title: Tissue-specific imaging is a robust methodology to differentiate in vivo T1 black holes with advanced multiple sclerosis-induced damage.
abstract: OBJECTIVE
  Brains of patients with multiple sclerosis (MS) characteristically have "black holes" (BHs), hypointense lesions on T1-weighted (T1W) spin-echo (SE) images. Although conventional MR imaging can disclose chronic BHs (CBHs), it cannot stage the degree of their pathologic condition. Tissue-specific imaging (TSI), a recently introduced MR imaging technique, allows selective visualization of white matter (WM), gray matter (GM), and CSF on the basis of T1 values of classes of tissue. We investigated the ability of TSI-CSF to separate CBHs with longer T1 values, which likely represent lesions containing higher levels of destruction and unbound water.
  
  
  METHODS
  Eighteen patients with MS, who had already undergone MR imaging twice (24 months apart) on a 1.5T scanner, underwent a 3T MR imaging examination. Images acquired at 1.5T included sequences of precontrast and postcontrast T1W SE, T2-weighted (T2W) SE, and magnetization transfer (MT). Sequences obtained at 3T included precontrast and postcontrast T1W SE, T2W SE, T1 inversion recovery prepared fast spoiled gradient recalled-echo (IR-FSPGR) and TSI. A BH on the 3T-IR-FSPGR was defined as a CBH if seen as a hypointense, nonenhancing lesion with a corresponding T2 abnormality for at least 24 months. CBHs were separated into 2 groups: those visible as hyperintensities on TSI-CSF (group A), and those not appearing on the TSI-CSF (group B).
  
  
  RESULTS
  Mean MT ratios of group-A lesions (0.22 +/- 0.06, 0.13-0.35) were lower (F(1,13) = 60.39; P < .0001) than those of group-B lesions (0.32 +/- 0.03, 0.27-0.36).
  
  
  CONCLUSIONS
  Group-A lesions had more advanced tissue damage; thus, TSI is a potentially valuable method for qualitative and objective identification.
authors.affiliation: Neuroimmunology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892-1400, USA.
authors.forename: M
authors.initials: M
authors.lastname: Riva
authors.forename: V N
authors.initials: VN
authors.lastname: Ikonomidou
authors.forename: J J
authors.initials: JJ
authors.lastname: Ostuni
authors.forename: P
authors.initials: P
authors.lastname: van Gelderen
authors.forename: S
authors.initials: S
authors.lastname: Auh
authors.forename: J M
authors.initials: JM
authors.lastname: Ohayon
authors.forename: F
authors.initials: F
authors.lastname: Tovar-Moll
authors.forename: N D
authors.initials: ND
authors.lastname: Richert
authors.forename: J H
authors.initials: JH
authors.lastname: Duyn
authors.forename: F
authors.initials: F
authors.lastname: Bagnato
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity