Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty
Background International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages. Objectives To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or ma...
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| creator | Chougar, Lydia Faucher, Alice Faouzi, Johann Lejeune, François‐Xavier Gama Lobo, Gonçalo Jovanovic, Carna Cormier, Florence Dupont, Gwendoline Vidailhet, Marie Corvol, Jean‐Christophe Colliot, Olivier Lehéricy, Stéphane Grabli, David Degos, Bertrand |
| description | Background
International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages.
Objectives
To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine‐learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism.
Materials
Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2‐year follow‐up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 (“Clin1”); (2) MRI visual reading blinded to the clinical diagnosis (“MRI”); (3) both MRI visual reading and clinical criteria at V1 (“MRI and Clin1”), and (4) a machine‐learning algorithm (“Algorithm”). The gold standard diagnosis was established by expert consensus after a 2‐year follow‐up.
Results
We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit (“Clin1”: balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% (“MRI”: 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit (“MRI and Clin1”: 85.4%; P |
| doi_str_mv | 10.1002/mds.29760 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_04675671v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2958301252</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4220-5ff6349c4f792faed006a30b492d757a1ff300fef974bfbe52703af1a68e3f073</originalsourceid><addsrcrecordid>eNp10U1PHCEYB3DStKnr2kO_gCHppR5GH2AYmKNZtWuypo0vZ8LMgovOgAVGs9--s11fEhNPBPjlz0P-CH0ncEgA6FG_TIe0FhV8QhPCGSkk5eIzmoCUvGBE8h20m9IdACGcVF_RDpOlrErKJqidBZ-ja4bsgsfB4ovLc2xDxHll8KmO3RqfOH3rQ3Jpc_1Hx3vnU_Au9dj5cZ-d8TnhJ5dXLzS7Ft_41sSsnc_rPfTF6i6Zb8_rFN2cnV7P5sXi96_z2fGiaEtKoeDWVqys29KKmlptlgCVZtCUNV0KLjSxlgFYY2tRNrYxnApg2hJdScMsCDZFB9vcle7UQ3S9jmsVtFPz44XanEFZCV4J8khG-3NrH2L4O5iUVe9Sa7pOexOGpGjNJQNCOR3pj3f0LgzRjz9RDPjIiKzl2-NtDClFY18nIKA2LamxJfW_pdHuPycOTW-Wr_KllhEcbcGT68z64yR1cXK1jfwHL0eaow</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3055831898</pqid></control><display><type>article</type><title>Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Chougar, Lydia ; Faucher, Alice ; Faouzi, Johann ; Lejeune, François‐Xavier ; Gama Lobo, Gonçalo ; Jovanovic, Carna ; Cormier, Florence ; Dupont, Gwendoline ; Vidailhet, Marie ; Corvol, Jean‐Christophe ; Colliot, Olivier ; Lehéricy, Stéphane ; Grabli, David ; Degos, Bertrand</creator><creatorcontrib>Chougar, Lydia ; Faucher, Alice ; Faouzi, Johann ; Lejeune, François‐Xavier ; Gama Lobo, Gonçalo ; Jovanovic, Carna ; Cormier, Florence ; Dupont, Gwendoline ; Vidailhet, Marie ; Corvol, Jean‐Christophe ; Colliot, Olivier ; Lehéricy, Stéphane ; Grabli, David ; Degos, Bertrand</creatorcontrib><description>Background
International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages.
Objectives
To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine‐learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism.
Materials
Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2‐year follow‐up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 (“Clin1”); (2) MRI visual reading blinded to the clinical diagnosis (“MRI”); (3) both MRI visual reading and clinical criteria at V1 (“MRI and Clin1”), and (4) a machine‐learning algorithm (“Algorithm”). The gold standard diagnosis was established by expert consensus after a 2‐year follow‐up.
Results
We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit (“Clin1”: balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% (“MRI”: 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit (“MRI and Clin1”: 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% (“Algorithm”: 76.1%; P = 0.08).
Conclusion
Our study shows the use of MRI analysis, whether by visual reading or machine‐learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</description><identifier>ISSN: 0885-3185</identifier><identifier>EISSN: 1531-8257</identifier><identifier>DOI: 10.1002/mds.29760</identifier><identifier>PMID: 38486423</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Accuracy ; Algorithms ; Atrophy ; Basal ganglia ; Central nervous system diseases ; Cognitive science ; Diagnosis ; Learning algorithms ; Life Sciences ; Machine learning ; Magnetic resonance imaging ; Medical diagnosis ; Movement disorders ; MRI ; multisystem atrophy ; Neurodegenerative diseases ; Neuroimaging ; Neuroscience ; Parkinson's disease ; Progressive supranuclear palsy ; Reading ; Visual discrimination learning</subject><ispartof>Movement disorders, 2024-05, Vol.39 (5), p.825-835</ispartof><rights>2024 The Authors. published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</rights><rights>2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4220-5ff6349c4f792faed006a30b492d757a1ff300fef974bfbe52703af1a68e3f073</citedby><cites>FETCH-LOGICAL-c4220-5ff6349c4f792faed006a30b492d757a1ff300fef974bfbe52703af1a68e3f073</cites><orcidid>0000-0002-2409-9143 ; 0000-0001-9306-5687 ; 0000-0002-6229-5364 ; 0000-0001-5644-1292 ; 0000-0001-7325-0199 ; 0000-0002-9836-654X ; 0000-0002-5802-3518 ; 0000-0001-6798-4567</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmds.29760$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmds.29760$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38486423$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-04675671$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Chougar, Lydia</creatorcontrib><creatorcontrib>Faucher, Alice</creatorcontrib><creatorcontrib>Faouzi, Johann</creatorcontrib><creatorcontrib>Lejeune, François‐Xavier</creatorcontrib><creatorcontrib>Gama Lobo, Gonçalo</creatorcontrib><creatorcontrib>Jovanovic, Carna</creatorcontrib><creatorcontrib>Cormier, Florence</creatorcontrib><creatorcontrib>Dupont, Gwendoline</creatorcontrib><creatorcontrib>Vidailhet, Marie</creatorcontrib><creatorcontrib>Corvol, Jean‐Christophe</creatorcontrib><creatorcontrib>Colliot, Olivier</creatorcontrib><creatorcontrib>Lehéricy, Stéphane</creatorcontrib><creatorcontrib>Grabli, David</creatorcontrib><creatorcontrib>Degos, Bertrand</creatorcontrib><title>Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty</title><title>Movement disorders</title><addtitle>Mov Disord</addtitle><description>Background
International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages.
Objectives
To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine‐learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism.
Materials
Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2‐year follow‐up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 (“Clin1”); (2) MRI visual reading blinded to the clinical diagnosis (“MRI”); (3) both MRI visual reading and clinical criteria at V1 (“MRI and Clin1”), and (4) a machine‐learning algorithm (“Algorithm”). The gold standard diagnosis was established by expert consensus after a 2‐year follow‐up.
Results
We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit (“Clin1”: balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% (“MRI”: 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit (“MRI and Clin1”: 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% (“Algorithm”: 76.1%; P = 0.08).
Conclusion
Our study shows the use of MRI analysis, whether by visual reading or machine‐learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Atrophy</subject><subject>Basal ganglia</subject><subject>Central nervous system diseases</subject><subject>Cognitive science</subject><subject>Diagnosis</subject><subject>Learning algorithms</subject><subject>Life Sciences</subject><subject>Machine learning</subject><subject>Magnetic resonance imaging</subject><subject>Medical diagnosis</subject><subject>Movement disorders</subject><subject>MRI</subject><subject>multisystem atrophy</subject><subject>Neurodegenerative diseases</subject><subject>Neuroimaging</subject><subject>Neuroscience</subject><subject>Parkinson's disease</subject><subject>Progressive supranuclear palsy</subject><subject>Reading</subject><subject>Visual discrimination learning</subject><issn>0885-3185</issn><issn>1531-8257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp10U1PHCEYB3DStKnr2kO_gCHppR5GH2AYmKNZtWuypo0vZ8LMgovOgAVGs9--s11fEhNPBPjlz0P-CH0ncEgA6FG_TIe0FhV8QhPCGSkk5eIzmoCUvGBE8h20m9IdACGcVF_RDpOlrErKJqidBZ-ja4bsgsfB4ovLc2xDxHll8KmO3RqfOH3rQ3Jpc_1Hx3vnU_Au9dj5cZ-d8TnhJ5dXLzS7Ft_41sSsnc_rPfTF6i6Zb8_rFN2cnV7P5sXi96_z2fGiaEtKoeDWVqys29KKmlptlgCVZtCUNV0KLjSxlgFYY2tRNrYxnApg2hJdScMsCDZFB9vcle7UQ3S9jmsVtFPz44XanEFZCV4J8khG-3NrH2L4O5iUVe9Sa7pOexOGpGjNJQNCOR3pj3f0LgzRjz9RDPjIiKzl2-NtDClFY18nIKA2LamxJfW_pdHuPycOTW-Wr_KllhEcbcGT68z64yR1cXK1jfwHL0eaow</recordid><startdate>202405</startdate><enddate>202405</enddate><creator>Chougar, Lydia</creator><creator>Faucher, Alice</creator><creator>Faouzi, Johann</creator><creator>Lejeune, François‐Xavier</creator><creator>Gama Lobo, Gonçalo</creator><creator>Jovanovic, Carna</creator><creator>Cormier, Florence</creator><creator>Dupont, Gwendoline</creator><creator>Vidailhet, Marie</creator><creator>Corvol, Jean‐Christophe</creator><creator>Colliot, Olivier</creator><creator>Lehéricy, Stéphane</creator><creator>Grabli, David</creator><creator>Degos, Bertrand</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><general>Wiley</general><scope>24P</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-2409-9143</orcidid><orcidid>https://orcid.org/0000-0001-9306-5687</orcidid><orcidid>https://orcid.org/0000-0002-6229-5364</orcidid><orcidid>https://orcid.org/0000-0001-5644-1292</orcidid><orcidid>https://orcid.org/0000-0001-7325-0199</orcidid><orcidid>https://orcid.org/0000-0002-9836-654X</orcidid><orcidid>https://orcid.org/0000-0002-5802-3518</orcidid><orcidid>https://orcid.org/0000-0001-6798-4567</orcidid></search><sort><creationdate>202405</creationdate><title>Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty</title><author>Chougar, Lydia ; Faucher, Alice ; Faouzi, Johann ; Lejeune, François‐Xavier ; Gama Lobo, Gonçalo ; Jovanovic, Carna ; Cormier, Florence ; Dupont, Gwendoline ; Vidailhet, Marie ; Corvol, Jean‐Christophe ; Colliot, Olivier ; Lehéricy, Stéphane ; Grabli, David ; Degos, Bertrand</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4220-5ff6349c4f792faed006a30b492d757a1ff300fef974bfbe52703af1a68e3f073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Atrophy</topic><topic>Basal ganglia</topic><topic>Central nervous system diseases</topic><topic>Cognitive science</topic><topic>Diagnosis</topic><topic>Learning algorithms</topic><topic>Life Sciences</topic><topic>Machine learning</topic><topic>Magnetic resonance imaging</topic><topic>Medical diagnosis</topic><topic>Movement disorders</topic><topic>MRI</topic><topic>multisystem atrophy</topic><topic>Neurodegenerative diseases</topic><topic>Neuroimaging</topic><topic>Neuroscience</topic><topic>Parkinson's disease</topic><topic>Progressive supranuclear palsy</topic><topic>Reading</topic><topic>Visual discrimination learning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chougar, Lydia</creatorcontrib><creatorcontrib>Faucher, Alice</creatorcontrib><creatorcontrib>Faouzi, Johann</creatorcontrib><creatorcontrib>Lejeune, François‐Xavier</creatorcontrib><creatorcontrib>Gama Lobo, Gonçalo</creatorcontrib><creatorcontrib>Jovanovic, Carna</creatorcontrib><creatorcontrib>Cormier, Florence</creatorcontrib><creatorcontrib>Dupont, Gwendoline</creatorcontrib><creatorcontrib>Vidailhet, Marie</creatorcontrib><creatorcontrib>Corvol, Jean‐Christophe</creatorcontrib><creatorcontrib>Colliot, Olivier</creatorcontrib><creatorcontrib>Lehéricy, Stéphane</creatorcontrib><creatorcontrib>Grabli, David</creatorcontrib><creatorcontrib>Degos, Bertrand</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>PubMed</collection><collection>CrossRef</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>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Movement disorders</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chougar, Lydia</au><au>Faucher, Alice</au><au>Faouzi, Johann</au><au>Lejeune, François‐Xavier</au><au>Gama Lobo, Gonçalo</au><au>Jovanovic, Carna</au><au>Cormier, Florence</au><au>Dupont, Gwendoline</au><au>Vidailhet, Marie</au><au>Corvol, Jean‐Christophe</au><au>Colliot, Olivier</au><au>Lehéricy, Stéphane</au><au>Grabli, David</au><au>Degos, Bertrand</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty</atitle><jtitle>Movement disorders</jtitle><addtitle>Mov Disord</addtitle><date>2024-05</date><risdate>2024</risdate><volume>39</volume><issue>5</issue><spage>825</spage><epage>835</epage><pages>825-835</pages><issn>0885-3185</issn><eissn>1531-8257</eissn><abstract>Background
International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages.
Objectives
To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine‐learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism.
Materials
Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2‐year follow‐up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 (“Clin1”); (2) MRI visual reading blinded to the clinical diagnosis (“MRI”); (3) both MRI visual reading and clinical criteria at V1 (“MRI and Clin1”), and (4) a machine‐learning algorithm (“Algorithm”). The gold standard diagnosis was established by expert consensus after a 2‐year follow‐up.
Results
We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit (“Clin1”: balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% (“MRI”: 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit (“MRI and Clin1”: 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% (“Algorithm”: 76.1%; P = 0.08).
Conclusion
Our study shows the use of MRI analysis, whether by visual reading or machine‐learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>38486423</pmid><doi>10.1002/mds.29760</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-2409-9143</orcidid><orcidid>https://orcid.org/0000-0001-9306-5687</orcidid><orcidid>https://orcid.org/0000-0002-6229-5364</orcidid><orcidid>https://orcid.org/0000-0001-5644-1292</orcidid><orcidid>https://orcid.org/0000-0001-7325-0199</orcidid><orcidid>https://orcid.org/0000-0002-9836-654X</orcidid><orcidid>https://orcid.org/0000-0002-5802-3518</orcidid><orcidid>https://orcid.org/0000-0001-6798-4567</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Accuracy Algorithms Atrophy Basal ganglia Central nervous system diseases Cognitive science Diagnosis Learning algorithms Life Sciences Machine learning Magnetic resonance imaging Medical diagnosis Movement disorders MRI multisystem atrophy Neurodegenerative diseases Neuroimaging Neuroscience Parkinson's disease Progressive supranuclear palsy Reading Visual discrimination learning |
| title | Contribution of MRI for the Early Diagnosis of Parkinsonism in Patients with Diagnostic Uncertainty |
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