Methodological innovations in high-plex spatial imaging for single-cell immune profiling

High-plex spatial imaging has emerged as a transformative field within immunology, enabling researchers to visualize the immune landscape at single-cell resolution while preserving tissue context. Techniques such as imaging mass cytometry (IMC), multiplexed ion beam imaging (MIBI), and CODEX have drastically expanded the multiplexing capacity of protein detection, allowing simultaneous visualization of dozens to hundreds of immune markers. Despite these remarkable advances, several methodological bottlenecks persist. Challenges including accurate cell segmentation, signal spillover, inconsistent antibody validation, and lack of cross-platform standardization continue to hinder reproducibility and inter-study comparability. Current studies have demonstrated the potential of spatial imaging for deciphering immune architecture and cell–cell interactions, yet a systematic, validated approach for achieving reliable single-cell resolution across technologies remains unavailable. Addressing these gaps is essential for integrating spatial insights with single-cell omics data and achieving robust functional interpretations of immune responses.This Research Topic aims to accelerate methodological development, optimization, and benchmarking of high-plex spatial imaging for precise single-cell immunophenotyping. Specifically, it seeks to enhance the reproducibility and resolution of spatial imaging platforms, create standardized frameworks for antibody panel design and signal quantification, and foster interoperability between imaging and omics-based datasets. Contributions may include algorithmic advancements in cell segmentation, innovations in antibody validation and staining chemistry, improved correction strategies for signal spillover, and integrative computational tools that bridge spatial and single-cell modalities. Studies combining spatial imaging with single-cell RNA sequencing or proteomics for cross-validation and comparative benchmarking are particularly encouraged. By emphasizing methodological transparency, reproducibility, and validation, this Research Topic will establish robust frameworks for spatially resolved immune profiling at single-cell granularity.This Research Topic will cover studies focused on the design, validation, and integration of technologies that capture immune complexity through high-dimensional spatial imaging. To gather further insights in methodological and computational frontiers of single-cell spatial immunology, we welcome articles addressing, but not limited to, the following themes:• Development and optimization of spatial imaging platforms (IMC, MIBI, CODEX, multiplex IF)• Advances in single-cell resolution and segmentation for spatial data• Antibody validation, multiplex panel design, and staining chemistry for spatial immunoprofiling• Quantitative correction methods, including signal deconvolution, denoising, and intensity normalization• Integrative approaches linking spatial imaging with single-cell omics (scRNA-seq, proteomics)• Cross-platform benchmarking and standardization of high-plex datasetsInstrumentation improvements, acquisition pipelines, and workflow automation• Quality control, reproducibility, and data sharing in single-cell spatial imagingManuscript types: Original Research Articles, Methods Papers, and Technology Reports. Reviews will also be considered if focused on comparative methodological analyses or benchmarking.Please note that Dr. Kazuma Kiyotani is a scientific advisor to Cancer Precision Medicine, Inc. Topic editors: Koji Ueda, Kazuma Kiyotani Source: https://www.frontiersin.org/research-topics/81022/methodological-innovations-in-high-plex-spatial-imaging-for-single-cell-immune-profiling