title: Automated determination of brain parenchymal fraction in multiple sclerosis.
abstract: OBJECTIVE
  Brain atrophy is a manifestation of tissue damage in MS. Reduction in brain parenchymal fraction is an accepted marker of brain atrophy. In this study, the approach of synthetic tissue mapping was applied, in which brain parenchymal fraction was automatically calculated based on absolute quantification of the tissue relaxation rates R1 and R2 and the proton attenuation.
  
  
  METHODS
  The BPF values of 99 patients with MS and 35 control subjects were determined by using SyMap and tested in relationship to clinical variables. A subset of 5 patients with MS and 5 control subjects were also analyzed with a manual segmentation technique as a reference. Reproducibility of SyMap was assessed in a separate group of 6 healthy subjects, each scanned 6 consecutive times.
  
  
  RESULTS
  Patients with MS had significantly lower BPF (0.852 ± 0.0041, mean ± SE) compared with control subjects (0.890 ± 0.0040). Significant linear relationships between BPF and age, disease duration, and Expanded Disability Status Scale scores were observed (P < .001). A strong correlation existed between SyMap and the reference method (r = 0.96; P < .001) with no significant difference in mean BPF. Coefficient of variation of repeated SyMap BPF measurements was 0.45%. Scan time was <6 minutes, and postprocessing time was <2 minutes.
  
  
  CONCLUSIONS
  SyMap is a valid and reproducible method for determining BPF in MS within a clinically acceptable scan time and postprocessing time. Results are highly congruent with those described using other methods and show high agreement with the manual reference method.
authors.affiliation: Department of Pharmacology and Clinical Neuroscience, Section of Neuroscience, Umeå University, Umeå, Sweden. mattias.vagberg@neuro.umu.se
authors.forename: M
authors.initials: M
authors.lastname: Vågberg
authors.forename: T
authors.initials: T
authors.lastname: Lindqvist
authors.forename: K
authors.initials: K
authors.lastname: Ambarki
authors.forename: J B M
authors.initials: JB
authors.lastname: Warntjes
authors.forename: P
authors.initials: P
authors.lastname: Sundström
authors.forename: R
authors.initials: R
authors.lastname: Birgander
authors.forename: A
authors.initials: A
authors.lastname: Svenningsson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D001284:Atrophy / Q000473:pathology; D001921:Brain / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult