Sains Malaysiana 46(1)(2017): 67–74

http://dx.doi.org/10.17576/jsm-2017-4601-09

 

Determination of Optimum Combination of Voxel Size and b-value for Brain Diffusion Tensor Imaging

(Penentuan Gabungan Optimum Saiz Voksel dan Nilai-b untuk Pengimejan Tensor Difusi Otak)

NUR HARTINI MOHD TAIB1*, WAN AHMAD KAMIL WAN ABDULLAH1, IBRAHIM LUTFI SHUAIB2, ENRICO MAGOSSO2 & SUZANA MAT ISA2

 

1Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia

Kubang Kerian, Kelantan Darul Naim, Malaysia

 

2Advanced Medical and Dental Institute, Universiti Sains Malaysia, Kepala Batas, Pulau Pinang

Malaysia

 

Diserahkan: 20 Mei 2014/Diterima: 8 April 2016

 

ABSTRACT

Optimum combination of voxel size resolution and b-value for whole brain imaging has been determined. Data images were acquired using a 1.5T magnetic resonance imaging (MRI) system (GE Signa HDxt). Diffusion tensor imaging (DTI) scan was performed on phantom and a human volunteer. Six protocols which consist of various combination of voxel size and b-value were evaluated. Measurement of signal-to-noise ratio (SNR) and DTI parameter indices were carried out for both phantom and in-vivo studies. Due consideration was given to a combination of parameters yielding sufficient SNR with DTI values comparable to those obtained from previous reported studies. For the phantom study, SNR ≥ 20 was found in all of the protocols except for a combination of voxel size of 2.0 × 2.0 × 2.0 mm3 with b-value of 1200 s/mm2 (V2.0 B1200) and that of voxel size of 2.0 × 2.0 × 2.0 mm3 with b-value of 1000 s/mm2 (V2.0 B1000). For in-vivo study, all protocols presented SNR > 20. It was found that a combination of voxel size of 2.5 × 2.5 × 2.5 mm3 with b-value of 1000 s/mm2 (V2.5 B1000) and that of voxel size of 2.5 × 2.5 × 2.5 mm3 with b-value of 700 s/mm2 (V2.5 B700) displayed the most comparable ADC and FA values with references. In terms of anatomic coverage, V2.5 B700 was found better than V2.5 B1000 as it assures coverage of the whole brain. In conclusion, a combination of voxel size of 2.5 × 2.5 × 2.5 mm3 with b-value of 700 s/mm2 was considered as optimum parameters for brain DTI.

 

Keywords: Brain imaging; b-value; diffusion tensor imaging; optimization; voxel size

 

ABSTRAK

Gabungan optimum peleraian saiz voksel dan nilai-b untuk pengimejan seluruh otak telah ditentukan. Data imej telah diperoleh menggunakan sistem pengimejan resonans magnet (MRI) 1.5T (GE Signa HDxt). Imbasan pengimejan tensor difusi (DTI) telah dilakukan ke atas fantom dan seorang sukarelawan. Enam protokol yang terdiri daripada pelbagai gabungan saiz voksel dan nilai-b telah dinilai. Pengukuran nisbah isyarat-hingar (SNR) dan parameter indeks DTI telah dilakukan untuk kajian fantom dan in-vivo. Pertimbangan yang sewajarnya telah diberikan kepada gabungan parameter yang menghasilkan SNR mencukupi dan nilai DTI setara dengan yang diperoleh daripada kajian terdahulu. Untuk kajian fantom, didapati SNR ≥ 20 bagi semua protokol kecuali gabungan saiz voksel 2.0 × 2.0 × 2.0 mm3 dengan nilai-b 1200 s/mm2 (V2.0 B1200) dan gabungan saiz voksel 2.0 × 2.0 × 2.0 mm3 dengan nilai-b 1000 s/mm2 (V2.0 B1000). Bagi kajian in-vivo, semua protokol menunjukkan SNR > 20. Didapati gabungan saiz voksel 2.5 × 2.5 × 2.5 mm3 dengan nilai-b 1000 s/mm2 (V2.5 B1000) dan saiz voksel 2.5 × 2.5 × 2.5 mm3 dengan nilai-b 700 s/mm2 (V2.5 B700) telah mempamerkan nilai ADC dan FA paling setara dengan rujukan. Daripada segi liputan anatomi, didapati V2.5 B700 lebih baik daripada V2.5 B1000 kerana ia menjamin liputan seluruh otak. Kesimpulannya, gabungan saiz voxel 2.5 × 2.5 × 2.5 mm3 dengan nilai-b 700 s/mm2 dianggap sebagai parameter yang optimum untuk DTI otak.

 

Kata kunci: Nilai-b; pengimejan otak; pengimejan tensor difusi; pengoptimuman; saiz voksel

RUJUKAN

Alexander, D.C. & Barker, G.J. 2005. Optimal imaging parameters for fiber-orientation estimation in diffusion MRI. NeuroImage 27(2): 357-367.

Bastin, M.E., Armitage, P.A. & Marshall, I. 1998. A theoretical study of the effect of experimental noise on the measurement of anisotropy in diffusion imaging. Magnetic Resonance Imaging 16(7): 773-785.

Bougias, C. & Tripoliti, E.E. 2009. Theory of diffusion tensor imaging and fiber tractography analysis. European Journal of Radiography 1(1): 37-41.

Chanraud, S., Zahr, N., Sullivan, E.V. & Pfefferbaum, A. 2010. MR diffusion tensor imaging: A window into white matter integrity of the working brain. Neuropsychology Review 20(2): 209-225.

Ding, X.Q., Finsterbusch, J., Wittkugel, O., Saager, C., Geobell, E., Fitting, T., Grzyska, U., Zeumer, H. & Fiehler, J. 2007. Apparent diffusion coefficient, fractional anisotropy and T2 relaxation time measurement: Does the field strength matter? Clinical Neuroradiology 17: 230-238.

Dietrich, O., Raya, J.G., Reeder, S.B., Reiser, M.F. & Schoenberg, S.O. 2007. Measurement of signal-to-noise ratios in MR images: Influence of multichannel coils, parallel imaging, and reconstruction filters. Journal of Magnetic Resonance Imaging 26 (2): 375-385.

Hunsche, S., Moseley, M.E., Stoeter, P. & Hedehus, M. 2001. Diffusion-tensor MR imaging at 1.5 and 3.0 T: Initial observations. Radiology 221(2): 550-556.

Jones, D.K., Lythgoe, D., Horsfield, M.A., Simmons, A., Williams, S.C.R. & Markus, H.S. 1999. Characterization of white matter damage in Ischemic leukoaraiosis with diffusion tensor MRI. Stroke 30(2): 393-397.

Jones, D.K. 2004. The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: A Monte Carlo study. Magnetic Resonance in Medicine 51(4): 807-815.

Jones, D.K., Williams, S.C.R., Gasston, D., Horsfield, M.A., Sim, A. & Howard, R. 2002. Isotropic resolution diffusion tensor imaging with whole brain acquisition in a clinically acceptable time. Human Brain Mapping 15(4): 216-230.

Jones, D.K. & Basser, P.J. 2004. Squashing peanuts and smashing pumpkins: How noise distorts diffusion-weighted MR data. Magnetic Resonance in Medicine 52(5): 979-993.

King, K.F. 2004. ASSET - parallel imaging on the GE scanner. In GE Healthcare http://www.mr.ethz.ch/parallelmri04/ abstracts/pub/King.pdf. Accessed on 22 December 2011.

Laganà, M., Rovaris, M., Ceccarelli, A., Venturelli, C., Marini, S. & Baselli, G. 2010. DTI parameter optimisation for acquisition at 1.5T: SNR analysis and clinical application. Computational Intelligence and Neuroscience 2010: 1-8.

Lazar, M. & Alexander, A.L. 2003. An error analysis of white matter tractography methods: Synthetic diffusion tensor field simulations. NeuroImage 20(2): 1140-1153.

Le Bihan, D., Mangin, J-F., Poupon, C., Clark, C.A., Pappata, S., Molko, N. & Chabriat, H. 2001. Diffusion tensor imaging: Concepts and applications. Journal of Magnetic Resonance Imaging 13(4): 534-546.

Löbel, U., Sedlacik, J., Güllmar, D., Kaiser, W.A., Reichenbach, J.R. & Mentzel, H.J. 2009. Diffusion tensor imaging: The normal evolution of ADC, RA, FA, and eigenvalues studied in multiple anatomical regions of the brain. Neuroradiology 51(4): 253-263.

Madden, D.J., Bennett, I.J. & Song, A.W. 2009. Cerebral white matter integrity and cognitive aging: Contributions from diffusion tensor iamaging. Neuropsychology Review 19: 415-435.

McRobbie, Donald W., Elizabeth A. Moore, Martin J. Graves, and Martin R. Prince. 2006. Chapter 5 - What you set is what you get: basic image optimization. In MRI from Picture to Proton, edited by McRobbie, D.W., Moore, E.A., G.M.J. & Prince, M.R. Cambridge: Cambridge University Press.

Mohd Taib, Nur Hartini, Wan Ahmad Kamil Wan Abdullah, Ibrahim Lutfi Shuaib, Enrico Magosso, & Suzana Mat Isa. 2012. Diffusion tensor imaging and tractography for the assessment of leukoaraiosis. Paper read at IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), 17-19 December 2012, at Langkawi, Malaysia.

Mori, S. 2007. Chapter 6 - Practical aspects of diffusion tensor imaging. In Introduction to Diffusion Tensor Imaging. Amsterdam: Elsevier Science B.V.

Mukherjee, P., Chung, S.W., Berman, J.I., Hess, C.P. & Henry, R.G. 2008a. Diffusion tensor MR imaging and fiber tractography: Technical considerations. AJNR American Journal of Neuroradiology 29: 843-852.

Mukherjee, P., Berman, J.I., Chung, S.W., Hess, C.P. & Henry, R.G. 2008b. Diffusion tensor MR imaging and fiber tractography: Theoretic underpinnings. AJNR American Journal of Neuroradiology 29: 632-641.

Oouchi, H., Yamada, K., Sakai, K., Kizu, O., Kubota, T., Ito, H. & Nishimura, T. 2007. Diffusion anisotropy measurement of brain white matter is affected by voxel size: Underestimation occurs in areas with crossing fibers. AJNR American Journal of Neuroradiology 28(6): 1102-1106.

Reeder, S.B., Wintersperger, B.J., Dietrich, O., Lanz, T., Greiser, A., Reiser, M.F., Glazer, G.M. & Schoenberg, S.O. 2005. Practical approaches to the evaluation of signal-to-noise ratio performance with parallel imaging: Application with cardiac imaging and a 32-channel cardiac coil. Magnetic Resonance in Medicine 54(3): 748-754.

Sasaki, M. 2007. High-resolution, isotropic-voxel acquisition technique improves quality and utility of diffusion-weighted and diffusion tensor imaging. GE Healthcare Signa Pulse. pp. 20-23.

 

 

*Pengarang untuk surat-menyurat; email: nhartini@usm.my

 

 

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