Abstract
The aim of this study is to develop a framework for quantitative analysis of longitudinal T2-weighted MRIs (T2w) following radiotherapy (RT) for prostate cancer.
The developed methodology includes: (i) deformable image registration of longitudinal series to pre-RT T2w for automated detection of prostate, peripheral zone (PZ), and gross tumor volume (GTV); and (ii) T2w signal-intensity harmonization based on three reference tissues. The REgistration and HARMonization (REHARM) framework was applied on T2w acquired in a clinical trial consisting of two pre-RT and three post-RT MRI exams. Image registration was assessed by the DICE coefficient between automatic and manual contours, and intensity normalization via inter-patient histogram intersection. Longitudinal consistency was evaluated by the repeatability coefficient and Pearson correlation (r) between the two T2w exams before RT.
T2w from 107 MRI exams (23 patients) were utilized. Following REHARM, the histogram intersections for prostate, PZ and GTV increased from median = 0.43/0.16/0.13 to 0.66/0.44/0.46. The repeatability in T2w intensity estimation was better for the automatic than the manual contours for all three ROIs (r = 0.9, p < 0.0001, for GTV). The changes in the tissues’ T2w values pre- and post-RT became significant, indicating the measurable quantitative signal related to radiation.
The developed methodology allows to automate longitudinal analysis reducing data acquisition-related variation and improving consistency. The quantitative characterization of RT-induced changes in T2w will lead to new understanding of radiation effects enabling prediction modeling of RT response.