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Related Experiment Video

Updated: Jun 5, 2026

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

Multi-Scale Tri-Modal Histology Dataset Integrating Tumor Morphology, Immune Patterns, and Clinical Outcomes.

Kyeong Joo Jung1, Jianwei Qiu2, Sanghee Cho2

  • 1Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio, 43210, USA.

Biorxiv : the Preprint Server for Biology
|June 4, 2026
PubMed
Summary

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We introduce Prostate-TriMod, a new dataset integrating prostate cancer (PCa) histology, immune patterns, and clinical data. This resource aids AI development for better prognostic assessment by linking morphology and immune context to outcomes.

Area of Science:

  • Computational pathology
  • Medical imaging analysis
  • Cancer research

Background:

  • Accurate prostate cancer (PCa) prognosis requires integrating tissue morphology and immune microenvironment data.
  • Existing datasets often lack multi-modal integration for comprehensive analysis.

Purpose of the Study:

  • To present Prostate-TriMod, a novel tri-modal histology dataset for PCa.
  • To enable advanced AI development for prognostic assessment by linking morphology, immune context, and clinical outcomes.

Main Methods:

  • Generation of a tri-modal dataset using Cell DIVE™ multiplexed imaging.
  • Inclusion of multiscale virtual H&E tiles for morphology.
  • Integration of spatial tissue maps (TOPAZ, CAT models) and text captions from single-cell data.

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Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment
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Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Published on: June 2, 2023

Related Experiment Videos

Last Updated: Jun 5, 2026

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment
06:05

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Published on: June 2, 2023

  • Comprehensive clinical annotations including Grade Groups and biochemical recurrence (BCR) status.

    • Main Results:

    • Prostate-TriMod provides high-fidelity alignment between visual features, spatial maps, and textual descriptions.
    • The dataset integrates high-resolution morphology, spatial tissue organization, and immune infiltration patterns.
    • Clinical outcomes such as Grade Groups and BCR status are comprehensively annotated.

    Conclusions:

    • Prostate-TriMod is a valuable resource for multimodal AI development in prostate cancer research.
    • Facilitates multimodal representation learning, spatial analysis, and benchmarking studies.
    • Supports linking histological morphology and immune context to clinical outcomes for improved PCa prognosis.