Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease
Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic...
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| Veröffentlicht in: | Brain (London, England : 1878) England : 1878), 2009-08, Vol.132 (8), p.2048-2057 |
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| creator | Desikan, Rahul S. Cabral, Howard J. Hess, Christopher P. Dillon, William P. Glastonbury, Christine M. Weiner, Michael W. Schmansky, Nicholas J. Greve, Douglas N. Salat, David H. Buckner, Randy L. Fischl, Bruce |
| description | Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease. |
| doi_str_mv | 10.1093/brain/awp123 |
| format | Article |
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Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.</description><identifier>ISSN: 0006-8950</identifier><identifier>EISSN: 1460-2156</identifier><identifier>DOI: 10.1093/brain/awp123</identifier><identifier>PMID: 19460794</identifier><identifier>CODEN: BRAIAK</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Adolescent ; Adult ; Aged ; Aged, 80 and over ; Alzheimer Disease - diagnosis ; Alzheimer Disease - pathology ; Alzheimer Disease - psychology ; Alzheimer's disease ; Biological and medical sciences ; Biomarkers - cerebrospinal fluid ; Brain Mapping - methods ; Cerebral Cortex - pathology ; Cognition Disorders - diagnosis ; Cognition Disorders - etiology ; Cognition Disorders - pathology ; Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases ; diagnostic marker ; Disease Progression ; Early Diagnosis ; Epidemiologic Methods ; Female ; Humans ; Image Interpretation, Computer-Assisted - methods ; Magnetic Resonance Imaging - methods ; Male ; Medical sciences ; Middle Aged ; mild cognitive impairment ; MRI ; Neurology ; Neuropsychological Tests ; Original ; Prognosis ; Young Adult</subject><ispartof>Brain (London, England : 1878), 2009-08, Vol.132 (8), p.2048-2057</ispartof><rights>2009 The Author(s) 2009</rights><rights>2009 INIST-CNRS</rights><rights>2009 The Author(s)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-bbc1352fc0a94f0b61b5ba001bb9b25c5d2805f681762857e5af9516b56a35083</citedby><cites>FETCH-LOGICAL-c540t-bbc1352fc0a94f0b61b5ba001bb9b25c5d2805f681762857e5af9516b56a35083</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,1584,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21766772$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19460794$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Desikan, Rahul S.</creatorcontrib><creatorcontrib>Cabral, Howard J.</creatorcontrib><creatorcontrib>Hess, Christopher P.</creatorcontrib><creatorcontrib>Dillon, William P.</creatorcontrib><creatorcontrib>Glastonbury, Christine M.</creatorcontrib><creatorcontrib>Weiner, Michael W.</creatorcontrib><creatorcontrib>Schmansky, Nicholas J.</creatorcontrib><creatorcontrib>Greve, Douglas N.</creatorcontrib><creatorcontrib>Salat, David H.</creatorcontrib><creatorcontrib>Buckner, Randy L.</creatorcontrib><creatorcontrib>Fischl, Bruce</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><title>Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease</title><title>Brain (London, England : 1878)</title><addtitle>Brain</addtitle><description>Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Alzheimer Disease - diagnosis</subject><subject>Alzheimer Disease - pathology</subject><subject>Alzheimer Disease - psychology</subject><subject>Alzheimer's disease</subject><subject>Biological and medical sciences</subject><subject>Biomarkers - cerebrospinal fluid</subject><subject>Brain Mapping - methods</subject><subject>Cerebral Cortex - pathology</subject><subject>Cognition Disorders - diagnosis</subject><subject>Cognition Disorders - etiology</subject><subject>Cognition Disorders - pathology</subject><subject>Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases</subject><subject>diagnostic marker</subject><subject>Disease Progression</subject><subject>Early Diagnosis</subject><subject>Epidemiologic Methods</subject><subject>Female</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>mild cognitive impairment</subject><subject>MRI</subject><subject>Neurology</subject><subject>Neuropsychological Tests</subject><subject>Original</subject><subject>Prognosis</subject><subject>Young Adult</subject><issn>0006-8950</issn><issn>1460-2156</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNqF0Utv1DAUBWALgehQ2LFGFhJ0Q6jt-BFvkEYVpRVFSLzFxrIdp3PbPAY7mVJ-PYaMhsemKy_y5fj6HoQeUvKcEl0eumihP7RXa8rKW2hBuSQFo0LeRgtCiCwqLcgeupfSBSGUl0zeRXtUZ6U0XyC3nMahs2Oo8Zt3p7gLNk0xJAx16EdorjH0NWygnmyb8BWMK9xBW2M_nPcwwiZg6NYWYpc1tn2Nl-2PVYAuxIOEa0g5LtxHd5r8d3iwPffRx-OXH45OirO3r06PlmeFF5yMhXOeloI1nljNG-IkdcLZPLNz2jHhRc0qIhpZUSVZJVQQttGCSiekLQWpyn30Ys5dT64Ltc8jRduadYTOxmszWDD_fulhZc6HjWGKciJpDni6DYjDtymk0XSQfGhb24dhSkYqQbSu1I2QEaU4YSLDx__Bi2GKfd6CoVrwUiglM3o2Ix-HlGJodiNTYn5VbH5XbOaKM3_09zP_4G2nGTzZApu8bZtoew9p51jen1SKZXcwu2Fa33RlMUtIY_i-szZe5p2USpiTL18N4Z_459fH0rwvfwKOR842</recordid><startdate>20090801</startdate><enddate>20090801</enddate><creator>Desikan, Rahul S.</creator><creator>Cabral, Howard J.</creator><creator>Hess, Christopher P.</creator><creator>Dillon, William P.</creator><creator>Glastonbury, Christine M.</creator><creator>Weiner, Michael W.</creator><creator>Schmansky, Nicholas J.</creator><creator>Greve, Douglas N.</creator><creator>Salat, David H.</creator><creator>Buckner, Randy L.</creator><creator>Fischl, Bruce</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>BSCLL</scope><scope>TOX</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20090801</creationdate><title>Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease</title><author>Desikan, Rahul S. ; Cabral, Howard J. ; Hess, Christopher P. ; Dillon, William P. ; Glastonbury, Christine M. ; Weiner, Michael W. ; Schmansky, Nicholas J. ; Greve, Douglas N. ; Salat, David H. ; Buckner, Randy L. ; Fischl, Bruce</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-bbc1352fc0a94f0b61b5ba001bb9b25c5d2805f681762857e5af9516b56a35083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Alzheimer Disease - diagnosis</topic><topic>Alzheimer Disease - pathology</topic><topic>Alzheimer Disease - psychology</topic><topic>Alzheimer's disease</topic><topic>Biological and medical sciences</topic><topic>Biomarkers - cerebrospinal fluid</topic><topic>Brain Mapping - methods</topic><topic>Cerebral Cortex - pathology</topic><topic>Cognition Disorders - diagnosis</topic><topic>Cognition Disorders - etiology</topic><topic>Cognition Disorders - pathology</topic><topic>Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases</topic><topic>diagnostic marker</topic><topic>Disease Progression</topic><topic>Early Diagnosis</topic><topic>Epidemiologic Methods</topic><topic>Female</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>mild cognitive impairment</topic><topic>MRI</topic><topic>Neurology</topic><topic>Neuropsychological Tests</topic><topic>Original</topic><topic>Prognosis</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Desikan, Rahul S.</creatorcontrib><creatorcontrib>Cabral, Howard J.</creatorcontrib><creatorcontrib>Hess, Christopher P.</creatorcontrib><creatorcontrib>Dillon, William P.</creatorcontrib><creatorcontrib>Glastonbury, Christine M.</creatorcontrib><creatorcontrib>Weiner, Michael W.</creatorcontrib><creatorcontrib>Schmansky, Nicholas J.</creatorcontrib><creatorcontrib>Greve, Douglas N.</creatorcontrib><creatorcontrib>Salat, David H.</creatorcontrib><creatorcontrib>Buckner, Randy L.</creatorcontrib><creatorcontrib>Fischl, Bruce</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><creatorcontrib>Alzheimer's Disease Neuroimaging Initiative</creatorcontrib><collection>Istex</collection><collection>Oxford Journals Open Access Collection</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Brain (London, England : 1878)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Desikan, Rahul S.</au><au>Cabral, Howard J.</au><au>Hess, Christopher P.</au><au>Dillon, William P.</au><au>Glastonbury, Christine M.</au><au>Weiner, Michael W.</au><au>Schmansky, Nicholas J.</au><au>Greve, Douglas N.</au><au>Salat, David H.</au><au>Buckner, Randy L.</au><au>Fischl, Bruce</au><aucorp>Alzheimer's Disease Neuroimaging Initiative</aucorp><aucorp>Alzheimer's Disease Neuroimaging Initiative</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease</atitle><jtitle>Brain (London, England : 1878)</jtitle><addtitle>Brain</addtitle><date>2009-08-01</date><risdate>2009</risdate><volume>132</volume><issue>8</issue><spage>2048</spage><epage>2057</epage><pages>2048-2057</pages><issn>0006-8950</issn><eissn>1460-2156</eissn><coden>BRAIAK</coden><abstract>Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><pmid>19460794</pmid><doi>10.1093/brain/awp123</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; Oxford University Press Journals All Titles (1996-Current); EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Adolescent Adult Aged Aged, 80 and over Alzheimer Disease - diagnosis Alzheimer Disease - pathology Alzheimer Disease - psychology Alzheimer's disease Biological and medical sciences Biomarkers - cerebrospinal fluid Brain Mapping - methods Cerebral Cortex - pathology Cognition Disorders - diagnosis Cognition Disorders - etiology Cognition Disorders - pathology Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases diagnostic marker Disease Progression Early Diagnosis Epidemiologic Methods Female Humans Image Interpretation, Computer-Assisted - methods Magnetic Resonance Imaging - methods Male Medical sciences Middle Aged mild cognitive impairment MRI Neurology Neuropsychological Tests Original Prognosis Young Adult |
| title | Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease |
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