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A fast, model-independent method for cerebral cortical thickness estimation using MRI.

M L J Scott¹, P A Bromiley, N A Thacker

¹Division of Imaging Science and Biomedical Engineering, School of Cancer and Imaging Sciences, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK.

Medical Image Analysis

|December 11, 2008

Summary

This study introduces a novel voxel-based method for measuring human brain cortical thickness from MR images. This faster, more accurate technique avoids biases found in traditional deformable model approaches, especially in cases of severe cortical atrophy.

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Area of Science:

Neuroimaging
Computational Anatomy
Medical Image Analysis

Background:

Cortical thickness measurement from MR images is crucial for understanding brain structure and function.
Existing deformable model-based methods face limitations including computational expense and potential bias, particularly in cases of severe cortical atrophy.

Purpose of the Study:

To present a novel, faster, and more accurate voxel-based technique for measuring cortical thickness using inversion recovery anatomical MR images.
To overcome the limitations of deformable model-based methods, especially in challenging neuroimaging datasets.

Main Methods:

A voxel-based approach utilizing inversion recovery anatomical MR images.
Segmentation of grey matter, white matter, and cerebrospinal fluid (CSF).

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Edge detection to identify tissue boundaries and measurement of cortical thickness along the 3D surface normal.

Main Results:

The proposed technique demonstrated comparable accuracy to existing methods.
It offers a significant reduction in processing time compared to deformable model-based alternatives.
The method is robust and applicable to datasets with severe cortical atrophy and high curvature.

Conclusions:

The new voxel-based method provides an accurate and efficient alternative for cortical thickness measurement.
It is free from the potential biases associated with deformable model fitting.
This technique enhances the applicability of cortical thickness analysis in diverse neuroimaging studies, including those with significant brain atrophy.