Another approach is the co-registration of histological slices to corresponding in vivo MRI slices by elastic (non-rigid) transformations of the histology image. Additional limitations of this approach are the difficulty of transferring the results of automatic segmentation of MRI to histology images, as well as difficulties in tissue segmentation when the ROI boundaries are not obvious (for example, the boundaries of inflammation within an ischemic lesion). This approach is entirely based on the qualifications of the operator and his subjective assessment. The first approach includes the manual segmentation of both types of images based on a visual correspondence of histology images with MRI slices. Several methods are used to solve this problem. For this reason, the identification of anatomically matching ROIs on MR images and histological sections is crucial. However, for 3D MRI images, the slope of slice can be corrected by free rotation (linear interpolation) of the slice plane, implemented, for example, in MRIcron or ImageJ free software.Ī more serious problem is that postmortem sections undergo distortion during tissue processing which may include shrinkage, tears, and folds. The slope of histological sections cannot be changed once they have been obtained. First, MRI and histological sections should have the same spatial location, which is determined by the coordinate perpendicular to the slice plane (for example, along the anteroposterior axis for coronal slices), as well as the slope of the slice relative to this axis (sagittal plane in the case of coronal slices). The reliability of the correlations between in vivo and ex vivo data is determined by the similar anatomy in the ROIs on MRI and histology images. Typically, the validation of new MRI techniques includes an evaluation of the relationship between MRI and histological measurements in anatomically similar areas or regions of interest (ROI). Cell transplantation studies and gene reporter imaging also require histological validation. Histological validation of MRI findings is an important component of animal models of cerebrovascular and neurodegenerative pathologies, animal tumor models, human post-MRI studies when the treatment includes resections, and human post-MRI post-mortem histopathology. The gold standards for confirming the accuracy of MRI myelin estimates are Luxol Fast Blue (LFB) histology staining, immunohistochemistry for myelin basic protein (MBP), or proteolipid protein (PLP). Quantitative MRI techniques with an improved specificity to myelin have been rapidly developed in recent decades, such as methods based on single- or multi-component relaxation, magnetization transfer, anisotropic diffusion, and magnetic susceptibility. Many of these methods are positioned as quantitative therefore, they must be histologically validated in experimental animal studies to provide the foundation for further clinical applications. Novel MRI methods have been developed for the evaluation of tissue composition (e.g., conducting tracts, myelin, collagen) or specific pathological conditions (ischemia, demyelination, inflammation). Magnetic resonance imaging (MRI) provides important information about anatomy and pathology, allowing a non-invasive assessment of an organ’s structure and function.
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