Introducing ARONG, A 3D Reconstruction Method for Highly Deformed Histology

Area of Science:

• Biomedical Engineering
• Digital Pathology
• Medical Imaging

Background:

• Three-dimensional (3D) histopathology offers enhanced diagnostic and treatment insights but faces challenges with highly deformable tissues.
• Existing 3D reconstruction methods struggle with significant deformations and spatially disconnected components common in tissues like carotid plaques.

Purpose of the Study:

• To develop a novel 3D reconstruction pipeline, ARONG (Artifact-correcting Reconstruction Of Nonrigidly-deformed Geometries), specifically for highly deformed histology.
• To address challenges in reconstructing complex, non-rigid tissue structures and artifacts inherent in histological processing.

Main Methods:

• ARONG employs iterative alignment of 2D histology slides using affine transformations.
• The pipeline incorporates context-dependent artifact correction and specific matching criteria for distorted local features.
• It provides guidance on artifact correction mechanisms and their priority for complex tissue samples.

Main Results:

• ARONG successfully reconstructed 3D histology from twenty human atheromatous carotid plaques.
• The pipeline achieved a Jaccard index of 0.64 ± 0.19 when compared with ex vivo ultrasound for four specimens.
• ARONG demonstrated superior performance over the state-of-the-art CODA method, achieving approximately 14% higher Jaccard index.

Conclusions:

• ARONG provides a robust solution for 3D reconstruction of highly deformed histology, including samples with disconnected components.
• The pipeline's effectiveness was validated across various tissue types, including human tumors, murine hearts, and arteries.
• ARONG represents a significant advancement in 3D histopathology, enabling more accurate reconstructions for challenging biological samples.