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Identifying relevant biomarkers of brain injury from structural MRI: Validation using automated approaches in children with unilateral cerebral palsy
Previous studies have proposed that the early elucidation of brain injury from structural Magnetic Resonance Images (sMRI) is critical for the clinical assessment of children with cerebral palsy (CP). Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions an...
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| Published in: | PloS one 2017-08, Vol.12 (8), p.e0181605-e0181605 |
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| description | Previous studies have proposed that the early elucidation of brain injury from structural Magnetic Resonance Images (sMRI) is critical for the clinical assessment of children with cerebral palsy (CP). Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions and ventricular enlargement, have been categorised, these injuries are commonly only assessed in a qualitative fashion. As a result, sMRI remains relatively underexploited for clinical assessments, despite its widespread use. In this study, several automated and validated techniques to automatically quantify these three classes of injury were generated in a large cohort of children (n = 139) aged 5-17, including 95 children diagnosed with unilateral CP. Using a feature selection approach on a training data set (n = 97) to find severity of injury biomarkers predictive of clinical function (motor, cognitive, communicative and visual function), cortical shape and regional lesion burden were most often chosen associated with clinical function. Validating the best models on the unseen test data (n = 42), correlation values ranged between 0.545 and 0.795 (p |
| doi_str_mv | 10.1371/journal.pone.0181605 |
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Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions and ventricular enlargement, have been categorised, these injuries are commonly only assessed in a qualitative fashion. As a result, sMRI remains relatively underexploited for clinical assessments, despite its widespread use. In this study, several automated and validated techniques to automatically quantify these three classes of injury were generated in a large cohort of children (n = 139) aged 5-17, including 95 children diagnosed with unilateral CP. Using a feature selection approach on a training data set (n = 97) to find severity of injury biomarkers predictive of clinical function (motor, cognitive, communicative and visual function), cortical shape and regional lesion burden were most often chosen associated with clinical function. Validating the best models on the unseen test data (n = 42), correlation values ranged between 0.545 and 0.795 (p<0.008), indicating significant associations with clinical function. The measured prevalence of injury, including ventricular enlargement (70%), white and grey matter lesions (55%) and cortical malformations (30%), were similar to the prevalence observed in other cohorts of children with unilateral CP. These findings support the early characterisation of injury from sMRI into previously defined aetiologies as part of standard clinical assessment. Furthermore, the strong and significant association between quantifications of injury observed on structural MRI and multiple clinical scores accord with empirically established structure-function relationships.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0181605</identifier><identifier>PMID: 28763455</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Automation ; Biological markers ; Biology and Life Sciences ; Biomarkers ; Brain ; Brain injuries ; Brain Injuries - diagnostic imaging ; Brain Injuries - pathology ; Brain injury ; Brain research ; Cerebral palsy ; Cerebral Palsy - pathology ; Child ; Child, Preschool ; Children ; Cognition & reasoning ; Cognitive ability ; Cohort Studies ; Cortex ; Diagnosis ; Enlargement ; Female ; Gray Matter - pathology ; Head injuries ; Health aspects ; Humans ; Image Processing, Computer-Assisted ; Lesions ; Magnetic resonance ; Magnetic Resonance Imaging ; Male ; Medical research ; Medicine and Health Sciences ; Motor task performance ; NMR ; Nuclear magnetic resonance ; Paralysis ; Pediatrics ; People and Places ; Reproducibility of Results ; Research and Analysis Methods ; Sensorimotor integration ; Social Sciences ; Structure-Activity Relationship ; Structure-function relationships ; Substantia grisea ; Traumatic brain injury ; Ventricle ; Visual perception ; White Matter - pathology</subject><ispartof>PloS one, 2017-08, Vol.12 (8), p.e0181605-e0181605</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Pagnozzi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Furthermore, the strong and significant association between quantifications of injury observed on structural MRI and multiple clinical scores accord with empirically established structure-function relationships.</description><subject>Adolescent</subject><subject>Automation</subject><subject>Biological markers</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Brain</subject><subject>Brain injuries</subject><subject>Brain Injuries - diagnostic imaging</subject><subject>Brain Injuries - pathology</subject><subject>Brain injury</subject><subject>Brain research</subject><subject>Cerebral palsy</subject><subject>Cerebral Palsy - pathology</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Children</subject><subject>Cognition & reasoning</subject><subject>Cognitive ability</subject><subject>Cohort Studies</subject><subject>Cortex</subject><subject>Diagnosis</subject><subject>Enlargement</subject><subject>Female</subject><subject>Gray Matter - 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Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions and ventricular enlargement, have been categorised, these injuries are commonly only assessed in a qualitative fashion. As a result, sMRI remains relatively underexploited for clinical assessments, despite its widespread use. In this study, several automated and validated techniques to automatically quantify these three classes of injury were generated in a large cohort of children (n = 139) aged 5-17, including 95 children diagnosed with unilateral CP. Using a feature selection approach on a training data set (n = 97) to find severity of injury biomarkers predictive of clinical function (motor, cognitive, communicative and visual function), cortical shape and regional lesion burden were most often chosen associated with clinical function. Validating the best models on the unseen test data (n = 42), correlation values ranged between 0.545 and 0.795 (p<0.008), indicating significant associations with clinical function. The measured prevalence of injury, including ventricular enlargement (70%), white and grey matter lesions (55%) and cortical malformations (30%), were similar to the prevalence observed in other cohorts of children with unilateral CP. These findings support the early characterisation of injury from sMRI into previously defined aetiologies as part of standard clinical assessment. Furthermore, the strong and significant association between quantifications of injury observed on structural MRI and multiple clinical scores accord with empirically established structure-function relationships.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28763455</pmid><doi>10.1371/journal.pone.0181605</doi><tpages>e0181605</tpages><orcidid>https://orcid.org/0000-0001-7931-1204</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | PloS one, 2017-08, Vol.12 (8), p.e0181605-e0181605 |
| issn | 1932-6203 1932-6203 |
| language | eng |
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| source | Publicly Available Content Database (Proquest) (PQ_SDU_P3); PubMed Central Free |
| subjects | Adolescent Automation Biological markers Biology and Life Sciences Biomarkers Brain Brain injuries Brain Injuries - diagnostic imaging Brain Injuries - pathology Brain injury Brain research Cerebral palsy Cerebral Palsy - pathology Child Child, Preschool Children Cognition & reasoning Cognitive ability Cohort Studies Cortex Diagnosis Enlargement Female Gray Matter - pathology Head injuries Health aspects Humans Image Processing, Computer-Assisted Lesions Magnetic resonance Magnetic Resonance Imaging Male Medical research Medicine and Health Sciences Motor task performance NMR Nuclear magnetic resonance Paralysis Pediatrics People and Places Reproducibility of Results Research and Analysis Methods Sensorimotor integration Social Sciences Structure-Activity Relationship Structure-function relationships Substantia grisea Traumatic brain injury Ventricle Visual perception White Matter - pathology |
| title | Identifying relevant biomarkers of brain injury from structural MRI: Validation using automated approaches in children with unilateral cerebral palsy |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T16%3A42%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Identifying%20relevant%20biomarkers%20of%20brain%20injury%20from%20structural%20MRI:%20Validation%20using%20automated%20approaches%20in%20children%20with%20unilateral%20cerebral%20palsy&rft.jtitle=PloS%20one&rft.au=Pagnozzi,%20Alex%20M&rft.date=2017-08-01&rft.volume=12&rft.issue=8&rft.spage=e0181605&rft.epage=e0181605&rft.pages=e0181605-e0181605&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0181605&rft_dat=%3Cgale_plos_%3EA499700393%3C/gale_plos_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c692t-a29a4ea844e6b4392d29e62faa018178d2cbf187716a4b6d09ef1517493f23853%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1925201439&rft_id=info:pmid/28763455&rft_galeid=A499700393&rfr_iscdi=true |