Combining deep learning and radiomics for automated, objective, comprehensive bone marrow characterization from whole-body MRI: a multicentric feasibility study
Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole BM. Reading of such whole-body scans is time-consuming, and yet radiologists can transfer only a small fraction of the information of the imagi...
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
November 2022
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| In: |
Investigative radiology
Year: 2022, Jahrgang: 57, Heft: 11, Pages: 752-763 |
| ISSN: | 1536-0210 |
| DOI: | 10.1097/RLI.0000000000000891 |
| Online-Zugang: | Resolving-System, lizenzpflichtig, Volltext: https://doi.org/10.1097/RLI.0000000000000891 Verlag, lizenzpflichtig, Volltext: https://journals.lww.com/investigativeradiology/Abstract/2022/11000/Combining_Deep_Learning_and_Radiomics_for.6.aspx |
| Verfasserangaben: | Markus Wennmann, André Klein, Fabian Bauer, Jiri Chmelik, Martin Grözinger, Charlotte Uhlenbrock, Jakob Lochner, Tobias Nonnenmacher, Lukas Thomas Rotkopf, Sandra Sauer, Thomas Hielscher, Michael Götz, Ralf Omar Floca, Peter Neher, David Bonekamp, Jens Hillengass, Jens Kleesiek, Niels Weinhold, Tim Frederik Weber, Hartmut Goldschmidt, Stefan Delorme, Klaus Maier-Hein, Heinz-Peter Schlemmer |
| Zusammenfassung: | Disseminated bone marrow (BM) involvement is frequent in multiple myeloma (MM). Whole-body magnetic resonance imaging (wb-MRI) enables to evaluate the whole BM. Reading of such whole-body scans is time-consuming, and yet radiologists can transfer only a small fraction of the information of the imaging data set to the report. This limits the influence that imaging can have on clinical decision-making and in research toward precision oncology. The objective of this feasibility study was to implement a concept for automatic, comprehensive characterization of the BM from wb-MRI, by automatic BM segmentation and subsequent radiomics analysis of 30 different BM spaces (BMS). |
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| Beschreibung: | Gesehen am 03.01.2023 |
| Beschreibung: | Online Resource |
| ISSN: | 1536-0210 |
| DOI: | 10.1097/RLI.0000000000000891 |