Functional connectivity magnetic resonance imaging classification of autism

被引:296
作者
Anderson, Jeffrey S. [1 ,2 ,3 ,4 ]
Nielsen, Jared A. [2 ,5 ]
Froehlich, Alyson L. [5 ]
DuBray, Molly B. [2 ,5 ]
Druzgal, T. Jason [6 ]
Cariello, Annahir N. [5 ]
Cooperrider, Jason R. [2 ,5 ]
Zielinski, Brandon A. [7 ,8 ]
Ravichandran, Caitlin [9 ,10 ,11 ]
Fletcher, P. Thomas [3 ,12 ,13 ]
Alexander, Andrew L. [14 ,15 ]
Bigler, Erin D. [3 ,16 ,17 ]
Lange, Nicholas [9 ,10 ,11 ]
Lainhart, Janet E. [2 ,3 ,5 ]
机构
[1] Univ Utah, Dept Neuroradiol, Sch Med 1A71, Salt Lake City, UT 84132 USA
[2] Univ Utah, Interdept Program Neurosci, Salt Lake City, UT 84112 USA
[3] Univ Utah, Inst Brain, Salt Lake City, UT 84112 USA
[4] Univ Utah, Dept Bioengn, Salt Lake City, UT 84112 USA
[5] Univ Utah, Dept Psychiat, Salt Lake City, UT 84112 USA
[6] Univ Virginia, Dept Radiol, Charlottesville, VA 22908 USA
[7] Univ Utah, Dept Paediat, Salt Lake City, UT 84112 USA
[8] Univ Utah, Div Child Neurol, Salt Lake City, UT 84112 USA
[9] McLean Hosp, Neurostat Lab, Belmont, MA 02478 USA
[10] Harvard Univ, Sch Publ Hlth, Dept Psychiat, Boston, MA 02115 USA
[11] Harvard Univ, Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USA
[12] Univ Utah, Sch Comp, Salt Lake City, UT 84112 USA
[13] Univ Utah, Sci Comp & Imaging Inst, Salt Lake City, UT 84112 USA
[14] Univ Wisconsin, Waisman Ctr, Waisman Lab Brain Imaging & Behav, Dept Med Phys, Madison, WI 53705 USA
[15] Univ Wisconsin, Waisman Ctr, Waisman Lab Brain Imaging & Behav, Dept Psychiat, Madison, WI 53705 USA
[16] Brigham Young Univ, Dept Psychol, Provo, UT 84602 USA
[17] Brigham Young Univ, Neurosci Ctr, Provo, UT 84602 USA
基金
美国国家卫生研究院;
关键词
autism spectrum disorders; resting state functional MRI; brain development; functional MRI; functional connectivity MRI; SPECTRUM DISORDERS; CORPUS-CALLOSUM; FRONTAL-CORTEX; CORTICAL UNDERCONNECTIVITY; NARRATIVE COMPREHENSION; SENTENCE COMPREHENSION; DEFAULT NETWORK; WORKING-MEMORY; GLOBAL SIGNAL; BRAIN;
D O I
10.1093/brain/awr263
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 x 10(-7)). In subjects < 20 years of age, the classifier performed at 89% accuracy (P = 5.4 x 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects < 20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance > 10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.
引用
收藏
页码:3739 / 3751
页数:13
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