naa a22 4500 510808182 CHVBK 20180411083428.0 cr unu---uuuuu 180411e20130901xx s 000 0 eng 10.1007/s11548-012-0810-6 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0810-6 A computerized MRI biomarker quantification scheme for a canine model of Duchenne muscular dystrophy [Elektronische Daten] [Jiahui Wang, Zheng Fan, Krista Vandenborne, Glenn Walter, Yael Shiloh-Malawsky, Hongyu An, Joe Kornegay, Martin Styner] PurposeGolden 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. MethodsOur 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. ConclusionThe 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. CARS, 2013 Duchenne muscular dystrophy nationallicence Golden retriever muscular dystrophy nationallicence MRI nationallicence Canine model nationallicence Segmentation nationallicence Statistical texture analysis nationallicence Wang Jiahui Department of Psychiatry, University of North Carolina, 27599, Chapel Hill, NC, USA aut Fan Zheng Department of Neurology, University of North Carolina, 27599, Chapel Hill, NC, USA aut Vandenborne Krista Department of Physical Therapy, University of Florida, 32610, Gainesville, FL, USA aut Walter Glenn Department of Physiology and Functional Genomics, University of Florida, 32610, Gainesville, FL, USA aut Shiloh-Malawsky Yael Department of Neurology, University of North Carolina, 27599, Chapel Hill, NC, USA aut An Hongyu Department of Radiology, University of North Carolina, 27599, Chapel Hill, NC, USA aut Kornegay Joe Department of Neurology, University of North Carolina, 27599, Chapel Hill, NC, USA aut Styner Martin Department of Psychiatry, University of North Carolina, 27599, Chapel Hill, NC, USA aut International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/5(2013-09-01), 763-774 1861-6410 8:5<763 2013 8 11548 https://doi.org/10.1007/s11548-012-0810-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0810-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Jiahui Department of Psychiatry, University of North Carolina, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 700 1- Fan Zheng Department of Neurology, University of North Carolina, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 700 1- Vandenborne Krista Department of Physical Therapy, University of Florida, 32610, Gainesville, FL, USA aut NATIONALLICENCE 700 1- Walter Glenn Department of Physiology and Functional Genomics, University of Florida, 32610, Gainesville, FL, USA aut NATIONALLICENCE 700 1- Shiloh-Malawsky Yael Department of Neurology, University of North Carolina, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 700 1- An Hongyu Department of Radiology, University of North Carolina, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 700 1- Kornegay Joe Department of Neurology, University of North Carolina, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 700 1- Styner Martin Department of Psychiatry, University of North Carolina, 27599, Chapel Hill, NC, USA aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/5(2013-09-01), 763-774 1861-6410 8:5<763 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer