A semi-automatic registration protocol to match ex-vivo high-field 7T MR images and histological slices in surgical samples from patients with drug-resistant epilepsy

Abstract

BackgroundMRI is a fundamental tool to detect brain structural anomalies and improvement in this technique has the potential to visualize subtle abnormalities currently undetected. Correlation between pre-operative MRI and histopathology is required to validate the neurobiological basis of MRI abnormalities. However, precise MRI-histology matching is very challenging with the surgical samples. We previously developed a coregistration protocol to match the in-vivo MRI with ex-vivo MRI obtained from surgical specimens. Now, we complete the process to successfully align ex-vivo MRI data with the proper digitalized histological sections in an automatic way. New methodThe implemented pipeline is composed by the following steps: a) image pre-processing made of MRI and histology volumes conversion and masking; b) gross rigid body alignment between MRI volume and histology virtual slides; c) rigid alignment between each MRI section and histology slice and estimate of the correlation coefficient for each step to select the MRI slice that best matches histology; d) final linear registration of the selected slices. ResultsThis method is fully automatic, except for the first masking step, fast and reliable in comparison to the manual one, as assessed using a Bland-Altman plot. Comparison with existing methodsThe visual assessment usually employed for choosing the best fitting ex-vivo MRI slice for each stained section takes hours and requires practice. Goubran et al. (2015) proposed an iterative registration protocol but its aim and methods were different from ours. No others similar methods are reported in the literature. ConclusionsThis protocol completes our previous pipeline. The ultimate goal will be to apply the entire process to finely investigate the relationship between clinical MRI data and histopathological features in patients with drug-resistant epilepsy.