Interpretable model based on multisequence magnetic resonance imaging radiomics for predicting the pathological grades of hepatocellular carcinomas

doi:10.4329/wjr.v17.i12.112911

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World Journal of Radiology

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1949-8470

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Radiol. Dec 28, 2025; 17(12): 112911
Published online Dec 28, 2025. doi: 10.4329/wjr.v17.i12.112911

Table 3 Screened optimal radiomic features

MRI sequence	Feature type	Feature name
FS-T2WI	wavelet-HLL_first order	Kurtosis
	wavelet-HLL_glcm	Idn
	wavelet-HLL_gldm	Large dependence high gray level emphasis
AP	Original_shape	Sphericity
	Original_glcm	Cluster prominence
	Original_glszm	Large area high gray level emphasis
	wavelet-LLL_glcm	Cluster prominence
PVP	Original_shape	Sphericity
	log-sigma-2-5-mm-3D_ gldm	Small dependence high gray level emphasis
	wavelet-HHL_glszm	Large area emphasis
	wavelet-HHL_glszm	Small area emphasis
	wavelet-LLL_glcm	Cluster prominence

MRI: Magnetic resonance imaging; FS-T2WI: Fat-suppressed T2-weighted image; AP: Arterial phase; PVP: Portal venous phase; Idn: Inverse difference normalized.

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Citation: Shi Y, Zhang P, Li L, Yang HM, Li ZM, Zheng J, Yang L. Interpretable model based on multisequence magnetic resonance imaging radiomics for predicting the pathological grades of hepatocellular carcinomas. World J Radiol 2025; 17(12): 112911
URL: https://www.wjgnet.com/1949-8470/full/v17/i12/112911.htm
DOI: https://dx.doi.org/10.4329/wjr.v17.i12.112911

Shi Y, Zhang P, Li L, Yang HM, Li ZM, Zheng J, Yang L. Interpretable model based on multisequence magnetic resonance imaging radiomics for predicting the pathological grades of hepatocellular carcinomas. World J Radiol 2025; 17(12): 112911 [PMID: 41480292 DOI: 10.4329/wjr.v17.i12.112911]

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