Amide proton transfer-weighted imaging combined with multiple models diffusion-weighted imaging of endometrial...

Hypoxia inducible factor (HIF-1α) is a major transcriptional factor regulating gene expression under hypoxic conditions. HIF-1α expression was closely correlated with the oxygenation status of tumor and could serve as an important biomarker for tumor hypoxia, aggressiveness, or radiation resistance. High expression of HIF-1α contributes to high aggressiveness or poor prognosis of endometrial cancer.

This study aimed to investigate correlations between multimodal MRI parameters (derived from amide proton transfer weighted imaging [APTw], conventional diffusion weighted imaging [DWI], intravoxel incoherent motion [IVIM] imaging and diffusion kurtosis imaging [DKI]) and HIF-1α expression, and to determine whether multimodal MRI can be used for quantitative evaluation of HIF-1α expression.

Retrospective.

A total of 94 patients with EC were examined with 32 cases finally included in the high HIF-1α expression group and 40 cases included in the low expression group according to the exclusion and inclusion criteria.

3.0T/APTw, DWI, IVIM, and DKI.

The asymmetry of magnetization transfer rate (MTR_asym), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) were calculated from multimodal MRI and compared between HIF-1α high expression and HIF-1α low expression groups.

Mann-Whitney U-test; Chi-square test or Fisher exact test; logistic regression analysis; Area under the receiver operating characteristic (ROC) curve (AUC); The Delong test; Pearson or Spearman correlation coefficients. The significance threshold was set at P < 0.05.

MTR_asym, ADC, D, D*, MK and MD values were significantly higher in high HIF-1α expression than in low HIF-1α expression groups, whereas f value was significantly lower in high HIF-1α expression than in low HIF-1α expression groups. The AUC of HIF-1 α expression evaluated by MTR_asym, ADC, D, D*, f, MD, MK and their combination were 0.894 (0.740, 0.973), 0.746 (0.568, 0.879), 0.716 (0.528, 0.904), 0.920 (0.772, 0.984), 0.756 (0.578, 0.886), and 0.973 (0.851-1.000), respectively. Multivariate analysis revealed that only f, MK, and MD values were independent predictors for evaluating HIF-1α expression in EC.

APTw combined with multi-model diffusion imaging can quantitatively evaluate the expression of HIF-1α in EC, and the combination of multiple quantitative parameters can improve the evaluation efficiency.