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Abstract #4795

Multiparametric MRI as an early outcome predictor to chemotherapy and radiotherapy in cervical cancers

Jelena Mihailovic1,2, Aleksandar Tomasevic3, Fahmeed Hyder1,4, and Daniel Coman1
1(1) Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, United States, 2(2) Department of Diagnostic Radiology, Yale University, New Haven, CT, United States, 3Institute for Oncology and Radiology Of Serbia, Belgrade, Yugoslavia, 4Center for Quantitative Neuroscience with Magnetic Resonance (QNMR), Yale University, New Haven, CT, United States

Pre/early intra-treatment prediction of patients with cervical cancer would enable treatment regimens to be changed at an early time point. We focused on diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI for quantifying of the tumor microenvironment in prediction of treatment response. Perfusion fraction multiplied by pseudo-diffusion coefficient, plasma flow, transfer constant between plasma and extracellular extravascular space were the parameters statistically significant associated with treatment outcome based on 95% CI in multivariate logistic regression model. Multi-parametric MRI techniques have the potential to assess tumor grade differentiation, and they showed additional value in detecting and therefore, predicting treatment response.

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