Advanced automated model for robust bone marrow segmentation in whole-body MRI
Rationale and Objectives - To establish an advanced automated bone marrow (BM) segmentation model on whole-body (WB-)MRI in monoclonal plasma cell disorders (MPCD), and to demonstrate its robust performance on multicenter datasets with severe myeloma-related pathologies. - Materials and Methods - Th...
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| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
May 2025
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| In: |
Academic radiology
Year: 2025, Volume: 32, Issue: 5, Pages: 2824-2835 |
| ISSN: | 1878-4046 |
| DOI: | 10.1016/j.acra.2024.12.060 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.acra.2024.12.060 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S1076633224010481 
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| Author Notes: | Fabian Bauer, Jessica Kächele, Juliane Bernhard, Marina Hajiyianni, Niels Weinhold, Sandra Sauer, Martin Grözinger, Marc-Steffen Raab, Elias K. Mai, Tim F. Weber, Hartmut Goldschmidt, Heinz-Peter Schlemmer, Klaus Maier-Hein, Stefan Delorme, Peter Neher, Markus Wennmann |
| Summary: | Rationale and Objectives - To establish an advanced automated bone marrow (BM) segmentation model on whole-body (WB-)MRI in monoclonal plasma cell disorders (MPCD), and to demonstrate its robust performance on multicenter datasets with severe myeloma-related pathologies. - Materials and Methods - The study cohort comprised multi-vendor, multi-protocol imaging data acquired with varying field strength across 8 different centers. In total, 210 WB-MRIs of 207 MPCD patients were included. An nnU-Net algorithm was established for segmenting the individual bone marrow spaces (BMS) of the spine, pelvis, humeri and femora (advanced segmentation model). For this task, 186 T1-weighted (T1w) WB-MRIs from center 1 were used in the training set. Test sets included 12 T1w WB-MRIs from center 2 (I) and 9 T1w WB-MRIs from centers 3-8 (II). Example cases were included to showcase segmentation performance on T1w WB-MRIs with extensive tumor load. The segmentation accuracy of the advanced segmentation model was compared to a prior established basic segmentation model by calculating Dice scores and using the Wilcoxon signed-rank test. - Results - The mean Dice score on the individual BMS was 0.89±0.13 (test set I) and 0.88±0.11 (test set II), significantly higher than the Dice scores of a prior basic model (p<0.05). Dice scores for the BMS of the individual bones ranged from 0.77 to 0.96 (test set I), and 0.81 to 0.95 (test set II). BM altered by myeloma-relevant pathologies, artifacts or low imaging quality was precisely segmented. - Conclusion - The advanced model performed reliable, automated segmentations, even on heterogeneously acquired multicenter WB-MRIs with severe pathologies. |
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| Item Description: | Online verfügbar: 22. Januar 2025, Artikelversion: 19. April 2025 Gesehen am 04.11.2025 |
| Physical Description: | Online Resource |
| ISSN: | 1878-4046 |
| DOI: | 10.1016/j.acra.2024.12.060 |