Evolutionary Paradigms in Histopathology Serial Sections technology

TL;DR

This review discusses recent advances in serial section-based histopathology, highlighting computational methods for 3D reconstruction and molecular profiling that improve diagnostic precision in oncology and inflammatory diseases.

Contribution

It categorizes key computational workflows and outlines future directions integrating spatial transcriptomics and AI for enhanced histopathological analysis.

Findings

Enhanced 3D histoarchitecture reconstruction techniques

Integration of multimodal imaging for molecular profiling

Identification of challenges in dataset harmonization and interpretability

Abstract

Histopathological analysis has been transformed by serial section-based methods, advancing beyond traditional 2D histology to enable volumetric and microstructural insights in oncology and inflammatory disease diagnostics. This review outlines key developments in specimen preparation and high-throughput imaging that support these innovations. Computational workflows are categorized into multimodal image co-registration, 3D histoarchitecture reconstruction, multiplexed immunohistochemical correlation, and cross-scale data fusion. These approaches exploit serial section-derived spatial concordance to enhance resolution in microenvironmental and molecular profiling. Despite progress, challenges remain in harmonizing heterogeneous datasets, optimizing large-scale registration, and ensuring interpretability. Future directions include spatial transcriptomics, and applications in developmental biology and neuroscience in AI integration, establishing serial section analytics as central to precision histopathology.