from a prospective study.

Wei Y, Yun L, Liang Y, Grimm R, Yang C, Tao Y Sci Rep. 2024; 14(1):31738.

PMID: 39738357 PMC: 11685758. DOI: 10.1038/s41598-024-82333-7.


Pathological prognostic factors of rectal cancer based on diffusion-weighted imaging, intravoxel incoherent motion, and diffusion kurtosis imaging.

Zhou M, Chen M, Luo M, Chen M, Huang H Eur Radiol. 2024; 35(2):979-988.

PMID: 39143248 DOI: 10.1007/s00330-024-11025-7.


Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.

Ma Y, Yue P, Zhang J, Yuan J, Liu Z, Chen Z Ann Med. 2024; 56(1):2357354.

PMID: 38813815 PMC: 11141304. DOI: 10.1080/07853890.2024.2357354.