Abstract #0189

Volumetric Histology via High-Fidelity Coregistration with MRI

Yixin Wang¹, William Ho², Istvan N. Huszar³, Hossein Moein Taghavi², Jeff Nirschl⁴, Lee Tao², Nhu Nguyen², Samantha Leventis², David Camarillo¹, Philipp Schlömer⁵, Markus Axer⁵, Wei Shao⁶, Mirabela Rusu², Phillip DiGiacomo², Inma Cobos⁴, Marios Georgiadis², and Michael Zeineh²

¹Department of Bioengineering, Stanford University, Palo Alto, CA, United States, ²Department of Radiology, Stanford School of Medicine, Palo Alto, CA, United States, ³Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, United States, ⁴Department of Pathology, Stanford School of Medicine, Palo Alto, CA, United States, ⁵Forschungszentrum Jülich, Jülich, Germany, ⁶Department of Electrical & Computer Engineering, University of Florida, Gainesville, FL, United States

Synopsis

Keywords: Alzheimer's Disease, Tissue Characterization, biomarkers, Correlative MR-Histology

Motivation: Corroborating findings in 3D from ex-vivo MRI with densely-sampled histology is essential to biomarker development, but challenging due to nonlinear 3D deformations.

Goal(s): Reconstructing volumetric histology by accurately aligning densely-sampled histological images with post-mortem MRI data to enhance validation of 3D pathological findings.

Approach: We built and optimized a novel pipeline integrating advanced imaging with precise registration algorithms to link high-resolution MRI via blockface imaging to volumetric 3D histology aligned.

Results: Our optimized blockface volumes contain minimal artifacts and were precisely aligned with MRI, facilitating the coregistration of multi-slice histology, and demonstrating accurate correspondences between MRI and histology slides in 3D.

Impact: This study introduces an advanced correlative MRI-histology pipeline to reconstruct volumetric histology, promising to enhance our understanding of neurodegenerative diseases and contribute to the evolution of MRI-based disease biomarkers.

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