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Updated: Feb 12, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
Published on: September 25, 2019
An image registration protocol to integrate electrophysiology, MRI and neuropathology data in epileptic patients
Ileana Zucca1, Gloria Milesi2, Francesco Padelli1
1Scientific Department, Fondazione IRCCS, Istituto Neurologico C. Besta, Milano, Italy.
Background:
Several attempts have been made to coregister in vivo MRI with the histopathology of surgical samples, aiming to validate new MRI biomarkers and improve the detection of epileptogenic lesions. As a further implementation, we propose a method to reconstruct the anatomical localization of the intracerebral electrodes on the histological sections, developing a coregistration protocol to match the in vivo MRI onto the ex vivo MRI obtained from the surgical specimen.
New Method:
Since the ex vivo MRI is natively in geometrical correspondence with histology slices, the goal of the coregistration process is to compute the transform function mapping the clinical MRI space to the ex vivo MRI. Electrodes and leads, identified in CT-MRI, can then be segmented and translated onto the histological slices.
Results:
Step-by-step, qualitative visual inspection showed an improved matching of the anatomical structures or boundaries and electrodes positions between the two modalities. The quantitative evaluation of the coregistration protocol reported a mean error ranging between 0.82 and 1.27 mm when a sufficient number of landmarks, particularly in the core of the specimen, were clearly identified.
Comparison With Existing Methods:
Because histology was performed according to ex vivo MRI geometry we chose to transform the in vivo onto the ex vivo MRI, differently from other methods.
Conclusions:
Interesting applications of the method will include correlating the locally-generated pathological electrical activity with the subtle morphological alterations of the tissue, and histologically validating the origin of signal alterations or quantitative parameter variations in MRI studies.
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