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Haueise, T. ; Stefan, N. ; Schulz, T.J.* ; Schick, F. ; Birkenfeld, A.L. ; Machann, J.

Automated shape-independent assessment of the spatial distribution of proton density fat fraction in vertebral bone marrow.

Z. Med. Phys., DOI: 10.1016/j.zemedi.2022.12.004 (2023)
Verlagsversion DOI PMC
Open Access Gold
This work proposes a method for automatic standardized assessment of bone marrow volume and spatial distribution of the proton density fat fraction (PDFF) in vertebral bodies. Intra- and interindividual variability in size and shape of vertebral bodies is a challenge for comparable interindividual evaluation and monitoring of changes in the composition and distribution of bone marrow due to aging and/or intervention. Based on deep learning image segmentation, bone marrow PDFF of single vertebral bodies is mapped to a cylindrical template and corrected for the inclination with respect to the horizontal plane. The proposed technique was applied and tested in a cohort of 60 healthy (30 males, 30 females) individuals. Obtained bone marrow volumes and mean PDFF values are comparable to former manual and (semi-)automatic approaches. Moreover, the proposed method allows shape-independent characterization of the spatial PDFF distribution inside vertebral bodies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Bone Marrow ; Cse Mri ; Deep Learning ; Pdff ; Segmentation
Sprache englisch
Veröffentlichungsjahr 2023
HGF-Berichtsjahr 2023
ISSN (print) / ISBN 0939-3889
e-ISSN 1876-4436
Zeitschrift Zeitschrift für Medizinische Physik
Verlag Elsevier
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Diabetes Research and Metabolic Diseases (IDM)
POF Topic(s) 90000 - German Center for Diabetes Research
Forschungsfeld(er) Helmholtz Diabetes Center
PSP-Element(e) G-502400-001
DOI 10.1016/j.zemedi.2022.12.004
Scopus ID 85147305869
PubMed ID 36725478
Erfassungsdatum 2023-02-10
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