Registration and warping of magnetic resonance images to histological sections

We present a method for coregistration and warping of magnetic resonance images (MRI) to histological sections for comparison purposes. This methodology consists of a modified head and hat surface-based registration algorithm followed by a new automated warping approach using nonlinear thin plate splines to compensate for distortions between the data sets. To test the methodology, 15 male Wistar rats were subjected to focal cerebral ischemia via permanent occlusion of the middle cerebral artery. The MRI images were acquired in separate groups of animals at 16-24 h (n=9) and 48-168 h (n=6) postocclusion, After imaging, animals were immediately sacrificed and hematoxylin- and eosin-stained brain sections were obtained for histological analysis. The MRI was coregistered and warped to histological sections. The MRI lesion areas were defined using the Eigenimage (EI) filter technique. The EI is a linear filter that maximizes the projection of a desired tissue (ischemic tissue) while it minimizes the projection of undesired tissues (nonischemic tissue) onto a composite image called an EI. When using coregistration without warping the MRI lesion area demonstrated poor correlation (r=0.55, p>0.01) with a percent difference between the two lesion areas of 22.5%+/-10.8%. After warping, the MRI and histology had significant correlation (r=0.97, p<0.01) and a decreased percent difference of 5.56%+/-4.31%. This methodology is simple and robust for coregistration and warping of MRI to histological sections and can be utilized in many applications for comparison of MRI to histological data. (C) 1999 American Association of Physicists in Medicine. [S0094-2405(99)00908-6].