Three-dimensional histology reveals dissociable human hippocampal long-axis gradients of Alzheimer's pathology

Abstract

Introduction: Three-dimensional (3D) histology analyses are essential to overcome sampling variability and understand pathological differences beyond the dissection axis. We present Path2MR, the first pipeline allowing 3D reconstruction of sparse human histology without a magnetic resonance imaging (MRI) reference. We implemented Path2MR with post-mortem hippocampal sections to explore pathology gradients in Alzheimer's disease.

Methods: Blockface photographs of brain hemisphere slices are used for 3D reconstruction, from which an MRI-like image is generated using machine learning. Histology sections are aligned to the reconstructed hemisphere and subsequently to an atlas in standard space.

Results: Path2MR successfully registered histological sections to their anatomic position along the hippocampal longitudinal axis. Combined with histopathology quantification, we found an expected peak of tau pathology at the anterior end of the hippocampus, whereas amyloid-beta (Aβ) displayed a quadratic anterior-posterior distribution.

Conclusion: Path2MR, which enables 3D histology using any brain bank data set, revealed significant differences along the hippocampus between tau and Aβ.

Highlights: Path2MR enables three-dimensional (3D) brain reconstruction from blockface dissection photographs. This pipeline does not require dense specimen sampling or a subject-specific magnetic resonance (MR) image. Anatomically consistent mapping of hippocampal sections was obtained with Path2MR. Our analyses revealed an anterior-posterior gradient of hippocampal tau pathology. In contrast, the peak of amyloid-beta (Aβ) deposition was closer to the hippocampal body.

Keywords: amyloid beta; hippocampus; histology; machine learning; neuropathology; photography; reconstruction; tau; three dimensional.