Multi-parametric MRI in cervical cancer: early prediction of response to concurrent chemoradiotherapy in combination with clinical prognostic factors.

<bold>Objective: </bold>To investigate the prediction of response to concurrent chemoradiotherapy (CCRT) through a combination of pretreatment multi-parametric magnetic resonance imaging (MRI) with clinical prognostic factors (CPF) in cervical cancer patients.<bold>Methods: </bold>Sixty-five patients underwent conventional MRI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI (DCE-MRI) before CCRT. The patients were divided into non- and residual tumour groups according to post-treatment MRI. Pretreatment MRI parameters and CPF between the two groups were compared and prognostic factors, optimal thresholds, and predictive performance for post-treatment residual tumour occurrence were estimated.<bold>Results: </bold>The residual group showed a lower maximum slope of increase (MSIL) and signal enhancement ratio (SERL) in low-perfusion subregions, a higher apparent diffusion coefficient (ADC) value, and a higher stage than the non-residual tumour group (p < 0.001, p = 0.003, p < 0.001, and p < 0.001, respectively). MSIL and ADC were independent prognostic factors. The combination of both measures improved the diagnostic performance compared with individual MRI parameters. A further combination of these two factors with CPF exhibited the highest predictive performance.<bold>Conclusions: </bold>Pretreatment MSIL and ADC were independent prognostic factors for cervical cancer. The predictive capacity of multi-parametric MRI was superior to individual MRI parameters. The combination of multi-parametric MRI with CPF further improved the predictive performance.<bold>Key Points: </bold>• Pretreatment MSI L and ADC were independent prognostic factors for post-treatment residual tumours. • The residual groups showed lower MSI L , higher ADC and higher stage. • The predictive capacity of multi-parametric MRI was superior to individual MRI parameters. • The combination of multi-parametric MRI with CPF exhibited the highest predictive performance. [ABSTRACT FROM AUTHOR]