Cargando…
Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder
Atypical eye gaze is an established clinical sign in the diagnosis of autism spectrum disorder (ASD). We propose a computerized diagnostic algorithm for ASD, applicable to children and adolescents aged between 5 and 17 years using Gazefinder, a system where a set of devices to capture eye gaze patte...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876254/ https://www.ncbi.nlm.nih.gov/pubmed/33584502 http://dx.doi.org/10.3389/fneur.2020.603085 |
_version_ | 1783649932783124480 |
---|---|
author | Tsuchiya, Kenji J. Hakoshima, Shuji Hara, Takeshi Ninomiya, Masaru Saito, Manabu Fujioka, Toru Kosaka, Hirotaka Hirano, Yoshiyuki Matsuo, Muneaki Kikuchi, Mitsuru Maegaki, Yoshihiro Harada, Taeko Nishimura, Tomoko Katayama, Taiichi |
author_facet | Tsuchiya, Kenji J. Hakoshima, Shuji Hara, Takeshi Ninomiya, Masaru Saito, Manabu Fujioka, Toru Kosaka, Hirotaka Hirano, Yoshiyuki Matsuo, Muneaki Kikuchi, Mitsuru Maegaki, Yoshihiro Harada, Taeko Nishimura, Tomoko Katayama, Taiichi |
author_sort | Tsuchiya, Kenji J. |
collection | PubMed |
description | Atypical eye gaze is an established clinical sign in the diagnosis of autism spectrum disorder (ASD). We propose a computerized diagnostic algorithm for ASD, applicable to children and adolescents aged between 5 and 17 years using Gazefinder, a system where a set of devices to capture eye gaze patterns and stimulus movie clips are equipped in a personal computer with a monitor. We enrolled 222 individuals aged 5–17 years at seven research facilities in Japan. Among them, we extracted 39 individuals with ASD without any comorbid neurodevelopmental abnormalities (ASD group), 102 typically developing individuals (TD group), and an independent sample of 24 individuals (the second control group). All participants underwent psychoneurological and diagnostic assessments, including the Autism Diagnostic Observation Schedule, second edition, and an examination with Gazefinder (2 min). To enhance the predictive validity, a best-fit diagnostic algorithm of computationally selected attributes originally extracted from Gazefinder was proposed. The inputs were classified automatically into either ASD or TD groups, based on the attribute values. We cross-validated the algorithm using the leave-one-out method in the ASD and TD groups and tested the predictability in the second control group. The best-fit algorithm showed an area under curve (AUC) of 0.84, and the sensitivity, specificity, and accuracy were 74, 80, and 78%, respectively. The AUC for the cross-validation was 0.74 and that for validation in the second control group was 0.91. We confirmed that the diagnostic performance of the best-fit algorithm is comparable to the diagnostic assessment tools for ASD. |
format | Online Article Text |
id | pubmed-7876254 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78762542021-02-12 Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder Tsuchiya, Kenji J. Hakoshima, Shuji Hara, Takeshi Ninomiya, Masaru Saito, Manabu Fujioka, Toru Kosaka, Hirotaka Hirano, Yoshiyuki Matsuo, Muneaki Kikuchi, Mitsuru Maegaki, Yoshihiro Harada, Taeko Nishimura, Tomoko Katayama, Taiichi Front Neurol Neurology Atypical eye gaze is an established clinical sign in the diagnosis of autism spectrum disorder (ASD). We propose a computerized diagnostic algorithm for ASD, applicable to children and adolescents aged between 5 and 17 years using Gazefinder, a system where a set of devices to capture eye gaze patterns and stimulus movie clips are equipped in a personal computer with a monitor. We enrolled 222 individuals aged 5–17 years at seven research facilities in Japan. Among them, we extracted 39 individuals with ASD without any comorbid neurodevelopmental abnormalities (ASD group), 102 typically developing individuals (TD group), and an independent sample of 24 individuals (the second control group). All participants underwent psychoneurological and diagnostic assessments, including the Autism Diagnostic Observation Schedule, second edition, and an examination with Gazefinder (2 min). To enhance the predictive validity, a best-fit diagnostic algorithm of computationally selected attributes originally extracted from Gazefinder was proposed. The inputs were classified automatically into either ASD or TD groups, based on the attribute values. We cross-validated the algorithm using the leave-one-out method in the ASD and TD groups and tested the predictability in the second control group. The best-fit algorithm showed an area under curve (AUC) of 0.84, and the sensitivity, specificity, and accuracy were 74, 80, and 78%, respectively. The AUC for the cross-validation was 0.74 and that for validation in the second control group was 0.91. We confirmed that the diagnostic performance of the best-fit algorithm is comparable to the diagnostic assessment tools for ASD. Frontiers Media S.A. 2021-01-28 /pmc/articles/PMC7876254/ /pubmed/33584502 http://dx.doi.org/10.3389/fneur.2020.603085 Text en Copyright © 2021 Tsuchiya, Hakoshima, Hara, Ninomiya, Saito, Fujioka, Kosaka, Hirano, Matsuo, Kikuchi, Maegaki, Harada, Nishimura and Katayama. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Tsuchiya, Kenji J. Hakoshima, Shuji Hara, Takeshi Ninomiya, Masaru Saito, Manabu Fujioka, Toru Kosaka, Hirotaka Hirano, Yoshiyuki Matsuo, Muneaki Kikuchi, Mitsuru Maegaki, Yoshihiro Harada, Taeko Nishimura, Tomoko Katayama, Taiichi Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder |
title | Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder |
title_full | Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder |
title_fullStr | Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder |
title_full_unstemmed | Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder |
title_short | Diagnosing Autism Spectrum Disorder Without Expertise: A Pilot Study of 5- to 17-Year-Old Individuals Using Gazefinder |
title_sort | diagnosing autism spectrum disorder without expertise: a pilot study of 5- to 17-year-old individuals using gazefinder |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876254/ https://www.ncbi.nlm.nih.gov/pubmed/33584502 http://dx.doi.org/10.3389/fneur.2020.603085 |
work_keys_str_mv | AT tsuchiyakenjij diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT hakoshimashuji diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT haratakeshi diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT ninomiyamasaru diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT saitomanabu diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT fujiokatoru diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT kosakahirotaka diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT hiranoyoshiyuki diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT matsuomuneaki diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT kikuchimitsuru diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT maegakiyoshihiro diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT haradataeko diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT nishimuratomoko diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder AT katayamataiichi diagnosingautismspectrumdisorderwithoutexpertiseapilotstudyof5to17yearoldindividualsusinggazefinder |