Development of a high-precision image-processing automatic measurement system for MRI visceral fat images acquired using a binomial RF-excitation pulse.
Development of a rapid and accurate method for visceral fat measurement is an important task, given the recent increase in the number of patients with metabolic syndrome. In this study, we optimized the Fast Low Angle Shot (FLASH) sequence using a binominal radiofrequency excitation pulse, in which the acquisition time is short, and measured changes in the amount of visceral fat in subjects after a period of wearing clothes with a fat-reducing effect during walking. We solved the reproducibility problem associated with the number of slices, and developed automatic measurement software for high-precision separation and extraction of abdominal visceral fat images. This software was developed using intensity correction with the coil position, derivation of a threshold by histogram analysis and fat separation by template matching for abdominal images. The cross-sectional area of a single slice varies for every acquisition due to visceral organ movement, but the relative error largely converged for seven slices. The measured amount of abdominal fat tended to be consistent with changes in the body fat and waist circumference of the subjects. The correlation coefficients between automatic extraction using the measurement software and manual extraction were 0.9978 for subcutaneous fat and 0.9972 for visceral fat, showing very strong positive correlations. The consistency rates were 0.9502+/-0.0167 for subcutaneous fat and 0.9395+/-0.0147 for visceral fat, and the shapes of the regions were also extracted very accurately. These results show that the magnetic resonance imaging acquisition method and image processing system developed in this study are beneficial for measurement of abdominal visceral fat. Therefore, this method may have a major role in future diagnosis of metabolic syndrome.
Nakai
Ryusuke
R
Department of Medical Simulation Engineering, Research Center for Nano Medical Engineering, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan. rnakai@frontier.kyoto-u.ac.jp
Azuma
Takashi
T
Kishimoto
Taizou
T
Hirata
Tazuko
T
Takizawa
Osamu
O
Hyon
Suong-Hyu
SH
Tsutsumi
Sadami
S
D000273:Adipose Tissue / Q000473:pathology; D000328:Adult; D001331:Automation; D015444:Exercise; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D050152:Intra-Abdominal Fat / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D018482:Muscle, Skeletal / Q000473:pathology; D011846:Radio Waves; D015203:Reproducibility of Results; D012984:Software