A computerized MRI biomarker quantification scheme for a canine model of Duchenne muscular dystrophy

Jiahui Wang, Zheng Fan, Krista Vandenborne, Glenn Walter, Yael Shiloh-Malawsky, Hongyu An, Joe N. Kornegay, Martin A. Styner

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Purpose Golden retriever muscular dystrophy (GRMD) is a widely used canine model of Duchenne muscular dystrophy (DMD). Recent studies have shown that magnetic resonance imaging (MRI) can be used to non-invasively detect consistent changes in both DMD and GRMD. In this paper, we propose a semiautomated system to quantify MRI biomarkers of GRMD. Methods Our system was applied to a database of 45 MRI scans from 8 normal and 10 GRMD dogs in a longitudinal natural history study. We first segmented six proximal pelvic limb muscles using a semiautomated full muscle segmentation method. We then performed preprocessing, including intensity inhomogeneity correction, spatial registration of different image sequences, intensity calibration of T2-weighted and T2-weighted fat-suppressed images, and calculation of MRI biomarker maps. Finally, for each of the segmented muscles, we automatically measured MRI biomarkers of muscle volume, intensity statistics over MRI biomarker maps, and statistical image texture features. Results The muscle volume and the mean intensities in T2 value, fat, and water maps showed group differences between normal and GRMD dogs. For the statistical texture biomarkers, both the histogram and run-length matrix features showed obvious group differences between normal and GRMD dogs. The full muscle segmentation showed significantly less error and variability in the proposed biomarkers when compared to the standard, limited muscle range segmentation. Conclusion The experimental results demonstrated that this quantification tool could reliably quantify MRI biomarkers in GRMD dogs, suggesting that it would also be useful for quantifying disease progression and measuring therapeutic effect in DMD patients.

Original languageEnglish
Pages (from-to)763-774
Number of pages12
JournalInternational Journal of Computer Assisted Radiology and Surgery
Volume8
Issue number5
DOIs
StatePublished - Sep 2013

Keywords

  • Canine model
  • Duchenne muscular dystrophy
  • Golden retriever muscular dystrophy
  • MRI
  • Segmentation
  • Statistical texture analysis

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