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Histogram analysis of multiple mathematical diffusion-weighted imaging models for preoperative prediction of Ki-67 expression in hepatocellular carcinoma

  • 0Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Frontiers in Oncology +

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March 26, 2025

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March 26, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Predicting hepatocellular carcinoma (HCC) cell proliferation is possible using diffusion-weighted imaging (DWI) histogram parameters. A combined model including alpha-fetoprotein (AFP) and DWI metrics effectively predicts Ki-67 expression in HCC.

Area Of Science

  • Radiology
  • Oncology
  • Medical Imaging

Background

  • Ki-67 expression is a key indicator of hepatocellular carcinoma (HCC) cell proliferation.
  • Accurate prediction of Ki-67 expression is crucial for guiding treatment decisions in HCC management.

Purpose Of The Study

  • To investigate the utility of clinico-radiological factors and histogram parameters from diffusion-weighted imaging (DWI) using various mathematical models for predicting Ki-67 expression in HCC.
  • To develop and validate a predictive model for Ki-67 expression in HCC.

Main Methods

  • Whole-tumor histogram parameters were derived from monoexponential, biexponential, and stretched exponential DWI models.
  • Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were employed to assess predictive performance.
  • A combined model incorporating alpha-fetoprotein (AFP) level, skewness of perfusion fraction (f), and 5th percentile of distributed diffusion coefficient (DDC) was developed.

Main Results

  • The 5th percentile of DDC showed significant predictive value (AUC 0.816 training, 0.867 test set).
  • Multivariable analysis identified AFP level, skewness of f, and 5th percentile of DDC as independent predictors of high Ki-67 expression.
  • The combined model achieved high predictive accuracy in both training (AUC 0.902) and test sets (AUC 0.908).

Conclusions

  • Histogram parameters from multiple DWI mathematical models are valuable for predicting high Ki-67 expression in HCC.
  • The developed combined model, utilizing AFP, skewness of f, and 5th percentile of DDC, offers an effective approach for predicting Ki-67 expression in HCC.

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