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Related Experiment Video

Updated: Mar 16, 2026

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
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Practical AI-based cell extraction and spatial statistics for large 3D bone marrow tissue images.

George Adams1, Floriane S Tissot2, Chang Liu3

  • 1Department of Life Sciences, Sir Alexander Fleming Building, Imperial College London, London SW7 2AZ, UK; Centre for Haematology, Department of Immunology and Inflammation, Imperial College London, London W12 0NN, UK.

Cell Reports Methods
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed PACESS, a computational workflow for analyzing bone marrow (BM) architecture. This tool reveals how distinct leukemic cell clusters create unique neighborhoods within the BM, offering new insights into spatial organization.

Keywords:
3DCP: computational biologyCP: systems biologybone marrow tissue architecturecell clustersconvolutional neural networkleukemialymphocytesmegakaryocytesspatial statisticsthick histological preparationstissue clearing

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Area of Science:

  • Hematology
  • Computational Biology
  • Bioinformatics

Background:

  • The spatial organization of hematopoietic cells within bone marrow (BM) is not well understood, despite advances in microscopy.
  • Existing methods for analyzing complex BM imaging datasets are limited in accuracy and scalability.

Purpose of the Study:

  • To present PACESS, a novel computational workflow designed for the analysis of bone marrow architecture.
  • To investigate the spatial organization of specific cell types, including T cells, megakaryocytes, and leukemic cells, within the BM.

Main Methods:

  • PACESS integrates convolutional neural networks for 2D cell detection and classification.
  • It employs automated 3D extrapolation, spatial statistical analyses for tissue region definition, and logistic regression for cell-type dependency assessment.

Main Results:

  • PACESS successfully analyzed the spatial organization of T cells, megakaryocytes, and leukemic cells.
  • Distinct leukemic cell clusters were found to generate previously unrecognized neighborhoods within the BM cavity.

Conclusions:

  • PACESS provides a powerful and scalable computational tool for dissecting bone marrow architecture.
  • The findings highlight the complex spatial interactions and neighborhood formation within the BM, particularly in the context of leukemia.