{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T20:55:29Z","timestamp":1782334529034,"version":"3.54.5"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T00:00:00Z","timestamp":1613520000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T00:00:00Z","timestamp":1613520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG054520"],"award-info":[{"award-number":["R01AG054520"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["RF1AG054023"],"award-info":[{"award-number":["RF1AG054023"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["RF1AG054023"],"award-info":[{"award-number":["RF1AG054023"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["R01AG054520"],"award-info":[{"award-number":["R01AG054520"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Cerebral microbleeds, observed as small, spherical hypointense regions on gradient echo (GRE) or susceptibility weighted (SWI) magnetic resonance imaging (MRI) sequences, reflect small hemorrhagic infarcts, and are associated with conditions such as vascular dementia, small vessel disease, cerebral amyloid angiopathy, and Alzheimer\u2019s disease. The current gold standard for detecting and rating cerebral microbleeds in a research context is visual inspection by trained raters, a process that is both time consuming and subject to poor reliability. We present here a novel method to automate microbleed detection on GRE and SWI images. We demonstrate in a community-based cohort of older adults that the method is highly sensitive (greater than 92% of all microbleeds accurately detected) across both modalities, with reasonable precision (fewer than 20 and 10 false positives per scan on GRE and SWI, respectively). We also demonstrate that the algorithm can be used to identify microbleeds over longitudinal scans with a higher level of sensitivity than visual ratings (50% of longitudinal microbleeds correctly labeled by the algorithm, while manual ratings was 30% or lower). Further, the algorithm identifies the anatomical localization of microbleeds based on brain atlases, and greatly reduces time spent completing visual ratings (43% reduction in visual rating time). Our automatic microbleed detection instrument is ideal for implementation in large-scale studies that include cross-sectional and longitudinal scanning, as well as being capable of performing well across multiple commonly used MRI modalities.<\/jats:p>","DOI":"10.1038\/s41598-021-83607-0","type":"journal-article","created":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T16:46:37Z","timestamp":1613753197000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Automated detection of cerebral microbleeds on T2*-weighted MRI"],"prefix":"10.1038","volume":"11","author":[{"given":"Anthony G.","family":"Chesebro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erica","family":"Amarante","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick J.","family":"Lao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irene B.","family":"Meier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Mayeux","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam M.","family":"Brickman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,2,17]]},"reference":[{"key":"83607_CR1","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/S1474-4422(09)70013-4","volume":"8","author":"SM Greenberg","year":"2009","unstructured":"Greenberg, S. M. et al. Cerebral microbleeds: A field guide to their detection and interpretation. Lancet Neurol. 8, 165\u2013174 (2009).","journal-title":"Lancet Neurol."},{"key":"83607_CR2","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/alzrt263","volume":"6","author":"S Martinez-Ramirez","year":"2014","unstructured":"Martinez-Ramirez, S., Greenberg, S. M. & Viswanathan, A. Cerebral microbleeds: Overview and implications in cognitive impairment. Alzheimers Res. Ther. 6, 33 (2014).","journal-title":"Alzheimers Res. Ther."},{"key":"83607_CR3","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.jns.2014.07.024","volume":"345","author":"AF Wiegman","year":"2014","unstructured":"Wiegman, A. F. et al. Cerebral microbleeds in a multiethnic elderly community: Demographic and clinical correlates. J. Neurol. Sci. 345, 125\u2013130 (2014).","journal-title":"J. Neurol. Sci."},{"key":"83607_CR4","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1016\/j.jalz.2011.05.2351","volume":"7","author":"RA Sperling","year":"2011","unstructured":"Sperling, R. A. et al. Amyloid related imaging abnormalities (ARIA) in amyloid modifying therapeutic trials: Recommendations from the Alzheimer\u2019s Association Research Roundtable Workgroup. Alzheimers Dement. 7, 367\u2013385 (2011).","journal-title":"Alzheimers Dement."},{"key":"83607_CR5","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1148\/radiol.2018170803","volume":"287","author":"S Haller","year":"2018","unstructured":"Haller, S. et al. Cerebral microbleeds: Imaging and clinical significance. Radiology 287, 11\u201328 (2018).","journal-title":"Radiology"},{"key":"83607_CR6","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1159\/000139661","volume":"26","author":"S Tatsumi","year":"2008","unstructured":"Tatsumi, S., Shinohara, M. & Yamamoto, T. Direct comparison of histology of microbleeds with postmortem MR images: A case report. Cerebrovasc. Dis. 26, 142\u2013146 (2008).","journal-title":"Cerebrovasc. Dis."},{"key":"83607_CR7","first-page":"637","volume":"20","author":"F Fazekas","year":"1999","unstructured":"Fazekas, F. et al. Histopathologic analysis of foci of signal loss on gradient-echo T2*-weighted MR images in patients with spontaneous intracerebral hemorrhage: Evidence of microangiopathy-related microbleeds. AJNR Am. J. Neuroradiol. 20, 637\u2013642 (1999).","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"83607_CR8","doi-asserted-by":"crossref","unstructured":"Cordonnier, C., Al-Shahi Salman, R. & Wardlaw, J. Spontaneous brain microbleeds: Systematic review, subgroup analyses and standards for study design and reporting. Brain 130, 1988\u20132003 (2007).","DOI":"10.1093\/brain\/awl387"},{"key":"83607_CR9","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1161\/STROKEAHA.108.526996","volume":"40","author":"C Cordonnier","year":"2009","unstructured":"Cordonnier, C. et al. Improving interrater agreement about brain microbleeds: Development of the Brain Observer MicroBleed Scale (BOMBS). Stroke 40, 94\u201399 (2009).","journal-title":"Stroke"},{"key":"83607_CR10","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1016\/j.exger.2012.06.008","volume":"47","author":"A Charidimou","year":"2012","unstructured":"Charidimou, A., J\u00e4ger, H. R. & Werring, D. J. Cerebral microbleed detection and mapping: Principles, methodological aspects and rationale in vascular dementia. Exp. Gerontol. 47, 843\u2013852 (2012).","journal-title":"Exp. Gerontol."},{"key":"83607_CR11","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1002\/jmri.22001","volume":"31","author":"M Ayaz","year":"2010","unstructured":"Ayaz, M., Boikov, A. S., Haacke, E. M., Kirsch, W. M. & Kido, D. K. Imaging cerebral microbleeds using susceptibility weighted imaging: One step toward detecting vascular dementia. J. Magn. Reson. Imaging 31, 142\u2013148 (2010).","journal-title":"J. Magn. Reson. Imaging"},{"key":"83607_CR12","doi-asserted-by":"publisher","first-page":"1930","DOI":"10.1212\/01.wnl.0000436609.20587.65","volume":"81","author":"S Akoudad","year":"2013","unstructured":"Akoudad, S. et al. Cerebral microbleeds are related to loss of white matter structural integrity. Neurology 81, 1930\u20131937 (2013).","journal-title":"Neurology"},{"key":"83607_CR13","doi-asserted-by":"publisher","first-page":"1759","DOI":"10.1212\/WNL.0b013e3181c34a7d","volume":"73","author":"SM Gregoire","year":"2009","unstructured":"Gregoire, S. M. et al. The Microbleed Anatomical Rating Scale (MARS): Reliability of a tool to map brain microbleeds. Neurology 73, 1759\u20131766 (2009).","journal-title":"Neurology"},{"key":"83607_CR14","doi-asserted-by":"crossref","unstructured":"van den Heuvel, T. L. A. et al. Automated detection of cerebral microbleeds in patients with traumatic brain injury. NeuroImage Clin. 12, 241\u2013251 (2016).","DOI":"10.1016\/j.nicl.2016.07.002"},{"key":"83607_CR15","doi-asserted-by":"crossref","unstructured":"Bian, W., Hess, C. P., Chang, S. M., Nelson, S. J. & Lupo, J. M. Computer-aided detection of radiation-induced cerebral microbleeds on susceptibility-weighted MR images. NeuroImage Clin. 2, 282\u2013290 (2013).","DOI":"10.1016\/j.nicl.2013.01.012"},{"key":"83607_CR16","doi-asserted-by":"publisher","first-page":"766","DOI":"10.1007\/s10278-018-0146-z","volume":"32","author":"Y Chen","year":"2019","unstructured":"Chen, Y., Villanueva-Meyer, J. E., Morrison, M. A. & Lupo, J. M. Toward Automatic detection of radiation-induced cerebral microbleeds using a 3D deep residual network. J. Digit. Imaging 32, 766\u2013772 (2019).","journal-title":"J. Digit. Imaging"},{"key":"83607_CR17","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1016\/j.nicl.2018.08.002","volume":"20","author":"MA Morrison","year":"2018","unstructured":"Morrison, M. A. et al. A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning. Neuroimage Clin. 20, 498\u2013505 (2018).","journal-title":"Neuroimage Clin."},{"key":"83607_CR18","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1212\/WNL.0b013e3182452928","volume":"78","author":"MMF Poels","year":"2012","unstructured":"Poels, M. M. F. et al. Cerebral microbleeds are associated with worse cognitive function: the Rotterdam Scan Study. Neurology 78, 326\u2013333 (2012).","journal-title":"Neurology"},{"key":"83607_CR19","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1159\/000092958","volume":"22","author":"Y Nakata-Kudo","year":"2006","unstructured":"Nakata-Kudo, Y. et al. Microbleeds in Alzheimer disease are more related to cerebral amyloid angiopathy than cerebrovascular disease. Dement. Geriatr. Cogn. Disord. 22, 8\u201314 (2006).","journal-title":"Dement. Geriatr. Cogn. Disord."},{"key":"83607_CR20","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.jns.2007.03.008","volume":"258","author":"S-H Lee","year":"2007","unstructured":"Lee, S.-H., Kim, S.-M., Kim, N., Yoon, B.-W. & Roh, J.-K. Cortico-subcortical distribution of microbleeds is different between hypertension and cerebral amyloid angiopathy. J. Neurol. Sci. 258, 111\u2013114 (2007).","journal-title":"J. Neurol. Sci."},{"key":"83607_CR21","doi-asserted-by":"crossref","unstructured":"Ivanoiu, A. et al. Long-term safety and tolerability of bapineuzumab in patients with Alzheimer\u2019s disease in two phase 3 extension studies. Alzheimers Res. Ther. 8 (2016).","DOI":"10.1186\/s13195-016-0193-y"},{"key":"83607_CR22","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1038\/nature19323","volume":"537","author":"J Sevigny","year":"2016","unstructured":"Sevigny, J. et al. The antibody aducanumab reduces A\u03b2 plaques in Alzheimer\u2019s disease. Nature 537, 50\u201356 (2016).","journal-title":"Nature"},{"key":"83607_CR23","doi-asserted-by":"publisher","first-page":"232","DOI":"10.3174\/ajnr.A1461","volume":"30","author":"S Mittal","year":"2009","unstructured":"Mittal, S., Wu, Z., Neelavalli, J. & Haacke, E. M. Susceptibility-weighted imaging: Technical aspects and clinical applications, Part 2. Am. J. Neuroradiol. 30, 232\u2013252 (2009).","journal-title":"Am. J. Neuroradiol."},{"key":"83607_CR24","doi-asserted-by":"publisher","first-page":"1553","DOI":"10.3174\/ajnr.A3108","volume":"33","author":"MMF Poels","year":"2012","unstructured":"Poels, M. M. F., Ikram, M. A. & Vernooij, M. W. Improved MR imaging detection of cerebral microbleeds more accurately identifies persons with vasculopathy. Am. J. Neuroradiol. 33, 1553\u20131556 (2012).","journal-title":"Am. J. Neuroradiol."},{"key":"83607_CR25","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.1109\/TMI.2016.2528129","volume":"35","author":"Q Dou","year":"2016","unstructured":"Dou, Q. et al. Automatic detection of cerebral microbleeds from MR images via 3D convolutional neural networks. IEEE Trans. Med. Imaging 35, 1182\u20131195 (2016).","journal-title":"IEEE Trans. Med. Imaging"},{"key":"83607_CR26","doi-asserted-by":"crossref","unstructured":"Kuijf, H. J. et al. Efficient detection of cerebral microbleeds on 7.0T MR images using the radial symmetry transform. NeuroImage 59, 2266\u20132273 (2012).","DOI":"10.1016\/j.neuroimage.2011.09.061"},{"key":"83607_CR27","doi-asserted-by":"publisher","first-page":"844","DOI":"10.1016\/j.mri.2011.02.028","volume":"29","author":"SRS Barnes","year":"2011","unstructured":"Barnes, S. R. S. et al. Semiautomated detection of cerebral microbleeds in magnetic resonance images. Magn. Reson. Imaging 29, 844\u2013852 (2011).","journal-title":"Magn. Reson. Imaging"},{"key":"83607_CR28","doi-asserted-by":"publisher","first-page":"e17547","DOI":"10.1371\/journal.pone.0017547","volume":"6","author":"ML Seghier","year":"2011","unstructured":"Seghier, M. L. et al. Microbleed detection using automated segmentation (MIDAS): A new method applicable to standard clinical MR images. PLoS ONE 6, e17547 (2011).","journal-title":"PLoS ONE"},{"key":"83607_CR29","doi-asserted-by":"publisher","unstructured":"Ghafaryasl, B. et al. A computer aided detection system for cerebral microbleeds in brain MRI. in 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI) 138\u2013141 (2012). https:\/\/doi.org\/10.1109\/ISBI.2012.6235503.","DOI":"10.1109\/ISBI.2012.6235503"},{"key":"83607_CR30","doi-asserted-by":"publisher","unstructured":"Fazlollahi, A. et al. Efficient machine learning framework for computer-aided detection of cerebral microbleeds using the Radon transform. in 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI) 113\u2013116 (2014). https:\/\/doi.org\/10.1109\/ISBI.2014.6867822.","DOI":"10.1109\/ISBI.2014.6867822"},{"key":"83607_CR31","doi-asserted-by":"publisher","unstructured":"Chen, H. et al. Automatic detection of cerebral microbleeds via deep learning based 3D feature representation. in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) 764\u2013767 (2015). https:\/\/doi.org\/10.1109\/ISBI.2015.7163984.","DOI":"10.1109\/ISBI.2015.7163984"},{"key":"83607_CR32","doi-asserted-by":"publisher","first-page":"1621","DOI":"10.1001\/archneurol.2012.1527","volume":"69","author":"AM Brickman","year":"2012","unstructured":"Brickman, A. M. et al. Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Arch. Neurol. 69, 1621\u20131627 (2012).","journal-title":"Arch. Neurol."},{"key":"83607_CR33","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1037\/h0031619","volume":"76","author":"JL Fleiss","year":"1971","unstructured":"Fleiss, J. L. Measuring nominal scale agreement among many raters. Psychol. Bull. 76, 378\u2013382 (1971).","journal-title":"Psychol. Bull."},{"key":"83607_CR34","doi-asserted-by":"publisher","first-page":"276","DOI":"10.11613\/BM.2012.031","volume":"22","author":"ML McHugh","year":"2012","unstructured":"McHugh, M. L. Interrater reliability: The kappa statistic. Biochem Med (Zagreb) 22, 276\u2013282 (2012).","journal-title":"Biochem Med (Zagreb)"},{"key":"83607_CR35","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1016\/j.neuroimage.2011.09.015","volume":"62","author":"M Jenkinson","year":"2012","unstructured":"Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. NeuroImage 62, 782\u2013790 (2012).","journal-title":"NeuroImage"},{"key":"83607_CR36","unstructured":"Penny, W., Friston, K., Ashburner, J., Kiebel, S. & Nichols, T. Statistical Parametric Mapping: The Analysis of Functional Brain Images. (Academic Press, 2006)."},{"key":"83607_CR37","unstructured":"Duda, R. O. & Hart, P. E. Pattern Classification and Scene Analysis. (Wiley and Sons, 1973)."},{"key":"83607_CR38","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","volume":"8","author":"J Canny","year":"1986","unstructured":"Canny, J. A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679\u2013698 (1986).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"83607_CR39","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/361237.361242","volume":"15","author":"RO Duda","year":"1972","unstructured":"Duda, R. O. & Hart, P. E. Use of the Hough transformation to detect lines and curves in pictures. Commun. ACM 15, 11\u201315 (1972).","journal-title":"Commun. ACM"},{"key":"83607_CR40","doi-asserted-by":"crossref","unstructured":"Kuijf, H. J. et al. Semi-automated detection of cerebral microbleeds on 3.0 T MR images. PLOS ONE 8, e66610 (2013).","DOI":"10.1371\/journal.pone.0066610"},{"key":"83607_CR41","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1109\/TPAMI.2003.1217601","volume":"25","author":"G Loy","year":"2003","unstructured":"Loy, G. & Zelinsky, A. Fast radial symmetry for detecting points of interest. IEEE Trans. Pattern Anal. Mach. Intell. 25, 959\u2013973 (2003).","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"83607_CR42","unstructured":"Gonz\u00e1lez, R. C. & Woods, R. E. Digital Image Processing, 3rd Edn. (Pearson Prentice Hall, 2009)."},{"key":"83607_CR43","doi-asserted-by":"publisher","unstructured":"Frangi, A. F., Niessen, W. J., Vincken, K. L. & Viergever, M. A. Multiscale vessel enhancement filtering. in Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI\u201998 (eds. Wells, W. M., Colchester, A. & Delp, S.) 130\u2013137 (Springer, 1998). https:\/\/doi.org\/10.1007\/BFb0056195.","DOI":"10.1007\/BFb0056195"},{"issue":"2","key":"83607_CR44","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1148\/radiol.2015150160","volume":"278","author":"W Liu","year":"2016","unstructured":"Liu, W. et al. Imaging cerebral microhemorrhages in military service members with chronic traumatic brain injury. Radiology 278(2), 536\u2013545 (2016).","journal-title":"Radiology"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-83607-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-83607-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-83607-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,3]],"date-time":"2022-12-03T03:55:37Z","timestamp":1670039737000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-021-83607-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,17]]},"references-count":44,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["83607"],"URL":"https:\/\/doi.org\/10.1038\/s41598-021-83607-0","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,17]]},"assertion":[{"value":"10 April 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 February 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 February 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"4004"}}