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Traditionally, atrophy has been quantified by differences in brain volume or thickness over a specified timeframe. Research indicates that the rate of atrophy varies across different brain regions, which themselves exhibit complex spatial and hierarchical organizations. These characteristics collectively emphasize the need for diverse summary measures that can effectively capture the multidimensional nature of degeneration. In this study, we explore the use of distance measurements to quantify brain volumetric changes using processed MRI data from the Preclinical Alzheimer's Disease Consortium (PAC). We conducted a series of analyses to predict future diagnostic status by modeling MRI trajectories for participants who were cognitively normal at baseline and either remained cognitively normal or progressed to mild cognitive impairment (MCI) over time, with adjustments for age, sex, education, and APOE genotype. We consider multiple distance measures and brain regions through a two\u2010step approach. First, we build base models by fitting individual mixed\u2010effect models for each distance metric and brain region pairing, using follow\u2010up diagnosis (normal vs. MCI) as the outcome and volumetric changes from the baseline, as summarized by a given distance measure, as predictors. The second step aggregates these individual region\u2010distance base models to derive an overall estimate of diagnostic status. Our analyses showed that the distance measures approach consistently outperformed the traditional direct volumetric approach in terms of predictive accuracy, both in individual base models and the aggregated models. This work highlights the potential advantage of using distance measures over the traditional direct volumetric approach to capture the multidimensional aspects of atrophy in the development of AD and related disorders.<\/jats:p>","DOI":"10.1002\/hbm.70205","type":"journal-article","created":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T09:37:44Z","timestamp":1745487464000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["<scp>MRI<\/scp> Distance Measures as a Predictor of Subsequent Clinical Status During the Preclinical Phase of Alzheimer's Disease and Related Disorders"],"prefix":"10.1002","volume":"46","author":[{"given":"Xinyi","family":"Zhang","sequence":"first","affiliation":[{"name":"Division of Quantitative Sciences, Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University  Baltimore Maryland USA"},{"name":"Department of Biostatistics Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brian S.","family":"Caffo","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anja","family":"Soldan","sequence":"additional","affiliation":[{"name":"Department of Neurology Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Corinne","family":"Pettigrew","sequence":"additional","affiliation":[{"name":"Department of Neurology Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erus","family":"Guray","sequence":"additional","affiliation":[{"name":"Center for Biomedical Image Computing and Analytics University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christos","family":"Davatzikos","sequence":"additional","affiliation":[{"name":"Center for Biomedical Image Computing and Analytics University of Pennsylvania  Philadelphia Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John C.","family":"Morris","sequence":"additional","affiliation":[{"name":"Department of Neurology Washington University in St. Louis  St. Louis Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tammie L. S.","family":"Benzinger","sequence":"additional","affiliation":[{"name":"Department of Radiology Washington University School of Medicine in St. Louis  St. Louis Missouri USA"},{"name":"Department of Neurosurgery Washington University School of Medicine in St. Louis  St. Louis Missouri USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sterling C.","family":"Johnson","sequence":"additional","affiliation":[{"name":"Department of Medicine University of Wisconsin\u2010Madison  Madison Wisconsin USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Colin L.","family":"Masters","sequence":"additional","affiliation":[{"name":"Florey Institute of Neuroscience and Mental Health, University of Melbourne  Melbourne Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jurgen","family":"Fripp","sequence":"additional","affiliation":[{"name":"CSIRO Health and Biosecurity, Australian e\u2010Health Research Centre CSIRO  Brisbane Queensland Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susan M.","family":"Resnick","sequence":"additional","affiliation":[{"name":"Laboratory of Behavioral Neuroscience National Institute on Aging  Bethesda Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Murat","family":"Bilgel","sequence":"additional","affiliation":[{"name":"Laboratory of Behavioral Neuroscience National Institute on Aging  Bethesda Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Walter A.","family":"Kukull","sequence":"additional","affiliation":[{"name":"Department of Epidemiology University of Washington  Seattle Washington USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marilyn S.","family":"Albert","sequence":"additional","affiliation":[{"name":"Department of Neurology Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7806-5002","authenticated-orcid":false,"given":"Zheyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Division of Quantitative Sciences, Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University  Baltimore Maryland USA"},{"name":"Department of Biostatistics Johns Hopkins University  Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,4,24]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.2174\/156720501108140910121920"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2011.03.008"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awh451"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/1.1.103"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1202753"},{"volume-title":"Dynamic Programming","year":"1957","author":"Bellman R.","key":"e_1_2_9_7_1"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1001\/archgenpsychiatry.2011.155"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.2014.1909"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(20000515)19:9<1141::AID-SIM479>3.0.CO;2-F"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1177\/0891988705281881"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.8346443"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(11)70289-7"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2013.09.010"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.11.073"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1041610209009405"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/121.1.135"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3007901"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20744"},{"key":"e_1_2_9_20_1","first-page":"147","article-title":"A Classification Algorithm for Predicting Progression From Normal Cognition to Mild Cognitive Impairment Across Five Cohorts: The Preclinical AD Consortium","volume":"8","author":"Gross A. 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