title: Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.
abstract: OBJECTIVE
  Atlas-based segmentation is a powerful method for automatic structural segmentation of several sub-structures in many organs. However, such an approach has been very scarcely used in the context of muscle segmentation, and so far no study has assessed such a method for the automatic delineation of individual muscles of the quadriceps femoris (QF). In the present study, we have evaluated a fully automated multi-atlas method and a semi-automated single-atlas method for the segmentation and volume quantification of the four muscles of the QF and for the QF as a whole.
  
  
  METHODS
  The study was conducted in 32 young healthy males, using high-resolution magnetic resonance images (MRI) of the thigh. The multi-atlas-based segmentation method was conducted in 25 subjects. Different non-linear registration approaches based on free-form deformable (FFD) and symmetric diffeomorphic normalization algorithms (SyN) were assessed. Optimal parameters of two fusion methods, i.e., STAPLE and STEPS, were determined on the basis of the highest Dice similarity index (DSI) considering manual segmentation (MSeg) as the ground truth. Validation and reproducibility of this pipeline were determined using another MRI dataset recorded in seven healthy male subjects on the basis of additional metrics such as the muscle volume similarity values, intraclass coefficient, and coefficient of variation. Both non-linear registration methods (FFD and SyN) were also evaluated as part of a single-atlas strategy in order to assess longitudinal muscle volume measurements. The multi- and the single-atlas approaches were compared for the segmentation and the volume quantification of the four muscles of the QF and for the QF as a whole.
  
  
  RESULTS
  Considering each muscle of the QF, the DSI of the multi-atlas-based approach was high 0.87 ± 0.11 and the best results were obtained with the combination of two deformation fields resulting from the SyN registration method and the STEPS fusion algorithm. The optimal variables for FFD and SyN registration methods were four templates and a kernel standard deviation ranging between 5 and 8. The segmentation process using a single-atlas-based method was more robust with DSI values higher than 0.9. From the vantage of muscle volume measurements, the multi-atlas-based strategy provided acceptable results regarding the QF muscle as a whole but highly variable results regarding individual muscle. On the contrary, the performance of the single-atlas-based pipeline for individual muscles was highly comparable to the MSeg, thereby indicating that this method would be adequate for longitudinal tracking of muscle volume changes in healthy subjects.
  
  
  CONCLUSIONS
  In the present study, we demonstrated that both multi-atlas and single-atlas approaches were relevant for the segmentation of individual muscles of the QF in healthy subjects. Considering muscle volume measurements, the single-atlas method provided promising perspectives regarding longitudinal quantification of individual muscle volumes.
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France. arnaud.le-troter@univ-amu.fr.|APHM, CHU Timone, Pôle imagerie médicale, CEMEREM, 13005, Marseille, France. arnaud.le-troter@univ-amu.fr.
authors.forename: Arnaud
authors.identifier: http://orcid.org/0000-0002-7897-9672
authors.initials: A
authors.lastname: Le Troter
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France.|APHM, CHU Timone, Pôle imagerie médicale, CEMEREM, 13005, Marseille, France.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Fouré
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France.|APHM, CHU Timone, Pôle imagerie médicale, CEMEREM, 13005, Marseille, France.
authors.forename: Maxime
authors.initials: M
authors.lastname: Guye
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France.|APHM, CHU Timone, Pôle imagerie médicale, CEMEREM, 13005, Marseille, France.
authors.forename: Sylviane
authors.initials: S
authors.lastname: Confort-Gouny
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France.|APHM, CHU Sainte-Marguerite, Département de Rhumatologie, 13009, Marseille, France.
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Mattei
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France.|APHM, CHU Timone, Pôle imagerie médicale, CEMEREM, 13005, Marseille, France.
authors.forename: Julien
authors.initials: J
authors.lastname: Gondin
authors.affiliation: APHM, CHU Timone, Centre de Référence des Maladies Neuromusculaires et de la SLA, 13005, Marseille, France.
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Salort-Campana
authors.affiliation: Aix Marseille Université, CNRS, CRMBM UMR 7339, 13385, Marseille, France.|APHM, CHU Timone, Pôle imagerie médicale, CEMEREM, 13005, Marseille, France.
authors.forename: David
authors.initials: D
authors.lastname: Bendahan
mesh_terms: D000328:Adult; D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009929:Organ Size; D010363:Pattern Recognition, Automated / Q000379:methods*; D052097:Quadriceps Muscle / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D055815:Young Adult
keywords: Fusion; Individual muscle volume measurements; MRI; Multi-atlas-based segmentation; Non-linear registration; Quadriceps femoris muscle