{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T19:29:23Z","timestamp":1790278163743,"version":"4.1.0"},"reference-count":30,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T00:00:00Z","timestamp":1710115200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["movementdisorders.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Movement Disorders"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Intrastriatal delivery of potential therapeutics in Huntington's disease (HD) requires sufficient caudate and putamen volumes. Currently, volumetric magnetic resonance imaging is rarely done in clinical practice, and these data are not available in large research cohorts such as Enroll\u2010HD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>The objective of this study was to investigate whether predictive models can accurately classify HD patients who exceed caudate and putamen volume thresholds required for intrastriatal therapeutic interventions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We obtained and merged data for 1374 individuals across three HD cohorts: IMAGE\u2010HD, PREDICT\u2010HD, and TRACK\u2010HD\/TRACK\u2010ON. We imputed missing data for clinical variables with &gt;72% non\u2010missing values and used the model\u2010building algorithm BORUTA to identify the 10 most important variables. A random forest algorithm was applied to build a predictive model for putamen volume &gt;2500\u2009mm<jats:sup>3<\/jats:sup> and caudate volume &gt;2000\u2009mm<jats:sup>3<\/jats:sup> bilaterally. Using the same 10 predictors, we constructed a logistic regression model with predictors significant at <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The random forest model with 1000 trees and minimal terminal node size of 5 resulted in 83% area under the curve (AUC). The logistic regression model retaining age, CAG repeat size, and symbol digit modalities test\u2010correct had 85.1% AUC. A probability cutoff of 0.8 resulted in 5.4% false positive and 66.7% false negative rates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Using easily obtainable clinical data and machine learning\u2010identified initial predictor variables, random forest, and logistic regression models can successfully identify people with sufficient striatal volumes for inclusion cutoffs. Adopting these models in prescreening could accelerate clinical trial enrollment in HD and other neurodegenerative disorders when volume cutoffs are necessary enrollment criteria. \u00a9 2024 The Authors. <jats:italic>Movement Disorders<\/jats:italic> published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mds.29749","type":"journal-article","created":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T07:24:54Z","timestamp":1710141894000},"page":"855-862","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Optimizing Screening for Intrastriatal Interventions in Huntington's Disease Using Predictive Models"],"prefix":"10.1002","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4480-0221","authenticated-orcid":false,"given":"Matthew J.","family":"Barrett","sequence":"first","affiliation":[{"name":"Department of Neurology Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed","family":"Negida","sequence":"additional","affiliation":[{"name":"Department of Neurology Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nitai","family":"Mukhopadhyay","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin K.","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Neurology Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huma","family":"Nawaz","sequence":"additional","affiliation":[{"name":"Department of Neurology Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jefin","family":"Jose","sequence":"additional","affiliation":[{"name":"Department of Neurology Virginia Commonwealth University  Richmond Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia","family":"Testa","sequence":"additional","affiliation":[{"name":"Department of Neurology University of North Carolina at Chapel Hill  Chapel Hill North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,3,11]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0092-8674(93)90585-e"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/1750-1172-5-40"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A2018"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.2217\/nmt.12.34"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13311-020-00891-w"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.14802\/jmd.21006"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(22)00121-1"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.5603\/PJNNS.a2020.0046"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci6030038"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2021.667420"},{"key":"e_1_2_10_12_1","article-title":"Evolving inclusion criteria in early manifest Huntington's disease (HD) to address striatal atrophy: lessons from HD\u2010GeneTRX\u20101, the first gene therapy trial","volume":"36","author":"Furr\u2010Stimming E","year":"2021","journal-title":"Mov Disord"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1136\/jnnp.2007.128728"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0074131"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(13)70088-7"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2015.08.002"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1002\/ana.25709"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(22)00120-X"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/mds.870110204"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/mpr.329"},{"key":"e_1_2_10_21_1","volume-title":"Statistical Analysis with Missing Data, New York","author":"Little R","year":"1987"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v036.i11"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1212\/01.wnl.0000086373.32347.16"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2019.2368"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1371\/currents.RRN1235"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1111\/ene.15806"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/mds.28489"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00415-015-7900-7"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.psychres.2010.04.030"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.1002\/brb3.185"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2010.09.027"}],"container-title":["Movement Disorders"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/movementdisorders.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mds.29749","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T14:05:33Z","timestamp":1760969133000},"score":1,"resource":{"primary":{"URL":"https:\/\/movementdisorders.onlinelibrary.wiley.com\/doi\/10.1002\/mds.29749"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,11]]},"references-count":30,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["10.1002\/mds.29749"],"URL":"https:\/\/doi.org\/10.1002\/mds.29749","archive":["Portico"],"relation":{},"ISSN":["0885-3185","1531-8257"],"issn-type":[{"value":"0885-3185","type":"print"},{"value":"1531-8257","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,11]]},"assertion":[{"value":"2023-11-02","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-02-02","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-03-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}