Motivation: Time dependent diffusion MRI coud be utilized to quantify cell size, cellulartity, and extracellular space, but its ability to distinguish histopathological parameters of cervical cancer remains unknown. Goal(s): This study aims to evaluate the potential of time-dependent diffusion MRI with whole-tumor histogram analysis to non-invasively predict aggressive characteristics of cervical cancer Approach: Using the IMPULSED model, we extracted diffusion parameters from time-dependent diffusion MRI. Subsequently, histogram features were extracted from these parameters and assessed their diagnostic accuracy. Results: Our findings indicate that time-dependent diffusion MRI with whole-tumor histogram analysis can predict histologic differentiation degree, LVSI, LNM, and FIGO stage in CC. Impact: This study highlights time-dependent diffusion MRI with whole-tumor histogram analysis as a valuable tool for non-invasively assessing cervical cancer aggressiveness, potentially improving treatment planning and patient outcomes.
TianHui et al. (Tue,) studied this question.