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Evaluation of Hippocampal Volume Based on Various Inversion Time in Normal Adults by Manual Tracing and Automated Segmentation Methods

  • Kim, Ju Ho (Department of Convergence Medical Science, Gyeongsang National University Graduate School) ;
  • Choi, Dae Seob (Department of Radiology, Gyeongsang National University School of Medicine) ;
  • Kim, Seong-hu (Department of Radiology, Gyeongsang National University Hospital) ;
  • Shin, Hwa Seon (Department of Radiology, Gyeongsang National University School of Medicine) ;
  • Seo, Hyemin (Department of Radiology, Gyeongsang National University School of Medicine) ;
  • Choi, Ho Cheol (Department of Radiology, Gyeongsang National University School of Medicine) ;
  • Son, Seungnam (Department of Neurology, Gyeongsang National University School of Medicine) ;
  • Tae, Woo Suk (Neuroscience Research Institute, Kangwon National University School of Medicine) ;
  • Kim, Sam Soo (Department of Radiology, Kangwon National University School of Medicine)
  • 투고 : 2015.04.28
  • 심사 : 2015.05.20
  • 발행 : 2015.06.30

초록

Purpose: To investigate the value of image post-processing software (FreeSurfer, IBASPM [individual brain atlases using statistical parametric mapping software]) and inversion time (TI) in volumetric analyses of the hippocampus and to identify differences in comparison with manual tracing. Materials and Methods: Brain images from 12 normal adults were acquired using magnetization prepared rapid acquisition gradient echo (MPRAGE) with a slice thickness of 1.3 mm and TI of 800, 900, 1000, and 1100 ms. Hippocampal volumes were measured using FreeSurfer, IBASPM and manual tracing. Statistical differences were examined using correlation analyses accounting for spatial interpretations percent volume overlap and percent volume difference. Results: FreeSurfer revealed a maximum percent volume overlap and maximum percent volume difference at TI = 800 ms ($77.1{\pm}2.9%$) and TI = 1100 ms ($13.1{\pm}2.1%$), respectively. The respective values for IBASPM were TI = 1100 ms ($55.3{\pm}9.1%$) and TI = 800 ms ($43.1{\pm}10.7%$). FreeSurfer presented a higher correlation than IBASPM but it was not statistically significant. Conclusion: FreeSurfer performed better in volumetric determination than IBASPM. Given the subjective nature of manual tracing, automated image acquisition and analysis image is accurate and preferable.

키워드

참고문헌

  1. Sanchez-Benavides G, Gomez-Anson B, Sainz A, Vives Y, Delfino M, Pena-Casanova J. Manual validation of FreeSurfer's automated hippocampal segmentation in normal aging, mild cognitive impairment, and Alzheimer Disease subjects. Psychiatry Res 2010;181:219-225 https://doi.org/10.1016/j.pscychresns.2009.10.011
  2. Takao H, Abe O, Ohtomo K. Computational analysis of cerebral cortex. Neuroradiology 2010;52:691-698 https://doi.org/10.1007/s00234-010-0715-4
  3. Geuze E, Vermetten E, Bremner JD. MR-based in vivo hippocampal volumetrics: 2. Findings in neuropsychiatric disorders. Mol Psychiatry 2005;10:160-184 https://doi.org/10.1038/sj.mp.4001579
  4. Giedd JN, Vaituzis AC, Hamburger SD, et al. Quantitative MRI of the temporal lobe, amygdala, and hippocampus in normal human development: ages 4-18 years. J Comp Neurol 1996;366:223-230 https://doi.org/10.1002/(SICI)1096-9861(19960304)366:2<223::AID-CNE3>3.0.CO;2-7
  5. Tae WS, Kim SS, Lee KU, Nam EC, Kim KW. Validation of hippocampal volumes measured using a manual method and two automated methods (FreeSurfer and IBASPM) in chronic major depressive disorder. Neuroradiology 2008;50:569-581 https://doi.org/10.1007/s00234-008-0383-9
  6. Petersen RC, Doody R, Kurz A, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001;58:1985-1992 https://doi.org/10.1001/archneur.58.12.1985
  7. Chupin M, Chetelat G, Lemieux L, et al. Fully automatic hippocampus segmentation discriminates between early alzheimer's disease and normal aging. Biomedical imaging from nano to macro: 5th IEEE International Symposium 2008:97-100
  8. Dickerson BC, Goncharova I, Sullivan MP, et al. MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer's disease. Neurobiol Aging 2001;22:747-754 https://doi.org/10.1016/S0197-4580(01)00271-8
  9. Pedraza O, Bowers D, Gilmore R. Asymmetry of the hippocampus and amygdala in MRI volumetric measurements of normal adults. J Int Neuropsychol Soc 2004;10:664-678 https://doi.org/10.1017/S1355617704105080
  10. Hammers A, Heckemann R, Koepp MJ, et al. Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: a proof-of-principle study. Neuroimage 2007;36:38-47 https://doi.org/10.1016/j.neuroimage.2007.02.031
  11. Brewer JB. Fully-automated volumetric MRI with normative ranges: translation to clinical practice. Behav Neurol 2009;21:21-28 https://doi.org/10.1155/2009/616581
  12. Jung WB, Kang MJ, Son DB, et al. Reproducibility analysis of brain volumetry measured from inter MR scanner of multi-Institute. J Korean Soc Magn Reson Med 2012;16:243-252 https://doi.org/10.13104/jksmrm.2012.16.3.243
  13. Nelson F, Poonawalla A, Hou P, Wolinsky JS, Narayana PA. 3D MPRAGE improves classification of cortical lesions in multiple sclerosis. Mult Scler 2008;14:1214-1219 https://doi.org/10.1177/1352458508094644
  14. van der Kouwe AJ, Benner T, Salat DH, Fischl B. Brain morphometry with multiecho MPRAGE. Neuroimage 2008;40:559-569 https://doi.org/10.1016/j.neuroimage.2007.12.025
  15. Kim HD, Chang KH, Han MH, Kim HJ, Lee SG, Lee MC. The significance and limitation of MR volumetry: comparison between normal adults and the patients with epilepsy and hippocampal sclerosis. J Korean Soc Magn Reson Med 2002;6:47-54
  16. Choi N, Nam Y, Kim DH. Cortical thickness estimation using DIR imaging with GRAPPA factor 2. J Korean Soc Magn Reson Med 2010;14:56-63 https://doi.org/10.13104/jksmrm.2010.14.1.56
  17. Kim JH, Kim SH, Choi DS. A study of changes of inversion time effect on brain volume of normal volunteers. J Korean Soc Magn Reson Med 2013;17:286-293 https://doi.org/10.13104/jksmrm.2013.17.4.286
  18. Morey RA, Petty CM, Xu Y, et al. A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes. Neuroimage 2009;45:855-866 https://doi.org/10.1016/j.neuroimage.2008.12.033
  19. Khan AR, Wang L, Beg MF. FreeSurfer-initiated fullyautomated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping. Neuroimage 2008;41:735-746 https://doi.org/10.1016/j.neuroimage.2008.03.024
  20. Fischl B. FreeSurfer. Neuroimage 2012;62:774-781 https://doi.org/10.1016/j.neuroimage.2012.01.021
  21. Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM. Fsl. Neuroimage 2012;62:782-790 https://doi.org/10.1016/j.neuroimage.2011.09.015
  22. Aleman-Gomez Y, Melie-Garcia L, Valdes-Hernandez P. IBASPM: toolbox for automatic parcellation of brain structures. Presented at the 12th Annual Meeting of the organization for human brain mapping, June 2006, Florence, Italy. Available on CD-Rom in neuroImage, vol. 27, no. 1
  23. Watson C, Andermann F, Gloor P, et al. Anatomic basis of amygdaloid and hippocampal volume measurement by magnetic resonance imaging. Neurology 1992;42:1743-1750 https://doi.org/10.1212/WNL.42.9.1743
  24. Hasboun D, Chantome M, Zouaoui A, et al. MR determination of hippocampal volume: comparison of three methods. AJNR Am J Neuroradiol 1996;17:1091-1098
  25. Jack CR Jr, Theodore WH, Cook M, McCarthy G. MRI-based hippocampal volumetrics: data acquisition, normal ranges, and optimal protocol. Magn Reson Imaging 1995;13:1057-1064 https://doi.org/10.1016/0730-725X(95)02013-J
  26. Yushkevich PA, Piven J, Hazlett HC, et al. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 2006;31:1116-1128 https://doi.org/10.1016/j.neuroimage.2006.01.015
  27. Fischl B, Salat DH, Busa E, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002;33:341-355 https://doi.org/10.1016/S0896-6273(02)00569-X
  28. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 2002;15:273-289 https://doi.org/10.1006/nimg.2001.0978
  29. Jung WB, Son DB, Kim YJ, Kim YH, Eun CK, Mun CW. A comparison study on human brain volume of white matter, gray matter and hippocampus depending on magnetic resonance imaging conditions and applied brain template. J Korean Soc Magn Reson Med 2011;15:242-250 https://doi.org/10.13104/jksmrm.2011.15.3.242

피인용 문헌

  1. The impact of hippocampal segmentation methods on correlations with clinical data vol.61, pp.7, 2015, https://doi.org/10.1177/0284185119885120