Multiparametric MRI habitat radiomics and longitudinal dynamic clinical parameters predict TACE refractoriness in HCC
Abstract
Predicting transarterial chemoembolization (TACE) refractoriness is critical for optimizing treatment strategies in hepatocellular carcinoma (HCC); however, accurate risk assessment remains challenging. The initial therapeutic response, captured through imaging and clinical indicators, reflects intrinsic treatment sensitivity and holds substantial predictive value for long-term refractoriness. This study evaluated treatment effect heterogeneity following the initial TACE to develop a multimodal nomogram for predicting TACE refractoriness after repeated sessions. Using multiparametric MRI spatial habitat radiomics, we identified three imaging-defined habitats with signal profiles resembling liquefactive necrosis, residual viable tumor, and coagulative necrosis. By integrating habitat and conventional radiomic features, an interpretable radiomic score was constructed utilizing eight machine learning algorithms. This score was subsequently combined with longitudinal dynamic clinical parameters to build a joint clinical-radiomic nomogram. The nomogram achieved areas under the curve (AUCs) of 0.924, 0.860, and 0.864 in the training, internal validation, and external validation cohorts, respectively. These findings suggest that integrating habitat radiomics with dynamic clinical features may help stratify the risk of subsequent TACE refractoriness after the initial TACE session and before repeated treatment, potentially supporting early treatment-response assessment and individualized clinical decision-making.
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BibTeX
@article{liu2026multiparametric,
title = {{Multiparametric MRI habitat radiomics and longitudinal dynamic clinical parameters predict TACE refractoriness in HCC}},
author = {Jia-Kang Liu and Yu-Qin Gu and Qi-Ao Sun and Jiang-Han Chang and Jian Zhao and Yan-Bin Liu and Hao-Sheng Chen and Ke Li and Xiao-Xue Zhang and Jun-Tao Zhang and Fu-Zhou Li and Wei-Wei Lv and Yan-Feng Liu},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-74555-8},
url = {https://www.nature.com/articles/s41598-026-74555-8},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Multiparametric MRI habitat radiomics and longitudinal dynamic clinical parameters predict TACE refractoriness in HCC
AU - Jia-Kang Liu
AU - Yu-Qin Gu
AU - Qi-Ao Sun
AU - Jiang-Han Chang
AU - Jian Zhao
AU - Yan-Bin Liu
AU - Hao-Sheng Chen
AU - Ke Li
AU - Xiao-Xue Zhang
AU - Jun-Tao Zhang
AU - Fu-Zhou Li
AU - Wei-Wei Lv
AU - Yan-Feng Liu
PY - 2026
DA - 2026/10/09
JO - Scientific Reports
DO - 10.1038/s41598-026-74555-8
UR - https://www.nature.com/articles/s41598-026-74555-8
AB - Predicting transarterial chemoembolization (TACE) refractoriness is critical for optimizing treatment strategies in hepatocellular carcinoma (HCC); however, accurate risk assessment remains challenging. The initial therapeutic response, captured through imaging and clinical indicators, reflects intrinsic treatment sensitivity and holds substantial predictive value for long-term refractoriness. This study evaluated treatment effect heterogeneity following the initial TACE to develop a multimodal nomogram for predicting TACE refractoriness after repeated sessions. Using multiparametric MRI spatial habitat radiomics, we identified three imaging-defined habitats with signal profiles resembling liquefactive necrosis, residual viable tumor, and coagulative necrosis. By integrating habitat and conventional radiomic features, an interpretable radiomic score was constructed utilizing eight machine learning algorithms. This score was subsequently combined with longitudinal dynamic clinical parameters to build a joint clinical-radiomic nomogram. The nomogram achieved areas under the curve (AUCs) of 0.924, 0.860, and 0.864 in the training, internal validation, and external validation cohorts, respectively. These findings suggest that integrating habitat radiomics with dynamic clinical features may help stratify the risk of subsequent TACE refractoriness after the initial TACE session and before repeated treatment, potentially supporting early treatment-response assessment and individualized clinical decision-making.
SN - 2045-2322
ER -