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Characterizing White Matter Tract Organization in Polymicrogyria and Lissencephaly: a Multifiber Diffusion MRI Modeling and Tractography Study

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Characterizing White Matter Tract Organization in Polymicrogyria and Lissencephaly: a Multifiber Diffusion MRI Modeling and Tractography Study ORIGINAL RESEARCH PEDIATRICS Characterizing White Matter Tract Organization in Polymicrogyria and Lissencephaly: A Multifiber Diffusion MRI Modeling and Tractography Study F. Arrigoni, D. Peruzzo, S. Mandelstam, G. Amorosino, D. Redaelli, R. Romaniello, R. Leventer, R. Borgatti, M. Seal, and J.Y.-M. Yang ABSTRACT BACKGROUND AND PURPOSE: Polymicrogyria and lissencephaly may be associated with abnormal organization of the undelying white matter tracts that have been rarely investigated so far. Our aim was to characterize white matter tract organization in poly- microgyria and lissencephaly using constrained spherical deconvolution, a multifiber diffusion MR imaging modeling technique for white matter tractography reconstruction. MATERIALS AND METHODS: We retrospectively reviewed 50 patients (mean age, 8.3 6 5.4 years; range, 1.4–21.2 years; 27 males) with different polymicrogyria (n ¼ 42) and lissencephaly (n ¼ 8) subtypes. The fiber direction-encoded color maps and 6 different white matter tracts reconstructed from each patient were visually compared with corresponding images reconstructed from 7 age- matched, healthy control WM templates. Each white matter tract was assessed by 2 experienced pediatric neuroradiologists and scored in consensus on the basis of the severity of the structural abnormality, ranging from the white matter tracts being absent to thickened. The results were summarized by different polymicrogyria and lissencephaly subgroups. RESULTS: More abnormal-appearing white matter tracts were identified in patients with lissencephaly compared with those with polymi- crogyria (79.2% versus 37.3%). In lissencephaly, structural abnormalities were identified in all studied white matter tracts. In polymicrogy- ria, the more frequently affected white matter tracts were the cingulum, superior longitudinal fasciculus, inferior longitudinal fasciculus, and optic radiation–posterior corona radiata. The severity of superior longitudinal fasciculus and cingulum abnormalities was associated with the polymicrogyria distribution and extent. A thickened superior fronto-occipital fasciculus was demonstrated in 3 patients. CONCLUSIONS: We demonstrated a range of white matter tract structural abnormalities in patients with polymicrogyria and lissen- cephaly. The patterns of white matter tract involvement are related to polymicrogyria and lissencephaly subgroups, distribution, and, possibly, their underlying etiologies. ABBREVIATIONS: CG ¼ cingulum; CMV ¼ cytomegalovirus; CSD ¼ constrained spherical deconvolution; DEC ¼ direction-encoded color; dMRI ¼ diffusion MRI; FOD ¼ fiber orientation distribution; HARDI ¼ high angular resolution diffusion imaging; IFOF ¼ inferior fronto-occipital fasciculus; ILF ¼ inferior longitudi- nal fasciculus; LIS ¼ lissencephaly; MCD ¼ malformation of cortical development; OR-PCR ¼ optic radiation–posterior corona radiata; PMG ¼ polymicrogyria; SBH ¼ subcortical band heterotopia; SFOF ¼ superior fronto-occipital fasciculus/Muratoff bundle; SLF ¼ superior longitudinal fasciculus; WMT ¼ white matter tract Received March 6, 2020; accepted after revision May 11. ages neonate through young adulthood, conducted by the Brain Development fi Cooperative Group and supported by the National Institute of Child Health and Human From the Scienti c Institute, IRCCS E. Medea (F.A., D.P., G.A., D.R., R.R.), Bosisio Parini, Italy; Development, the National Institute on Drug Abuse, the National Institute of Mental Murdoch Children’s Research Institute (S.M., R.L., M.S., J.Y.-M.Y.), Parkville, Australia; ’ Health, and the National Institute of Neurologic Disorders and Stroke (contract Nos. N01- Royal Children s Hospital (S.M., R.L.), Parkville, Australia; Neuroscience Advanced HD02-3343, N01-MH9-0002, and N01-NS-9–2314, À2315, À2316, À2317, À2319 and À2320). Clinical Imaging Suite (NACIS) (J.Y.-M.Y.), Department of Neurosurgery, The Royal fl fl Children’s Hospital, Victoria, Australia; University of Melbourne (S.M., R.L., M.S., This article re ects the views of the authors and may not re ect the opinions or J.Y.-M.Y.), Parkville, Australia; Florey Institute of Neuroscience and Mental Health views of the National Institutes of Health. (S.M.), Parkville, Australia; Bruno Kessler Foundation (G.A.), Trento, Italy; University Data previously presented, in part, as posters at: Annual Meeting of the Organization of Trento, Center for Mind/Brain Sciences (G.A.), Rovereto, Italy; Istituto di for Human Brain Mapping, June 9-13, 2019, Rome, Italy; and the Annual Meeting of the ricovero e cura a carattere scientifico Mondino Foundation (R.B.), Pavia, Italy; and European Society of Neuroradiology, September 19-22, 2019, Oslo, Norway. University of Pavia (R.B.), Pavia, Italy. Please address correspondence to Filippo Arrigoni, MD, Neuroimaging Lab, This study was funded by the Italian Ministry of Health (Ricerca Corrente 2018 and 2019 Scientific Institute IRCCS E. Medea, Via don Luigi Monza 20, 23842, Bosisio Parini, to Drs Arrigoni and Borgatti). Dr Arrigoni was also funded by the Australian Government Italy; e-mail: fi[email protected] through the Endeavor Research Fellowship program 2018 and by “Fondazione Banca del Monte di Lombardia.” Dr Yang was funded by the Royal Columbian Hospital Foundation Indicates open access to non-subscribers at www.ajnr.org (RCH-1000). The research was supported by the Royal Children’s Hospital Foundation, ’ Murdoch Children s Research Institute, The University of Melbourne Department of Indicates article with supplemental on-line appendix and tables. Pediatrics, and the Victorian Government’s Operational Infrastructure Support Program. Data used in the preparation of this article were obtained from the Pediatric MRI Data Indicates article with supplemental on-line photos. Repository created by the National Institutes of Health MRI Study of Normal Brain Development. This is a multisite, longitudinal study of typically developing children, from http://dx.doi.org/10.3174/ajnr.A6646 AJNR Am J Neuroradiol 41:1495–1502 Aug 2020 www.ajnr.org 1495 alformations of cortical development (MCDs) are a Inclusion criteria were the following: 1) radiologic diagno- Mspectrum of brain disorders characterized by neuronal sis of PMG or LIS spectrum (agyria, pachygyria and subcorti- 1 proliferation, neuronal migration, or postmigrational cortical cal band heterotopia [SBH]) made on the basis of screening organization abnormalities occurring during the prenatal pe- the hospital records and confirmed by an experienced pediat- riod.1 Polymicrogyria (PMG) is a class of MCD, characterized ric neuoradiologist (F.A.), who reviewed all MR imaging data; by cortical overfolding and increased gyral and sulcal num- and 2) a 3T MR imaging study including a 3D structural T1- $ bers. Pachygyria and lissencephaly (LIS) are characterized by weighted sequence and a DWI acquisition with 32 diffusion- $ 2 cortical underfolding and reduced gyral and sulcal numbers.1 weighted directions and a b-value 1000 s/mm . Compared with cortical abnormalities, the white matter tract MR imaging data of typically developing children (WMT) organization in MCD is less well-investigated. Con- obtained from the Pediatric MRI Data Repository were used ventional structural MR imaging, such as T1WI and T2WI, is as study control (NIH MRI Study of Normal Brain unable to demonstrate the WMT anatomy. Diffusion MR imag- Development; https://neuroscienceblueprint.nih.gov/resources- 22 ing (dMRI) tractography is currently the only noninvasive imag- tools/nih-mri-study-normal-brain-development). The MR ing technique that can estimate, in vivo, WMTs of the human imaging sequence details are summarized in On-line brain.2 Existing dMRI tractography studies in non-MCD brain Table 1. malformations have demonstrated different patterns of aberrant WM connections in patients sharing similar-appearing malfor- DWI Processing and Tractography Reconstruction mations. These studies help advance our understanding about The DWI data were first preprocessed with Tortoise software 23 the disease pathologic mechanisms3-7 and may aid radiology (Version 3.1.4; https://tortoise.nibib.nih.gov/), corrected for practice.8,9 thermal noise, Gibbs ringing artifacts, motion and eddy current Previous dMRI tractography studies in LIS and PMG distortions, and B1 bias field inhomogeneities. The EPI geometric included only small case series or single case reports.10-17 distortion was corrected using a reversed phase-polarity DWI se- ¼ 2 These studies typically investigated the superior longitudinal ries or b 0s/mm images. fasciculus (SLF), corpus callosum, and corticospinal tract and Voxelwise WM fiber orientation distribution (FOD) was esti- interrogated the association between WMT abnormalities and mated on the basis of the multitissue CSD model using the ¼ language or motor function. No studies additionally charac- MRtrix 3.0 software (www.mrtrix3.org)(lmax 4 for 32-direc- ¼ 24 terized structural abnormalities in other WMTs, such as the tion data; lmax 8 for 60-direction data). FOD-based direc- inferior fronto-occipital fasciculus (IFOF), inferior longitudi- tion-encoded color (DEC) maps were generated using the nal fasciculus (ILF), and optic radiation–posterior corona conventional orientation labels. radiata (OR-PCR). These WMTs are components of the lan- Due to a propensity for a noisier FOD modeling in most ¼ 2 guage and visual-spatial networks.18 Additionally, diffusion cases with b 1100 s/mm data, we elected to perform tractog- tensor imaging was used to model axonal fiber orientations
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