ArticleFrontiers in oncology2025
Amide proton transfer-weighted imaging combined with multiple models diffusion-weighted imaging of endometrial cancer: correlations between multi-modal MRI parameters and HIF-1α expression.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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Corrections and comments
- Erratum issued
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10 authors.
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Abstract
Background: 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. Purpose: 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. Study type: Retrospective. Population: 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. Field Strength/Sequence: 3.0T/APTw, DWI, IVIM, and DKI. Assessment: The asymmetry of magnetization transfer rate (MTR Statistical Test: 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 Result: MTR Conclusion: 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.
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