Takahiro Nakayama1, Akihiko Ishiyama2, Terumi Murakami3, En Kimura4, Satoshi Kuru5. 1. Department of Neurology, Division of Neuromuscular Diseases, Yokohama Rosai Hospital, Japan. Electronic address: tnakayama-tky@umin.ac.jp. 2. Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, Japan. 3. Department of Neurology, NHO Higashisaitama National Hospital, Japan. 4. Chief of Extra Early Exploratory Clinical Trail Unit, Department of Promoting Clinical Trial and Translational Medicine, Translational Medical Center, and Department of Neurology, National Center Hospital, National Center of Neurology and Psychiatry, Japan. 5. Department of Neurology, NHO Suzuka National Hospital, Japan.
Abstract
BACKGROUND: Mercuri grading of muscle images is a useful method to evaluate the progression of muscular dystrophies. However, because Mercuri grading is skill-based, few competent experts are available. We therefore developed an automated method for Mercuri grade calculations. METHODS: We used computed tomography (CT) and magnetic resonance (MR) images of the thigh and lower leg muscles taken from a Japanese limb-girdle muscular dystrophy patient database. We calculated muscle impairment ratios based on the CT images, and then converted the ratios to revised Mercuri grades. This method was also applied to T1-weighted MR images. Additionally, radiation absorption doses in muscle and chest CT images from a separate patient group were also analyzed. RESULTS: We observed a close correlation between our automatically calculated Mercuri grades and skill-based visually determined Mercuri grades in both CT and MR images. The radiation absorption, measured by total dose length product, was lower in muscle CT (121.8 mGy-cm) than in chest CT (524.1 mGy-cm). CONCLUSIONS: We developed a new automatic Mercuri grading method using values obtained from CT images. This method was also applied to calculate the Mercuri grade of T1-weighted MR images. In addition, the radiation doses from muscle CT were observed to be lower than those from chest CT.
BACKGROUND: Mercuri grading of muscle images is a useful method to evaluate the progression of muscular dystrophies. However, because Mercuri grading is skill-based, few competent experts are available. We therefore developed an automated method for Mercuri grade calculations. METHODS: We used computed tomography (CT) and magnetic resonance (MR) images of the thigh and lower leg muscles taken from a Japanese limb-girdle muscular dystrophypatient database. We calculated muscle impairment ratios based on the CT images, and then converted the ratios to revised Mercuri grades. This method was also applied to T1-weighted MR images. Additionally, radiation absorption doses in muscle and chest CT images from a separate patient group were also analyzed. RESULTS: We observed a close correlation between our automatically calculated Mercuri grades and skill-based visually determined Mercuri grades in both CT and MR images. The radiation absorption, measured by total dose length product, was lower in muscle CT (121.8 mGy-cm) than in chest CT (524.1 mGy-cm). CONCLUSIONS: We developed a new automatic Mercuri grading method using values obtained from CT images. This method was also applied to calculate the Mercuri grade of T1-weighted MR images. In addition, the radiation doses from muscle CT were observed to be lower than those from chest CT.
Authors: Emil Rydell Högelin; Kajsa Thulin; Ferdinand von Walden; Lotta Fornander; Piotr Michno; Björn Alkner Journal: Front Physiol Date: 2022-06-27 Impact factor: 4.755