Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2026
Associations between CT Radiomics Analyses and Hematopoietic Cell Mobilization in Patients with Multiple Myeloma: An Exploratory Analysis.
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Leonhardi Jakob, Dermendzhiev Tihomir, Bach Enrica, Brückner Mandy, Wang Song-Yau, Franke Georg-Nikolaus, Jentzsch Madlen, Heyn Simone, Metzeler Klaus H, Platzbecker Uwe, Denecke Timm, Merz Maximilan, Vučinić Vladan, Meyer Hans-Jonas
Аннотация
INTRODUCTION: Peripheral stem-cell collection is an essential step/prerequisite for high-dose treatment of patients with multiple myeloma (MM). Radiomics provides numerous analytic parameters from imaging modalities and can characterize tissues in a quantitative manner. The present study used radiomics derived parameters based on computed tomography (CT) images to identify prognostic factors for stem-cell mobilization in patients with MM.
METHODS: Between May 2020 and September 2022 all patients who had undergone quadruplet induction therapy, were scheduled for stem-cell mobilization in preparation for autologous stem cell transplantation, and had CT scans prior to chemomobilization were retrospectively analyzed. Total 34 patients (25 males [74%], median age 60 ± 8 years) were analyzed. Whole-body CT images routinely obtained before the start of mobilization were analyzed with texture analysis.
RESULTS: Of the investigated CT radiomics features, three CT textures were associated with the concentration of CD34+ cell count in peripheral blood at begin of apheresis. The second-order texture feature "S(1,0)AngScMom" and the wavelet transform feature "WavEnHH_s-5" were positively correlated (r = 0.375, p = 0.031 and r = 0.432, p = 0.012, respectively), whereas the autoregressive feature "Teta1" was inversely correlated (r = -0.375, p = 0.031). The significant CT radiomics features were used to build a model with a good diagnostic accuracy with an area under the curve of 0.77 (95% CI: 0.59-0.96).
CONCLUSION: CT radiomics features can predict apheresis yield in patients undergoing hematopoietic cell mobilization in patients with MM. Further analyses are needed to validate the identified radiomics signature in clinical routine and to test the predictive abilities.
METHODS: Between May 2020 and September 2022 all patients who had undergone quadruplet induction therapy, were scheduled for stem-cell mobilization in preparation for autologous stem cell transplantation, and had CT scans prior to chemomobilization were retrospectively analyzed. Total 34 patients (25 males [74%], median age 60 ± 8 years) were analyzed. Whole-body CT images routinely obtained before the start of mobilization were analyzed with texture analysis.
RESULTS: Of the investigated CT radiomics features, three CT textures were associated with the concentration of CD34+ cell count in peripheral blood at begin of apheresis. The second-order texture feature "S(1,0)AngScMom" and the wavelet transform feature "WavEnHH_s-5" were positively correlated (r = 0.375, p = 0.031 and r = 0.432, p = 0.012, respectively), whereas the autoregressive feature "Teta1" was inversely correlated (r = -0.375, p = 0.031). The significant CT radiomics features were used to build a model with a good diagnostic accuracy with an area under the curve of 0.77 (95% CI: 0.59-0.96).
CONCLUSION: CT radiomics features can predict apheresis yield in patients undergoing hematopoietic cell mobilization in patients with MM. Further analyses are needed to validate the identified radiomics signature in clinical routine and to test the predictive abilities.