title: Segmentation of subtraction images for the measurement of lesion change in multiple sclerosis.
abstract: OBJECTIVE
  Lesion volume change (LVC) assessment is essential in monitoring MS progression. LVC is usually measured by independently segmenting serial MR imaging examinations. Subtraction imaging has been proposed for improved visualization and characterization of lesion change. We compare segmentation of subtraction images (SSEG) with serial single time-point conventional segmentation (CSEG) by assessing the LVC relationship to brain atrophy and disease duration, as well as scan-rescan reproducibility and annual rates of lesion accrual.
  
  
  METHODS
  Pairs of scans were acquired 1.5 to 4.7 years apart in 21 patients with multiple sclerosis (MS). Scan-rescan MR images were acquired within 30 minutes in 10 patients with MS. LVC was measured with CSEG and SSEG after coregistration and normalization. Coefficient of variation (COV) and Bland-Altman analyses estimated method reproducibility. Spearman rank correlations probed associations between LVC and other measures.
  
  
  RESULTS
  Atrophy rate and net LVC were associated for SSEG (R = -0.446; P < .05) but not when using CSEG (R = -0.180; P = .421). Disease duration did not show an association with net lesion volume change per year measured by CSEG (R = -0.360; P = .11) but showed an inverse correlation with SSEG-derived measurements (R = -0.508; P < .05). Scan-rescan COV was lower for SSEG (0.98% +/- 1.55%) than for CSEG (8.64% +/- 9.91%).
  
  
  CONCLUSIONS
  SSEG unveiled a relationship between T2 LVC and concomitant brain atrophy and demonstrated significantly higher measurement reproducibility. SSEG, a promising tool providing detailed analysis of subtle alterations in lesion size and intensity, may provide critical outcome measures for clinical trials of novel treatments, and may provide further insight into progression patterns in MS.
authors.affiliation: Center for Neurological Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
authors.forename: Y
authors.initials: Y
authors.lastname: Duan
authors.forename: P G
authors.initials: PG
authors.lastname: Hildenbrand
authors.forename: M P
authors.initials: MP
authors.lastname: Sampat
authors.forename: D F
authors.initials: DF
authors.lastname: Tate
authors.forename: I
authors.initials: I
authors.lastname: Csapo
authors.forename: B
authors.initials: B
authors.lastname: Moraal
authors.forename: R
authors.initials: R
authors.lastname: Bakshi
authors.forename: F
authors.initials: F
authors.lastname: Barkhof
authors.forename: D S
authors.initials: DS
authors.lastname: Meier
authors.forename: C R G
authors.initials: CR
authors.lastname: Guttmann
mesh_terms: D000328:Adult; D001284:Atrophy / Q000175:diagnosis; D001921:Brain / Q000473:pathology*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009103:Multiple Sclerosis / Q000175:diagnosis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique