Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging

被引:5
作者
Arai, Takashi [1 ]
Kamagata, Koji [2 ]
Uchida, Wataru [1 ]
Andica, Christina [1 ,2 ]
Takabayashi, Kaito [1 ]
Saito, Yuya [1 ]
Tuerxun, Rukeye [1 ]
Mahemuti, Zaimire [1 ]
Morita, Yuichi [1 ,3 ]
Irie, Ryusuke [1 ]
Kirino, Eiji [4 ,5 ]
Aoki, Shigeki [1 ]
机构
[1] Juntendo Univ, Dept Radiol, Grad Sch Med, Tokyo, Japan
[2] Juntendo Univ, Fac Hlth Data Sci, Chiba, Japan
[3] Univ Tokyo, Grad Sch Med, Dept Radiol, Tokyo, Japan
[4] Juntendo Univ, Grad Sch Med, Dept Psychiat, Tokyo, Japan
[5] Juntendo Univ, Shizuoka Hosp, Dept Psychiat, Shizuoka, Japan
基金
日本学术振兴会;
关键词
autism; diffusion-weighted imaging; diffusion tensor imaging; gray matter; neurite orientation dispersion and density imaging; neuronal loss; surface-based cortical thickness measurement; HIGH-FUNCTIONING AUTISM; WHITE-MATTER; PARKINSONS-DISEASE; SPATIAL STATISTICS; SPECTRUM DISORDER; ASPERGER-SYNDROME; FRONTAL-LOBE; DIFFUSION; ABNORMALITIES; MICROSTRUCTURE;
D O I
10.3389/fneur.2023.1110883
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
BackgroundCore symptoms of autism-spectrum disorder (ASD) have been associated with prefrontal cortex abnormalities. However, the mechanisms behind the observation remain incomplete, partially due to the challenges of modeling complex gray matter (GM) structures. This study aimed to identify GM microstructural alterations in adults with ASD using neurite orientation dispersion and density imaging (NODDI) and voxel-wise GM-based spatial statistics (GBSS) to reduce the partial volume effects from the white matter and cerebrospinal fluid.Materials and methodsA total of 48 right-handed participants were included, of which 22 had ASD (17 men; mean age, 34.42 & PLUSMN; 8.27 years) and 26 were typically developing (TD) individuals (14 men; mean age, 32.57 & PLUSMN; 9.62 years). The metrics of NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) were compared between groups using GBSS. Diffusion tensor imaging (DTI) metrics and surface-based cortical thickness were also compared. The associations between magnetic resonance imaging-based measures and ASD-related scores, including ASD-spectrum quotient, empathizing quotient, and systemizing quotient were also assessed in the region of interest (ROI) analysis.ResultsAfter controlling for age, sex, and intracranial volume, GBSS demonstrated significantly lower NDI in the ASD group than in the TD group in the left prefrontal cortex (caudal middle frontal, lateral orbitofrontal, pars orbitalis, pars triangularis, rostral middle frontal, and superior frontal region). In the ROI analysis of individuals with ASD, a significantly positive correlation was observed between the NDI in the left rostral middle frontal, superior frontal, and left frontal pole and empathizing quotient score. No significant between-group differences were observed in all DTI metrics, other NODDI (i.e., ODI and ISOVF) metrics, and cortical thickness.ConclusionGBSS analysis was used to demonstrate the ability of NODDI metrics to detect GM microstructural alterations in adults with ASD, while no changes were detected using DTI and cortical thickness evaluation. Specifically, we observed a reduced neurite density index in the left prefrontal cortices associated with reduced empathic abilities.
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页数:11
相关论文
共 65 条
[1]   Analysis of partial volume effects in diffusion-tensor MRI [J].
Alexander, AL ;
Hasan, KM ;
Lazar, M ;
Tsuruda, JS ;
Parker, DL .
MAGNETIC RESONANCE IN MEDICINE, 2001, 45 (05) :770-780
[2]   Diffusion tensor imaging of the corpus callosum in Autism [J].
Alexander, Andrew L. ;
Lee, Jee Eun ;
Lazar, Mariana ;
Boudos, Rebecca ;
DuBray, Molly B. ;
Oakes, Terrence R. ;
Miller, Judith N. ;
Lu, Jeffrey ;
Jeong, Eun-Kee ;
McMahon, William M. ;
Bigler, Erin D. ;
Lainhart, Janet E. .
NEUROIMAGE, 2007, 34 (01) :61-73
[3]   Orientationally invariant indices of axon diameter and density from diffusion MRI [J].
Alexander, Daniel C. ;
Hubbard, Penny L. ;
Hall, Matt G. ;
Moore, Elizabeth A. ;
Ptito, Maurice ;
Parker, Geoff J. M. ;
Dyrby, Tim B. .
NEUROIMAGE, 2010, 52 (04) :1374-1389
[4]   Altered white matter connectivity as a neural substrate for social impairment in Autism Spectrum Disorder [J].
Ameis, Stephanie H. ;
Catani, Marco .
CORTEX, 2015, 62 :158-181
[5]   An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging [J].
Andersson, Jesper L. R. ;
Sotiropoulos, Stamatios N. .
NEUROIMAGE, 2016, 125 :1063-1078
[6]   Multimodal magnetic resonance imaging quantification of gray matter alterations in relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorder [J].
Andica, Christina ;
Hagiwara, Akifumi ;
Yokoyama, Kazumasa ;
Kato, Shimpei ;
Uchida, Wataru ;
Nishimura, Yuma ;
Fujita, Shohei ;
Kamagata, Koji ;
Hori, Masaaki ;
Tomizawa, Yuji ;
Hattori, Nobutaka ;
Aoki, Shigeki .
JOURNAL OF NEUROSCIENCE RESEARCH, 2022, 100 (07) :1395-1412
[7]   Neurite orientation dispersion and density imaging reveals white matter microstructural alterations in adults with autism [J].
Andica, Christina ;
Kamagata, Koji ;
Kirino, Eiji ;
Uchida, Wataru ;
Irie, Ryusuke ;
Murata, Syo ;
Aoki, Shigeki .
MOLECULAR AUTISM, 2021, 12 (01)
[8]   Gray Matter Alterations in Early and Late Relapsing-Remitting Multiple Sclerosis Evaluated with Synthetic Quantitative Magnetic Resonance Imaging [J].
Andica, Christina ;
Hagiwara, Akifumi ;
Kamagata, Koji ;
Yokoyama, Kazumasa ;
Shimoji, Keigo ;
Saito, Asami ;
Takenaka, Yuki ;
Nakazawa, Misaki ;
Hori, Masaaki ;
Cohen-Adad, Julien ;
Takemura, Mariko Yoshida ;
Hattori, Nobutaka ;
Aoki, Shigeki .
SCIENTIFIC REPORTS, 2019, 9 (1)
[9]  
[Anonymous], 2000, Diagnostic and statistical manual of mental disorders: DSM-5, V4th, DOI DOI 10.1176/APPI.BOOKS.9780890425596
[10]   Methodological considerations on tract-based spatial statistics (TBSS) [J].
Bach, Michael ;
Laun, Frederik B. ;
Leemans, Alexander ;
Tax, Chantal M. W. ;
Biessels, Geert J. ;
Stieltjes, Bram ;
Maier-Hein, Klaus H. .
NEUROIMAGE, 2014, 100 :358-369