A novel segmentation framework dedicated to the follow‐up of fat infiltration in individual muscles of patients with neuromuscular disorders
Autor: | C. Michel, Alexandre Fouré, David Bendahan, Arend Heerschap, Arnaud Le Troter, Linda Heskamp, Marc-Emmanuel Bellemare, Augustin C. Ogier |
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Přispěvatelé: | Images et Modèles (I&M), Laboratoire d'Informatique et Systèmes (LIS), Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Radboud University Medical Center [Nijmegen], Laboratoire Interuniversitaire de Biologie de la Motricité (LIBM ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]) |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Intraclass correlation
Fat infiltration Image registration Muscle volume 030218 nuclear medicine & medical imaging 03 medical and health sciences All institutes and research themes of the Radboud University Medical Center 0302 clinical medicine Urological cancers Radboud Institute for Molecular Life Sciences [Radboudumc 15] Quantitative assessment [INFO.INFO-IM]Computer Science [cs]/Medical Imaging Humans Medicine Radiology Nuclear Medicine and imaging Segmentation ComputingMilieux_MISCELLANEOUS Leg Reproducibility business.industry Reproducibility of Results Image segmentation Magnetic Resonance Imaging Thigh business Algorithms 030217 neurology & neurosurgery Follow-Up Studies Biomedical engineering |
Zdroj: | Magnetic Resonance in Medicine Magnetic Resonance in Medicine, Wiley, 2019, 83 (5), pp.1825-1836. ⟨10.1002/mrm.28030⟩ Magnetic Resonance in Medicine, 83, 1825-1836 Magnetic Resonance in Medicine, 2019, 83 (5), pp.1825-1836. ⟨10.1002/mrm.28030⟩ Magnetic Resonance in Medicine, 83, 5, pp. 1825-1836 |
ISSN: | 0740-3194 1522-2594 |
DOI: | 10.1002/mrm.28030⟩ |
Popis: | International audience; Purpose: To propose a novel segmentation framework that is dedicated to the follow-up of fat infiltration in individual muscles of patients with neuromuscular disorders.Methods: We designed a semi-automatic segmentation pipeline of individual leg muscles in MR images based on automatic propagation through nonlinear registrations of initial delineation in a minimal number of MR slices. This approach has been validated for the segmentation of individual muscles from MRI data sets, acquired over a 10-month period, from thighs and legs in 10 patients with muscular dystrophy. The robustness of the framework was evaluated using conventional metrics related to muscle volume and clinical metrics related to fat infiltration.Results: High accuracy of the semi-automatic segmentation (mean Dice similarity coefficient higher than 0.89) was reported. The provided method has excellent reliability regarding the reproducibility of the fat fraction estimation, with an average intraclass correlation coefficient score of 0.99. Furthermore, the present segmentation framework was determined to be more reliable than the intra-expert performance, which had an average intraclass correlation coefficient of 0.93.Conclusion: The proposed framework of segmentation can successfully provide an effective and reliable tool for accurate follow-up of any MRI biomarkers in neuromuscular disorders. This method could assist the quantitative assessment of muscular changes occurring in such diseases. |
Databáze: | OpenAIRE |
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