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PLOS ONE  2014 

Diffusion Tensor Imaging and Resting-State Functional MRI-Scanning in 5- and 6-Year-Old Children: Training Protocol and Motion Assessment

DOI: 10.1371/journal.pone.0094019

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Abstract:

Advanced Magnetic Resonance Imaging (MRI) techniques such as Diffusion Tensor Imaging (DTI) and resting-state functional MRI (rfMRI) are widely used to study structural and functional neural connectivity. However, as these techniques are highly sensitive to motion artifacts and require a considerable amount of time for image acquisition, successful acquisition of these images can be challenging to complete with certain populations. This is especially true for young children. This paper describes a new approach termed the ‘submarine protocol’, designed to prepare 5- and 6-year-old children for advanced MRI scanning. The submarine protocol aims to ensure that successful scans can be acquired in a time- and resource-efficient manner, without the need for sedation. This manuscript outlines the protocol and details its outcomes, as measured through the number of children who completed the scanning procedure and analysis of the degree of motion present in the acquired images. Seventy-six children aged between 5.8 and 6.9 years were trained using the submarine protocol and subsequently underwent DTI and rfMRI scanning. After completing the submarine protocol, 75 of the 76 children (99%) completed their DTI-scan and 72 children (95%) completed the full 35-minute scan session. Results of diffusion data, acquired in 75 children, showed that the motion in 60 of the scans (80%) did not exceed the threshold for excessive motion. In the rfMRI scans, this was the case for 62 of the 71 scans (87%). When placed in the context of previous studies, the motion data of the 5- and 6-year-old children reported here were as good as, or better than those previously reported for groups of older children (i.e., 8-year-olds). Overall, this study shows that the submarine protocol can be used successfully to acquire DTI and rfMRI scans in 5 and 6-year-old children, without the need for sedation or lengthy training procedures.

References

[1]  Van Dijk KRA, Sabuncu MR, Buckner RL (2012) The influence of head motion on intrinsic functional connectivity MRI. NeuroImage 59: 431–438. doi: 10.1016/j.neuroimage.2011.07.044
[2]  Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59: 2142–2154. doi: 10.1016/j.neuroimage.2011.10.018
[3]  Satterthwaite TD, Wolf DH, Loughead J, Ruparel K, Elliott MA, et al. (2012) Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. NeuroImage 60: 623–632. doi: 10.1016/j.neuroimage.2011.12.063
[4]  Ling J, Merideth F, Caprihan A, Pena A, Teshiba T, et al. (2012) Head injury of head motion? Assessment and quantification of motion artifacts in diffusion tensor imaging studies. Hum Brain Mapp 33: 50–62. doi: 10.1002/hbm.21192
[5]  Uddin LQ, Supekar K, Menon V (2013) Reconceptualizing functional brain connectivity in autism from a developmental perspective. Front Hum Neurosci 7: 458. doi: 10.3389/fnhum.2013.00458
[6]  Vandermosten M, Boets B, Wouters J, Ghesquière P (2012) A qualitative and quantitative review of diffusion tensor imaging studies in reading and dyslexia. Neurosci Biobehav Rev 36: 1532–1552. doi: 10.1016/j.neubiorev.2012.04.002
[7]  van Ewijk H, Heslenfeld DJ, Zwiers MP, Buitelaar JK, Oosterlaan J (2012) Diffusion tensor imaging in attention deficit/hyperactivity disorder: A systematic review and meta-analysis. Neurosci Biobehav Rev 36: 1093–1106. doi: 10.1016/j.neubiorev.2012.01.003
[8]  Hallowell LM, Stewart SE, de Amorim e Silva CT, Ditchfield MR (2008) Reviewing the process of preparing children for MRI. Pediatr Radiol 38: 271–279. doi: 10.1007/s00247-007-0704-x
[9]  Lawson GR (2000) Controversy: Sedation of children for magnetic resonance imaging. Arch Dis Child 82: 150–154. doi: 10.1136/adc.82.2.150
[10]  Hopkins KL, Davis PC, Sanders CL, Churchill LH (1999) Sedation for pediatric imaging studies. Neuroimaging Clin N Am 9: 1–10.
[11]  DiFrancesco MW, Robertson SA, Karunanayaka P, Holland SK (2013) BOLD fMRI in infants under sedation: Comparing the impact of pentobarbital and propofol on auditory and language activation. J Magn Reson Imaging 38: 1184–1195. doi: 10.1002/jmri.24082
[12]  Raschle N, Zuk J, Ortiz-Mantilla S, Sliva DD, Franceschi A, et al. (2012) Pediatric neuroimaging in early childhood and infancy: Challenges and practical guidelines. Ann N Y Acad Sci 1252: 43–50. doi: 10.1111/j.1749-6632.2012.06457.x
[13]  Raschle N, Chang M, Gaab N (2011) Structural brain alterations associated with dyslexia predate reading onset. 57: 742–749. doi: 10.1016/j.neuroimage.2010.09.055
[14]  de Bie HMA, Boersma M, Wattjes MP, Adriaanse S, Vermeulen RJ, et al. (2010) Preparing children with a mock scanner training protocol results in high quality structural and functional MRI scans. Eur J Pediatr 169: 1079–1085. doi: 10.1007/s00431-010-1181-z
[15]  de Bie HMA, Boersma M, Adriaanse S, Veltman DJ, Wink AM, et al. (2012) Resting-state networks in awake five- to eight-year old children. Hum Brain Mapp 33: 1189–1201. doi: 10.1002/hbm.21280
[16]  Yerys B, Jankowski KF, Shook D, Rosenberger LR, Barnes KA, et al. (2009) The fMRI success rate of children and adolescents: Typical development, epilespy, attention deficit/hyperactivity disorder, and autism spectrum disorders. Hum Brain Mapp 30: 3426–3435. doi: 10.1002/hbm.20767
[17]  Weber Byars A, Holland SK, Strawsburg RH, Bommer W, Dunn RS, et al. (2002) Practical aspects of conducting large-scale functional magnetic resonance imaging studies in children. J Child Neurol 17: 885–889. doi: 10.1177/08830738020170122201
[18]  Klaver P, Lichtensteiger J, Bucher K, Dietrich T, Loenneker T, et al. (2008) Dorsal stream development in motion and structure-from-motion perception. NeuroImage 39: 1815–1823. doi: 10.1016/j.neuroimage.2007.11.009
[19]  Wilke M (2012) An alternative approach towards assessing and accounting for individual motion in fMRI timeseries. NeuroImage 59: 2062–2072. doi: 10.1016/j.neuroimage.2011.10.043
[20]  Satterthwaite TD, Wolf DH, Ruparel K, Erus G, Elliott MA, et al. (2013) Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity in youth. NeuroImage 83: 45–57. doi: 10.1016/j.neuroimage.2013.06.045
[21]  Peeva MG, Tourville JA, Agam Y, Holland B, Manoach DS, et al. (2013) White matter impairment in the speech network in individuals with autism spectrum disorder. Neuroimage Clin 28: 234–41. doi: 10.1016/j.nicl.2013.08.011
[22]  Leemans A, Jeurissen B, Sijbers J, Jones DK (2009) ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. International Society for Magnetic Resonance in Medicine 17th Scientific Meeting, Honolulu, Hawaii 3537.
[23]  Leemans A, Jones DK (2009) The B-matrix must be rotated when correcting for subject motion in DTI data. Magn Reson Med 61: 1336–1349. doi: 10.1002/mrm.21890
[24]  Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, et al. (2004) Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23: 208–219. doi: 10.1016/j.neuroimage.2004.07.051
[25]  Jenkinson M, Bannister P, Brady M, Smith S (2002) Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 17: 825–841. doi: 10.1006/nimg.2002.1132
[26]  Mills KL, Bathula D, Dias TG, Iyer SP, Fenesy MC, et al.. (2012) Altered cortico-striatal-thalamic connectivity in relation to spatial working memory capacity in children with ADHD. Front Psychiatry 3 : Article 2.
[27]  Zhou Z, Liu W, Cui J, Wang X, Arias D, et al. (2011) Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares. NeuroImage 29: 230–242. doi: 10.1016/j.mri.2010.06.022
[28]  Yuan W, Altaye M, Ret J, Schmithorst V, Byars AW, et al. (2009) Quantification of head motion in children during various fMRI language tasks. Hum Brain Mapp 30: 1481–1489. doi: 10.1002/hbm.20616

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