title: An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre reproducibility based on two large community databases.
abstract: BACKGROUND
  An automated procedure for the detection, quantification, localization and statistical mapping of white matter hyperintensities (WMH) on T2-weighted magnetic resonance (MR) images is presented and validated based on the results of a between-centre reproducibility study.
  
  
  METHODS
  The first step is the identification of white matter (WM) tissue using a multispectral (T1, T2, PD) segmentation. In a second step, WMH are identified within the WM tissue by segmenting T2 images, isolating two different classes of WMH voxels - low- and high-contrast WMH voxels, respectively. The reliability of the whole procedure was assessed by applying it to the analysis of two large MR imaging databases (n = 650 and n= 710, respectively) of healthy elderly subjects matched for demographic characteristics.
  
  
  RESULTS
  Average overall WMH load and spatial distribution were found to be similar in the two samples, (1.81 and 1.79% of the WM volume, respectively). White matter hyperintensity load was found to be significantly associated with both age and high blood pressure, with similar effects in both samples. With specific reference to the 650 subject cohort, we also found that WMH load provided by this automated procedure was significantly associated with visual grading of the severity of WMH, as assessed by a trained neurologist.
  
  
  CONCLUSIONS
  The results show that this method is sensitive, well correlated with semi-quantitative visual rating and highly reproducible.
authors.affiliation: Centre d'Imagerie-Neurosciences et Applications aux Pathologies, CI-NAPS, CNRS, CEA, Université de Caen/Université Paris Descartes, GIP Cyceron, Boulevard Becquerel, BP 5229, 14074, Caen, France.
authors.forename: Pauline
authors.initials: P
authors.lastname: Maillard
authors.forename: Nicolas
authors.initials: N
authors.lastname: Delcroix
authors.forename: Fabrice
authors.initials: F
authors.lastname: Crivello
authors.forename: Carole
authors.initials: C
authors.lastname: Dufouil
authors.forename: Sebastien
authors.initials: S
authors.lastname: Gicquel
authors.forename: Marc
authors.initials: M
authors.lastname: Joliot
authors.forename: Nathalie
authors.initials: N
authors.lastname: Tzourio-Mazoyer
authors.forename: Annick
authors.initials: A
authors.lastname: Alpérovitch
authors.forename: Christophe
authors.initials: C
authors.lastname: Tzourio
authors.forename: Bernard
authors.initials: B
authors.lastname: Mazoyer
mesh_terms: D000368:Aged; D000465:Algorithms; D001927:Brain Diseases / Q000175:diagnosis*; D002545:Brain Ischemia / Q000175:diagnosis; D002908:Chronic Disease; D003072:Cognition Disorders / Q000175:diagnosis; D003711:Demyelinating Diseases / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008609:Mental Status Schedule; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D015588:Observer Variation; D012016:Reference Values; D015203:Reproducibility of Results; D012307:Risk Factors; D012984:Software