Shingo Kakeda1, Koichiro Futatsuya2, Satoru Ide2, Keita Watanabe2, Mari Miyata2, Junji Moriya2, Atsushi Ogasawara2, Toru Sato2, Hidekuni Narimatsu2, Kazumasa Okada3, Takenori Uozumi3, Tian Liu4, Yi Wang4, Yukunori Korogi2. 1. Department of Radiology, School of Medicine, University of Occupational and Environmental Health, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan. Electronic address: kakeda@med.uoeh-u.ac.jp. 2. Department of Radiology, School of Medicine, University of Occupational and Environmental Health, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan. 3. Department of Neurology, School of Medicine, University of Occupational and Environmental Health, Kitakyushu, Japan. 4. Department of Biomedical Engineering, Cornell University, Ithaca, New York.
Abstract
RATIONALE AND OBJECTIVES: Quantitative susceptibility mapping (QSM) is a novel technique which allows determining the bulk magnetic susceptibility distribution of tissue in vivo from gradient echo magnetic resonance (MR) phase images. Our purpose was to evaluate if there is additional diagnostic value of QSM images in detecting the cortical gray matter involvement in multiple sclerosis (MS) patients. MATERIALS AND METHODS: Our institutional review board approved this study. Conventional MR imaging, including T2-weighted imaging and two- or three-dimensional fluid-attenuated inversion recovery images, and QSM imaging examinations were performed in 27 patients (19 male and eight female) with MS. Two radiologists (radiologists 1 and 2) assessed the MS lesions in the following 3 anatomic regions: intracortical, mixed white matter-gray matter (WM-GM), and juxtacortical regions. The numbers of lesions per region category were compared between conventional MR images with and without QSM images. RESULTS: For radiologists 1 and 2, QSM images identified 6 (50.0%) and 7 (50.0%) additional lesions that were not seen in the conventional MR images, respectively. In a lesion-by-lesion analysis, the substantial fraction (20 [25.3%] of 79 at radiologist 1, 22 [29.7%] of 74 at radiologist 2) of juxtacortical white matter lesions on the conventional MR images were scored as mixed WM-GM lesions with QSM images. CONCLUSIONS: Our preliminary results suggest that the MR imaging with QSM may increase the sensitivity in cortical lesion detection in the MS brain and improved distinction between juxtacortical and mixed WM-GM lesions.
RATIONALE AND OBJECTIVES: Quantitative susceptibility mapping (QSM) is a novel technique which allows determining the bulk magnetic susceptibility distribution of tissue in vivo from gradient echo magnetic resonance (MR) phase images. Our purpose was to evaluate if there is additional diagnostic value of QSM images in detecting the cortical gray matter involvement in multiple sclerosis (MS) patients. MATERIALS AND METHODS: Our institutional review board approved this study. Conventional MR imaging, including T2-weighted imaging and two- or three-dimensional fluid-attenuated inversion recovery images, and QSM imaging examinations were performed in 27 patients (19 male and eight female) with MS. Two radiologists (radiologists 1 and 2) assessed the MS lesions in the following 3 anatomic regions: intracortical, mixed white matter-gray matter (WM-GM), and juxtacortical regions. The numbers of lesions per region category were compared between conventional MR images with and without QSM images. RESULTS: For radiologists 1 and 2, QSM images identified 6 (50.0%) and 7 (50.0%) additional lesions that were not seen in the conventional MR images, respectively. In a lesion-by-lesion analysis, the substantial fraction (20 [25.3%] of 79 at radiologist 1, 22 [29.7%] of 74 at radiologist 2) of juxtacortical white matter lesions on the conventional MR images were scored as mixed WM-GM lesions with QSM images. CONCLUSIONS: Our preliminary results suggest that the MR imaging with QSM may increase the sensitivity in cortical lesion detection in the MS brain and improved distinction between juxtacortical and mixed WM-GM lesions.
Authors: M Castellaro; R Magliozzi; A Palombit; M Pitteri; E Silvestri; V Camera; S Montemezzi; F B Pizzini; A Bertoldo; R Reynolds; S Monaco; M Calabrese Journal: AJNR Am J Neuroradiol Date: 2017-04-13 Impact factor: 3.825
Authors: Yi Wang; Pascal Spincemaille; Zhe Liu; Alexey Dimov; Kofi Deh; Jianqi Li; Yan Zhang; Yihao Yao; Kelly M Gillen; Alan H Wilman; Ajay Gupta; Apostolos John Tsiouris; Ilhami Kovanlikaya; Gloria Chia-Yi Chiang; Jonathan W Weinsaft; Lawrence Tanenbaum; Weiwei Chen; Wenzhen Zhu; Shixin Chang; Min Lou; Brian H Kopell; Michael G Kaplitt; David Devos; Toshinori Hirai; Xuemei Huang; Yukunori Korogi; Alexander Shtilbans; Geon-Ho Jahng; Daniel Pelletier; Susan A Gauthier; David Pitt; Ashley I Bush; Gary M Brittenham; Martin R Prince Journal: J Magn Reson Imaging Date: 2017-03-10 Impact factor: 4.813
Authors: Anjali A Roeth; Ioana Slabu; Martin Baumann; Patrick H Alizai; Maximilian Schmeding; Gernot Guentherodt; Thomas Schmitz-Rode; Ulf P Neumann Journal: Int J Nanomedicine Date: 2017-08-18