{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T21:38:42Z","timestamp":1761514722438,"version":"3.41.2"},"reference-count":43,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T00:00:00Z","timestamp":1613692800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>The frequently discovered incidental findings (IFs) from imaging observations are increasing. The IFs show the potential clues of structural abnormalities underlying cognitive decline in elders. Detecting brain IFs and their relationship with cognitive and behavioral functions helps provide the information for clinical strategies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Five hundred and seventy-nine participants were recruited in the Shanghai Changfeng Study. All participants performed the demographic, biochemical, and cognitive functions and gait speed assessment and underwent the high-resolution multimodal magnetic resonance imaging scans. We calculated the detection rate of brain IFs. The association between cardiovascular risk factors and IFs and the associations between IFs and cognitive and motor functions were assessed using regression models. The relationships among gray matter volume, cognitive function, and gait speed were assessed with\/without adjusting the IFs to evaluate the effects of potential IFs confounders.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>IFs were found in a total of 578 subjects with a detection rate of 99.8%. Age and blood pressure were the most significant cardiovascular risk factors correlated with IFs. IFs were found to be negatively associated with Montreal Cognitive Assessment, Mini-Mental State Examination, and gait speed. The gray matter volume was found to be positively correlated with the cognitive function without adjusting the white matter hyperintensity but not if adjusted.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>IFs are commonly found in the elderly population and related to brain functions. The adequate intervention of IFs related cardiovascular risk factors that may slow down the progression of brain function decline. We also suggest that IFs should be considered as confounding factors that may affect cognitive issues on the structural neuroimaging researches in aging or diseases.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnins.2021.631087","type":"journal-article","created":{"date-parts":[[2021,2,21]],"date-time":"2021-02-21T00:24:47Z","timestamp":1613867087000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Incidental Brain Magnetic Resonance Imaging Findings and the Cognitive and Motor Performance in the Elderly: The Shanghai Changfeng Study"],"prefix":"10.3389","volume":"15","author":[{"given":"Liangqi","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huandong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifeng","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zehua","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingyan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun-Yi Zac","family":"Lo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2021,2,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/j.dadm.2015.10.004","article-title":"A priori collaboration in population imaging: The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium.","volume":"1","author":"Adams","year":"2015","journal-title":"Alzheimers Dement"},{"key":"B2","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","article-title":"A fast diffeomorphic image registration algorithm.","volume":"38","author":"Ashburner","year":"2007","journal-title":"NeuroImage"},{"key":"B3","doi-asserted-by":"publisher","first-page":"839","DOI":"10.1016\/j.neuroimage.2005.02.018","article-title":"Unified segmentation.","volume":"26","author":"Ashburner","year":"2005","journal-title":"Neuroimage"},{"key":"B4","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1530\/eje.1.02107","article-title":"Subclinical adenomas in postmortem pituitaries: classification and correlations to clinical data.","volume":"154","author":"Buurman","year":"2006","journal-title":"Eur. 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