Abstract

The identification of hypoxia inducible factor (HIF-1α) expression is helpful for the quantitative assessment of tumor hypoxia. The application of multimodal imaging techniques may play a part in the assessment of HIF-1α expression of cervical carcinoma. To investigate the correlations between multiple imaging parameters and HIF-1α expression of early cervical carcinoma and to determine whether tumor hypoxia can be predicted using multisequence imaging parameters. Prospective observational. One hundred patients with early cervical carcinoma. 3.0 T MRI including intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) perfusion MRI sequences. DCE-MRI and IVIM DWI were performed for all patients. The imaging parameters included volume transfer constant (Ktrans ), rate constant (Kep ), extravascular extracellular volume fraction (Ve ), D, D*, and f. The comparisons of imaging parameters between two independent groups were performed using the Mann-Whitney U-test. Multiple linear regression analysis was performed to determine the correlation between multiple imaging parameters and HIF-1α expression. The diagnostic ability of DCE-MRI, IVIM DWI, and the combination of two techniques for discriminating high-expression and low-expression groups were analyzed. The high-expression group had a lower Ktrans or Kep value than the low-expression group (P = 0.03; 0.02), while the high-expression group had a higher Ve value than the low-expression group (P = 0.03). The high-expression group had a higher D or f value than the low-expression group (P = 0.02; 0.02). Ktrans , Kep , D, Ve , and f values were independently correlated with HIF-1α expression. The sensitivity or accuracy of a combined method was higher than that of DCE-MRI or IVIM DWI individually (P = 0.03, 0.02; 0.04, 0.03). The combination of DCE-MRI and IVIM DWI can improve the diagnostic ability of discriminating different HIF-1α expression levels for early cervical tumors. 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:918-929.

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