MIAAIM Key Resource Table for Multi-Omics Tissue Image Alignment

Joshua M. Hess published a key resource table for the MIAAIM framework on figshare in May 2026. The 17.5 KB XLS file supports the alignment and analysis of multi-omics tissue imaging data from platforms like histological staining, imaging mass cytometry, and mass spectrometry imaging. The framework was validated on a diabetic foot ulcer biopsy and prostate cancer tissue microarrays.

Use Cases

• Aligning multi-modal tissue images based on histological staining, imaging mass cytometry, and mass spectrometry imaging data mentioned in the description
• Identifying unbiased molecular phenotypes of immune cells based on high-resolution targeted immunodetection correlations described in the framework
• Classifying adjacent tumor grades in tissue microarrays based on spatial features generated from segmented cells across multiple imaging modalities
• Constructing multimodal tissue imaging datasets for analyzing complex tissue states in a disease-agnostic manner as described for MIAAIM

Strengths

• Framework validated on a large diabetic foot ulcer biopsy and multi-core prostate cancer tissue microarrays
• Reported over 90% of classification signal for prostate cancer tumor grades sourced from spatial features
• Dataset is openly licensed under CC-BY-4.0

Limitations

• Dataset is very small at 17.5 KB, indicating limited scope
• Row count and column-level documentation are absent; field semantics must be inferred after download
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

Joshua M. Hess via figshare

Collection Method

Likely generated as a supplementary resource for the MIAAIM computational framework.

Freshness

Last updated 2026-05-26 18:00:35; freshness should be verified