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Related Experiment Video

Updated: Sep 19, 2025

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells
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Advanced Quantification Pipeline Reveals New Spatial and Temporal Tumor Characteristics in Preclinical Multiple

Zhixin Sun1,2, Jacqueline Godbe2, Alexander Zheleznyak2

  • 1Department of Electrical and Systems Engineering, Washington University in St. Louis, Saint Louis, Missouri, USA.

Research Square
|June 5, 2025
PubMed
Summary
This summary is machine-generated.

A new semi-automated PET/CT pipeline precisely quantifies multiple myeloma (MM) tumor burden in mice. This method overcomes manual analysis limitations, revealing joint-specific tropism and sex-based differences in bone loss.

Keywords:
Bone SegmentationMultiple Myeloma (MM) ImagingPET/CT QuantificationSkeletal Lesions

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Area of Science:

  • * Preclinical imaging
  • * Cancer biology
  • * Medical physics

Background:

  • * Manual quantification of longitudinal small animal PET/CT for multiple myeloma (MM) is limited by annotator bias, excretion artifacts, and registration errors.
  • * Developing a semi-automated pipeline can improve the characterization of tumor biology in MM.
  • * Targeting regions of interest (ROIs) within the mouse skeleton, including complex areas like the pelvis, is crucial for accurate analysis.

Purpose of the Study:

  • * To develop and validate a semi-automated PET/CT quantification pipeline for MM in preclinical models.
  • * To achieve sub-organ spatial resolution for improved tumor characterization.
  • * To analyze tumor distribution, burden, and bone involvement in a longitudinal study.

Main Methods:

  • * An Attention U-Net model was trained to segment specific skeletal regions (spine, pelvis, sacrum, femurs) from CT slices.
  • * A custom algorithm was used to mask physiological excretion spillover signals.
  • * PCA-based projection mapped tumor distribution, and quantification metrics (SUVmean, SUVmax, HU) were calculated.

Main Results:

  • * Tumor burden was preferentially localized to skeletal regions near joints.
  • * Precise CT-based alignment (DICE = 0.966 ± 0.005) enabled detection of early disease progression.
  • * Significant increases in tumor uptake (SUVmean) were observed across multiple skeletal sites by day 18.
  • * Female mice exhibited greater bone loss near the hip joint at later stages, indicated by significant HUmean reductions.

Conclusions:

  • * The developed pipeline enables reproducible and anatomically precise quantification of MM progression.
  • * It accurately identifies region-specific trends, including joint tropism and sex-based differences.
  • * This approach mitigates common challenges in manual analysis, enhancing the evaluation of tumor biology and treatment response in bone-involved cancer models.