Magnetic Resonance Imaging
Volume 28, Issue 4 , Pages 520-526 , May 2010

Development of a high-precision image-processing automatic measurement system for MRI visceral fat images acquired using a binomial RF-excitation pulse

  • Ryusuke Nakai

      Affiliations

    • Department of Medical Simulation Engineering, Research Center for Nano Medical Engineering, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan
    • Corresponding Author InformationCorresponding author. Tel.: +81 075 751 4132; fax: +81 075 751 4132.
  • ,
  • Takashi Azuma

      Affiliations

    • Department of Medical Simulation Engineering, Research Center for Nano Medical Engineering, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan
  • ,
  • Taizou Kishimoto

      Affiliations

    • Human Science Research Center, Wacoal Corporation, Kyoto, Japan
  • ,
  • Tazuko Hirata

      Affiliations

    • Human Science Research Center, Wacoal Corporation, Kyoto, Japan
  • ,
  • Osamu Takizawa

      Affiliations

    • Medical Solution Marketing Division, Siemens Asahi Medical Technologies Ltd., Tokyo, Japan
  • ,
  • Suong-Hyu Hyon

      Affiliations

    • Department of Medical Simulation Engineering, Research Center for Nano Medical Engineering, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan
  • ,
  • Sadami Tsutsumi

      Affiliations

    • Nihon University School of Dentistry, Tokyo, Japan

Received 8 September 2009 ,Accepted 7 December 2009.

References 

  1. Choi HK, Ford ES. Prevalence of the metabolic syndrome in individuals with hyperuricemia. Am J Med. 2007;120(5):442–447
  2. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA. 2002;287(3):356–359
  3. Grandinetti A, Chang HK, Theriault A, Mor J. Metabolic syndrome in a multiethnic population in rural Hawaii.. Ethn. Dis. 2005;15(2):233–237
  4. Amemiya S, Dobashi K, Urakami T, Sugihara S, Ohzeki T, Tajima N. Metabolic syndrome in youths. Pediatr Diabetes. 2007;8(Suppl 9):48–54
  5. Munakata M, Honma H, Akasi M, Araki T, Kawamura T, Kubota M, et al. Japanese study to organize proper lifestyle modifications for metabolic syndrome (J-STOP-MetS): design and method. Vasc Health Risk Manag. 2008;4(2):415–420
  6. Oka R, Kobayashi J, Yagi K, Tanii H, Miyamoto S, Asano A, et al. Reassessment of the cutoff values of waist circumference and visceral fat area for identifying Japanese subjects at risk for the metabolic syndrome. Diabetes Res Clin Pract. 2008;79(3):474–481
  7. Tong J, Boyko EJ, Utzschneider KM, McNeely MJ, Hayashi T, Carr DB, et al. Intra-abdominal fat accumulation predicts the development of the metabolic syndrome in non-diabetic Japanese-Americans. Diabetologia. 2007;50(6):1156–1160
  8. Hyun YJ, Kim OY, Jang Y, Ha JW, Chae JS, Kim JY, et al. Evaluation of metabolic syndrome risk in korean premenopausal women. Circ J. 2008;72(8):1308–1315
  9. van der Kooy K, Leenen R, Seidell JC, Deurenberg P, Droop A, Bakker CJ. Waist-hip ratio is a poor predictor of changes in visceral fat. Am J Clin Nutr. 1993;57(3):327–333
  10. Kim S, Lee GH, Lee S, Park SH, Pyo HB, Cho JS. Body fat measurement in computed tomography image. Biomed Sci Instrum. 1999;35:303–308
  11. Nakamura T, Yoshizumi T. Measurement of visceral fat by CT scan. Nippon Rinsho. 2006;64(Suppl 9):476–480
  12. Yoshizumi T, Nakamura T, Yamane M, Islam AH, Menju M, Yamasaki K, et al. Abdominal fat: standardized technique for measurement at CT. Radiology. 1999;211(1):283–286
  13. Hwang JH, Stein DT, Barzilai N, Cui MH, Tonelli J, Kishore P, et al. Increased intrahepatic triglyceride is associated with peripheral insulin resistance: in vivo MR imaging and spectroscopy studies. Am J Physiol Endocrinol Metab. 2007;293(6):E1663–E1669
  14. Tanaka S, Yoshiyama M, Imanishi Y, Nakahira K, Hanaki T, Naito Y, et al. MR measurement of visceral fat: assessment of metabolic syndrome. Magn Reson Med Sci. 2006;5(4):207–210
  15. Tintera J, Harantova P, Suchanek P, Dvorakova A, Adamova M, Hajek M, et al. Quantification of intra-abdominal fat during controlled weight reduction: assessment using the water-suppressed breath-hold MRI technique. Physiol Res. 2004;53(2):229–234
  16. Wohlgemuth WA, Roemer FW, Bohndorf K. Short tau inversion recovery and three-point Dixon water-fat separation sequences in acute traumatic bone fractures at open 0.35 tesla MRI. Skeletal Radiol. 2002;31(6):343–348
  17. Nakai R, Azuma T, Sudo M, Urayama S, Takizawa O, Tsutsumi S. MRI analysis of structural changes in skeletal muscles and surrounding tissues following long-term walking exercise with training equipment. J Appl Physiol. 2008;105(3):958–963
  18. Nishiyama H, Hayashi T. Sensitivity correction of the circular type surface coil for temporomandibular joint. Niigata Dent J. 2004;34(1):49–51
  19. Pruis GW, Gilding BH, Peters MJ. A comparison of different numerical methods for solving the forward problem in EEG and MEG. Physiol Meas. 1993;14(Suppl 4A):A1–A9
  20. Vullo T, Pascone R, Mancuso R, Zipagan R, Cahill PT. Transmission line analysis of noncylindrical birdcage resonators. Magn Reson Imaging. 1994;12(5):785–797
  21. Press WH, Flannery BP, Teukolsky SA, Vetterling WT. LU Decomposition and Its Applications. In:  Press WH editors. §2.3 in Numerical Recipes in FORTRAN: the art of scientific computing. 2nd ed.. Cambridge, England: Cambridge University Press; 1992;p. 34–42
  22. Andrew M, Paul J. An improved seeded region growing algorithm. Pattern Recogn Lett. 1997;18(10):1065–1071
  23. Zucker SW. Survey, region growing: childhood and adolescence. Comput Graph Image Process. 1976;382–399
  24. Hounsfield GN. Nobel Award address. Computed medical imaging. Med Phys. 1980;7(4):283–290
  25. Ommaya AK, Murray G, Ambrose J, Richardson A, Hounsfield G. Computerized axial tomography: estimation of spatial and density resolution capability. Br J Radiol. 1976;49(583):604–611
  26. Potretzke AM, Schmitz KH, Jensen MD. Preventing overestimation of pixels in computed tomography assessment of visceral fat. Obes Res. 2004;12(10):1698–1701
  27. Jørgensen SP, Larsen R, Wraae K. Automatic assessment of intraabdominal fat by MRI. In: Proceedings of 2nd the International Workshop on Image Analysis and In-Vivo Pharmacology. 2007;

PII: S0730-725X(09)00311-7

doi: 10.1016/j.mri.2009.12.019

Magnetic Resonance Imaging
Volume 28, Issue 4 , Pages 520-526 , May 2010