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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