Improved contrast in multispectral phase images derived from magnetic resonance exams of multiple sclerosis patients

J. R. Mitchell, B. K. Rutt

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We describe a method to extract data from multispectral MR exams of patients with Multiple Sclerosis (MS). The technique produces images of "spectral phase" (SP) relative to a reference tissue. SP images allow retrospective suppression of signal in the reference tissue, while maintaining high spatial resolution. Image quality in SP images was determined from MR exams of 5 MS patients selected at random from a clinical trial underway at our institute. Exams consisting of proton density weighted (PDw), T2 weighted (T2w), T1 weighted (T1w), and gadolinium-DTPA enhanced T1w (GAD) images were acquired from each patient. The MR exams were corrected for intensity nonuniformity, then filtered with an algorithm based upon anisotropic diffusion, to reduce noise. Principal component (PC) images and SP images relative to cerebrospinal fluid (SPCSF), normal appearing white matter (SPNAWM), gray matter (SPGM), and temporalis muscle (SPMUS) were then calculated. Contrast between tissues and MS lesions in the MR and derived images was then determined by measuring the signal-difference-to-noise ratio (dSNR) between tissues. Our new SP images provided better tissue contrast than the original MR, filtered MR, and PC images. Contrast improved between CSF and NAWM (from 19.5 to 56), CSF and GM (from 15 to 36), GM and NAWM (from 8 to 14), MS lesions and CSF (from 16 to 35), and between MS lesions and NAWM (from 24 to 47). (Maximum contrast in the original MR images compared to maximum contrast in the SP images.) The additional contrast in SP images may aid the quantification and analysis of lesion activity in MR exams of MS patients.

Original languageEnglish (US)
Pages (from-to)727-735
Number of pages9
JournalMedical physics
Volume29
Issue number5
DOIs
StatePublished - 2002

Keywords

  • Feature space
  • Image processing
  • MRI
  • Multiple sclerosis
  • Multispectral analysis
  • Principal component analysis

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

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