Early prediction of disease progression is of potential clinical significance for the management of high-grade glioma (HGG) patients. We investigated the value of histogram models based on volume transfer constant (Ktrans) between the plasma and extravascular extracellular space and extravascular volume (Ve) in predicting the progression of enhancing non-measurable diseases (NMD) of HGG after chemoradiotherapy. Our results showed that histogram models based on Ktrans and Ve can accurately predict the progression of enhancing NMD of HGG following chemoradiotherapy, and combining Ktrans and Ve helps improve the prediction performance.
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Cao et al. (2024) studied this question.
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