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Study combines neuroimaging with machine learning to predict, with 96% accuracy, whether high-risk 6‑month-old babies will develop autism spectrum disorder (ASD) by age 2

Researchers use brain imag­ing and machine learn­ing to pre­dict which high-risk infants will devel­op autism. Cred­it: Car­oli­na Insti­tute for Devel­op­men­tal Dis­abil­i­ties.

A Sin­gle Brain Scan Has Been Used to Accu­rate­ly Pre­dict Autism at Just 6 Months Old (Sci­ence alert)

Researchers have used brain scans and arti­fi­cial intel­li­gence to spot dif­fer­ences in how key areas of infant brains syn­chro­nise, allow­ing them to accu­rate­ly pre­dict which babies would devel­op autism spec­trum dis­or­der (ASD) as a toddler…The research, led by sci­en­tists from the Uni­ver­si­ty of North Car­oli­na at  Chapel Hill and Wash­ing­ton Uni­ver­si­ty, comes hot on the heels of an ear­li­er study that used two scans tak­en at 6 and 12 months to make a sim­i­lar pre­dic­tion.

Not only has this new method reduced the num­ber of scans required to make the judge­ment, they were able to pre­dict with more than 96 per­cent accu­ra­cy which 6 month old infants would be diag­nosed with autism by age 2, com­pared to 81 per­cent previously…The researchers used mag­net­ic res­o­nance imag­ing to analyse the neur­al activ­i­ty of 230 regions across the brain in 59 infants who had at least one old­er sib­ling with a diag­no­sis of ASD…

A larg­er sam­ple size and more data will no doubt help deter­mine just how accu­rate this method of diag­no­sis could be in the long term, which is what the researchers are plan­ning next.

It’s also unlike­ly that a sin­gle test will form the basis of any future diag­noses – more like­ly, it would form one piece in a risk pro­file informed by research involv­ing a vari­ety of eval­u­a­tions.”

The Study

Func­tion­al neu­roimag­ing of high-risk 6‑month-old infants pre­dicts a diag­no­sis of autism at 24 months of age (Sci­ence Trans­la­tion­al Med­i­cine)

  • Sum­ma­ry: In a new study, Emer­son et al. show that brain func­tion in infan­cy can be used to accu­rate­ly pre­dict which high-risk infants will lat­er receive an autism diag­no­sis. Using machine learn­ing tech­niques that iden­ti­fy pat­terns in the brain’s func­tion­al con­nec­tions, Emer­son and col­leagues were able to pre­dict with greater than 96% accu­ra­cy whether a 6‑month-old infant would devel­op autism at 24 months of age. These find­ings must be repli­cat­ed, but they rep­re­sent an impor­tant step toward the ear­ly iden­ti­fi­ca­tion of indi­vid­u­als with autism before its char­ac­ter­is­tic symp­toms devel­op.
  • Abstract: Autism spec­trum dis­or­der (ASD) is a neu­rode­vel­op­men­tal dis­or­der char­ac­ter­ized by social deficits and repet­i­tive behav­iors that typ­i­cal­ly emerge by 24 months of age. To devel­op effec­tive ear­ly inter­ven­tions that can poten­tial­ly ame­lio­rate the defin­ing deficits of ASD and improve long-term out­comes, ear­ly detec­tion is essen­tial. Using prospec­tive neu­roimag­ing of 59 6‑month-old infants with a high famil­ial risk for ASD, we show that func­tion­al con­nec­tiv­i­ty mag­net­ic res­o­nance imag­ing cor­rect­ly iden­ti­fied which indi­vid­ual chil­dren would receive a research clin­i­cal best-esti­mate diag­no­sis of ASD at 24 months of age. Func­tion­al brain con­nec­tions were defined in 6‑month-old infants that cor­re­lat­ed with 24-month scores on mea­sures of social behav­ior, lan­guage, motor devel­op­ment, and repet­i­tive behav­ior, which are all fea­tures com­mon to the diag­no­sis of ASD. A ful­ly cross-val­i­dat­ed machine learn­ing algo­rithm applied at age 6 months had a pos­i­tive pre­dic­tive val­ue of 100% [95% con­fi­dence inter­val (CI), 62.9 to 100], cor­rect­ly pre­dict­ing 9 of 11 infants who received a diag­no­sis of ASD at 24 months (sen­si­tiv­i­ty, 81.8%; 95% CI, 47.8 to 96.8). All 48 6‑month-old infants who were not diag­nosed with ASD were cor­rect­ly clas­si­fied [speci­fici­ty, 100% (95% CI, 90.8 to 100); neg­a­tive pre­dic­tive val­ue, 96.0% (95% CI, 85.1 to 99.3)]. These find­ings have clin­i­cal impli­ca­tions for ear­ly risk assess­ment and the fea­si­bil­i­ty of devel­op­ing ear­ly pre­ven­ta­tive inter­ven­tions for ASD.

The Study and Innovation in Context

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As seen in The New York Times, The Wall Street Journal, BBC News, CNN, Reuters,  SharpBrains is an independent market research firm tracking how brain science can improve our health and our lives.

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