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Updated: Mar 3, 2026
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An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells
Published on: July 15, 2015
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Associations between CT Radiomics Analyses and Hematopoietic Cell Mobilization in Patients with Multiple Myeloma: An
Jakob Leonhardi1, Tihomir Dermendzhiev1, Enrica Bach2,3
1Department of Diagnostic and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany.
Summary
Computed tomography (CT) radiomics can predict stem-cell collection yield in multiple myeloma (MM) patients. Texture analysis of CT scans identified key features correlating with CD34+ cell counts, aiding treatment planning.
Area of Science:
- Medical Imaging
- Hematology
- Oncology
Background:
- Peripheral stem-cell collection is crucial for high-dose therapy in multiple myeloma (MM).
- Radiomics offers quantitative tissue characterization from medical imaging.
- Identifying prognostic factors for stem-cell mobilization is essential for MM treatment.
Purpose of the Study:
- To investigate the utility of computed tomography (CT) radiomics parameters in predicting stem-cell mobilization in MM patients.
- To identify imaging-based prognostic factors for successful stem-cell collection.
Main Methods:
- Retrospective analysis of 34 MM patients undergoing stem-cell mobilization between May 2020 and September 2022.
- Whole-body CT scans obtained before chemomobilization were analyzed using texture analysis.
- Statistical analysis correlated CT radiomics features with CD34+ cell counts.
Main Results:
- Three CT texture features significantly correlated with peripheral CD34+ cell counts.
- "S(1,0)AngScMom" and "WavEnHH_s-5" showed positive correlations (p=0.031, p=0.012).
- "Teta1" demonstrated an inverse correlation (p=0.031), with an AUC of 0.77 for the predictive model.
Conclusions:
- CT radiomics features can effectively predict apheresis yield in MM patients undergoing stem-cell mobilization.
- The identified radiomics signature shows potential for clinical application.
- Further validation studies are required to confirm predictive accuracy in routine clinical practice.
