{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T10:36:05Z","timestamp":1783161365618,"version":"3.54.6"},"reference-count":38,"publisher":"Journal of Neurosurgery Publishing Group (JNSPG)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,1]]},"abstract":"<jats:p>Features of new bleeding on conventional imaging in cerebral cavernous malformations (CCMs) often disappear after several weeks, yet the risk of rebleeding persists long thereafter. Increases in mean lesional quantitative susceptibility mapping (QSM) \u2265 6% on MRI during 1 year of prospective surveillance have been associated with new symptomatic hemorrhage (SH) during that period. The authors hypothesized that QSM at a single time point reflects features of hemorrhage in the prior year or potential bleeding in the subsequent year. Twenty-eight features were extracted from 265 QSM acquisitions in 120 patients enrolled in a prospective trial readiness project, and machine learning methods examined associations with SH and biomarker bleed (QSM increase \u2265 6%) in prior and subsequent years. QSM features including sum variance, variance, and correlation had lower average values in lesions with SH in the prior year (p &lt; 0.05, false discovery rate corrected). A support-vector machine classifier recurrently selected sum average, mean lesional QSM, sphericity, and margin sharpness features to distinguish biomarker bleeds in the prior year (area under the curve = 0.61, 95% CI 0.52\u20130.70; p = 0.02). No QSM features were associated with a subsequent bleed. These results provide proof of concept that machine learning may derive features of QSM reflecting prior hemorrhagic activity, meriting further investigation.<\/jats:p>\n                  <jats:p>\n                    Clinical trial registration no.: NCT03652181 (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/clinicalTrials.gov\">ClinicalTrials.gov<\/jats:ext-link>\n                    )\n                  <\/jats:p>","DOI":"10.3171\/2025.3.jns243051","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T21:35:05Z","timestamp":1751664905000},"page":"1567-1574","source":"Crossref","is-referenced-by-count":1,"title":["Identifying features of prior hemorrhage in cerebral cavernous malformations on quantitative susceptibility maps: a machine learning pilot study"],"prefix":"10.3171","volume":"143","author":[{"given":"Serena","family":"Kinkade","sequence":"first","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Li","sequence":"additional","affiliation":[{"name":"Diagnostic Radiology, University of Chicago Medicine and Biological Sciences, Chicago, Illinois;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephanie","family":"Hage","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janne","family":"Koskim\u00e4ki","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agnieszka","family":"Stadnik","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justine","family":"Lee","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Shenkar","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Papaioannou","sequence":"additional","affiliation":[{"name":"Diagnostic Radiology, University of Chicago Medicine and Biological Sciences, Chicago, Illinois;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelly D.","family":"Flemming","sequence":"additional","affiliation":[{"name":"Department of Neurology, Mayo Clinic, Rochester, Minnesota;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helen","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Perioperative Care, University of California, San Francisco, California;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michel","family":"Torbey","sequence":"additional","affiliation":[{"name":"Department of Neurology, University of Oklahoma Health Sciences, Oklahoma City, Oklahoma; and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Judy","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Johns Hopkins University Medical Institutions, Baltimore, Maryland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy J.","family":"Carroll","sequence":"additional","affiliation":[{"name":"Diagnostic Radiology, University of Chicago Medicine and Biological Sciences, Chicago, Illinois;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Romuald","family":"Girard","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryellen L.","family":"Giger","sequence":"additional","affiliation":[{"name":"Diagnostic Radiology, University of Chicago Medicine and Biological Sciences, Chicago, Illinois;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Issam A.","family":"Awad","sequence":"additional","affiliation":[{"name":"Departments of Neurological Surgery and"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1754","reference":[{"issue":"6","key":"b1","series-title":"Neurosurgery","first-page":"1454","article-title":"Ultrastructural pathological features of cerebrovascular malformations: a preliminary report","volume":"46","author":"Wong JH","year":"2000","unstructured":"Wong JH, Awad IA, Kim JH. Ultrastructural pathological features of cerebrovascular malformations: a preliminary report. Neurosurgery. 2000;46(6):1454\u20131459."},{"issue":"2","key":"b2","series-title":"Lancet Neurol","first-page":"166","article-title":"Clinical course of untreated cerebral cavernous malformations: a meta-analysis of individual patient data","volume":"15","author":"Horne MA","year":"2016","unstructured":"Horne MA, Flemming KD, Su IC,  Clinical course of untreated cerebral cavernous malformations: a meta-analysis of individual patient data. Lancet Neurol. 2016;15(2):166\u2013173."},{"issue":"3","key":"b3","series-title":"J Neurosurg","first-page":"1147","article-title":"Subclinical imaging changes in cerebral cavernous angiomas during prospective surveillance","volume":"134","author":"Carrion-Penagos J","year":"2021","unstructured":"Carrion-Penagos J, Zeineddine HA, Polster SP,  Subclinical imaging changes in cerebral cavernous angiomas during prospective surveillance. J Neurosurg. 2021;134(3):1147\u20131154."},{"issue":"5","key":"b4","series-title":"J Neurosurg","first-page":"1159","article-title":"Contemporary cohort of cerebral cavernous malformations: natural history and utility of follow-up MRI","volume":"141","author":"Flemming KD","year":"2024","unstructured":"Flemming KD, Brown RD, Lanzino G. Contemporary cohort of cerebral cavernous malformations: natural history and utility of follow-up MRI. J Neurosurg. 2024;141(5):1159\u20131167."},{"issue":"5","key":"b5","series-title":"Neurosurgery","first-page":"665","article-title":"Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel","volume":"80","author":"Akers A","year":"2017","unstructured":"Akers A, Al-Shahi Salman R, Awad IA,  Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel. Neurosurgery. 2017;80(5):665\u2013680."},{"issue":"7","key":"b6","series-title":"AJNR Am J Neuroradiol","first-page":"1209","article-title":"Quantitative susceptibility mapping in cerebral cavernous malformations: clinical correlations","volume":"37","author":"Tan H","year":"2016","unstructured":"Tan H, Zhang L, Mikati AG,  Quantitative susceptibility mapping in cerebral cavernous malformations: clinical correlations. AJNR Am J Neuroradiol. 2016;37(7):1209\u20131215."},{"issue":"1","key":"b7","series-title":"J Neurosurg","first-page":"102","article-title":"Vascular permeability and iron deposition biomarkers in longitudinal follow-up of cerebral cavernous malformations","volume":"127","author":"Girard R","year":"2017","unstructured":"Girard R, Fam MD, Zeineddine HA,  Vascular permeability and iron deposition biomarkers in longitudinal follow-up of cerebral cavernous malformations. J Neurosurg. 2017;127(1):102\u2013110."},{"issue":"1","key":"b8","series-title":"Stroke","first-page":"31","article-title":"Trial readiness of cavernous malformations with symptomatic hemorrhage, part II: biomarkers and trial modeling","volume":"55","author":"Hage S","year":"2024","unstructured":"Hage S, Kinkade S, Girard R,  Trial readiness of cavernous malformations with symptomatic hemorrhage, part II: biomarkers and trial modeling. Stroke. 2024;55(1):31\u201339."},{"issue":"1","key":"b9","series-title":"Stroke","first-page":"22","article-title":"Trial readiness of cavernous malformations with symptomatic hemorrhage, part I: event rates and clinical outcome","volume":"55","author":"Flemming KD","year":"2024","unstructured":"Flemming KD, Kim H, Hage S,  Trial readiness of cavernous malformations with symptomatic hemorrhage, part I: event rates and clinical outcome. Stroke. 2024;55(1):22\u201330."},{"issue":"3","key":"b10","series-title":"Magn Reson Med","first-page":"777","article-title":"Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging","volume":"66","author":"Liu T","year":"2011","unstructured":"Liu T, Liu J, de Rochefort L,  Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging. Magn Reson Med. 2011;66(3):777\u2013783."},{"issue":"2","key":"b11","series-title":"Stroke","first-page":"598","article-title":"Dynamic permeability and quantitative susceptibility: related imaging biomarkers in cerebral cavernous malformations","volume":"45","author":"Mikati AG","year":"2014","unstructured":"Mikati AG, Tan H, Shenkar R,  Dynamic permeability and quantitative susceptibility: related imaging biomarkers in cerebral cavernous malformations. Stroke. 2014;45(2):598\u2013601."},{"issue":"7","key":"b12","series-title":"Invest Radiol","first-page":"498","article-title":"Evaluation of iron content in human cerebral cavernous malformation using quantitative susceptibility mapping","volume":"49","author":"Tan H","year":"2014","unstructured":"Tan H, Liu T, Wu Y,  Evaluation of iron content in human cerebral cavernous malformation using quantitative susceptibility mapping. Invest Radiol. 2014;49(7):498\u2013504."},{"issue":"12","key":"b13","series-title":"Angioma Alliance Scientific Advisory Board. Stroke","first-page":"3222","article-title":"Hemorrhage from cavernous malformations of the brain: definition and reporting standards","volume":"39","author":"Al-Shahi Salman R","year":"2008","unstructured":"Al-Shahi Salman R, Berg MJ, Morrison L, Awad IA. Hemorrhage from cavernous malformations of the brain: definition and reporting standards. Angioma Alliance Scientific Advisory Board. Stroke. 2008;39(12):3222\u20133230."},{"issue":"6","key":"b14","series-title":"IEEE Trans Syst, Man, Cybern","first-page":"610","article-title":"Textural features for image classification","volume":"SMC-3","author":"Haralick RM","year":"1973","unstructured":"Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst, Man, Cybern. 1973;SMC-3(6):610-621."},{"key":"b15","first-page":"16012","article-title":"Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA\/TCIA data set","volume":"2","author":"Li H","year":"2016","unstructured":"Li H, Zhu Y, Burnside ES,  Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA\/TCIA data set. NPJ Breast Cancer.2016;2:16012."},{"key":"b16","article-title":"Applied Regression Analysis: Wiley Series in Probability and Statistics","author":"Draper NR","year":"1998","unstructured":"Draper NR, Smith H. Applied Regression Analysis: Wiley Series in Probability and Statistics. 3rd ed. John Wiley & Sons, Inc;1998."},{"issue":"5","key":"b17","series-title":"Am J Public Health","first-page":"726","article-title":"Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods","volume":"86","author":"Aickin M","year":"1996","unstructured":"Aickin M, Gensler H. Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods. Am J Public Health. 1996;86(5):726\u2013728."},{"issue":"4","key":"b18","series-title":"Semin Nucl Med","first-page":"283","article-title":"Basic principles of ROC analysis","volume":"8","author":"Metz CE","year":"1978","unstructured":"Metz CE. Basic principles of ROC analysis. 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Neurosurgery. 2000;46(6):1454\u20131459."},{"issue":"2","key":"b2","series-title":"Lancet Neurol","first-page":"166","article-title":"Clinical course of untreated cerebral cavernous malformations: a meta-analysis of individual patient data","volume":"15","author":"Horne MA","year":"2016","unstructured":"Horne MA, Flemming KD, Su IC,  Clinical course of untreated cerebral cavernous malformations: a meta-analysis of individual patient data. Lancet Neurol. 2016;15(2):166\u2013173."},{"issue":"3","key":"b3","series-title":"J Neurosurg","first-page":"1147","article-title":"Subclinical imaging changes in cerebral cavernous angiomas during prospective surveillance","volume":"134","author":"Carrion-Penagos J","year":"2021","unstructured":"Carrion-Penagos J, Zeineddine HA, Polster SP,  Subclinical imaging changes in cerebral cavernous angiomas during prospective surveillance. J Neurosurg. 2021;134(3):1147\u20131154."},{"issue":"5","key":"b4","series-title":"J Neurosurg","first-page":"1159","article-title":"Contemporary cohort of cerebral cavernous malformations: natural history and utility of follow-up MRI","volume":"141","author":"Flemming KD","year":"2024","unstructured":"Flemming KD, Brown RD, Lanzino G. Contemporary cohort of cerebral cavernous malformations: natural history and utility of follow-up MRI. J Neurosurg. 2024;141(5):1159\u20131167."},{"issue":"5","key":"b5","series-title":"Neurosurgery","first-page":"665","article-title":"Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel","volume":"80","author":"Akers A","year":"2017","unstructured":"Akers A, Al-Shahi Salman R, Awad IA,  Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel. 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J Neurosurg. 2017;127(1):102\u2013110."},{"issue":"1","key":"b8","series-title":"Stroke","first-page":"31","article-title":"Trial readiness of cavernous malformations with symptomatic hemorrhage, part II: biomarkers and trial modeling","volume":"55","author":"Hage S","year":"2024","unstructured":"Hage S, Kinkade S, Girard R,  Trial readiness of cavernous malformations with symptomatic hemorrhage, part II: biomarkers and trial modeling. Stroke. 2024;55(1):31\u201339."},{"issue":"1","key":"b9","series-title":"Stroke","first-page":"22","article-title":"Trial readiness of cavernous malformations with symptomatic hemorrhage, part I: event rates and clinical outcome","volume":"55","author":"Flemming KD","year":"2024","unstructured":"Flemming KD, Kim H, Hage S,  Trial readiness of cavernous malformations with symptomatic hemorrhage, part I: event rates and clinical outcome. Stroke. 2024;55(1):22\u201330."},{"issue":"3","key":"b10","series-title":"Magn Reson Med","first-page":"777","article-title":"Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging","volume":"66","author":"Liu T","year":"2011","unstructured":"Liu T, Liu J, de Rochefort L,  Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging. Magn Reson Med. 2011;66(3):777\u2013783."},{"issue":"2","key":"b11","series-title":"Stroke","first-page":"598","article-title":"Dynamic permeability and quantitative susceptibility: related imaging biomarkers in cerebral cavernous malformations","volume":"45","author":"Mikati AG","year":"2014","unstructured":"Mikati AG, Tan H, Shenkar R,  Dynamic permeability and quantitative susceptibility: related imaging biomarkers in cerebral cavernous malformations. Stroke. 2014;45(2):598\u2013601."},{"issue":"7","key":"b12","series-title":"Invest Radiol","first-page":"498","article-title":"Evaluation of iron content in human cerebral cavernous malformation using quantitative susceptibility mapping","volume":"49","author":"Tan H","year":"2014","unstructured":"Tan H, Liu T, Wu Y,  Evaluation of iron content in human cerebral cavernous malformation using quantitative susceptibility mapping. Invest Radiol. 2014;49(7):498\u2013504."},{"issue":"12","key":"b13","series-title":"Angioma Alliance Scientific Advisory Board. Stroke","first-page":"3222","article-title":"Hemorrhage from cavernous malformations of the brain: definition and reporting standards","volume":"39","author":"Al-Shahi Salman R","year":"2008","unstructured":"Al-Shahi Salman R, Berg MJ, Morrison L, Awad IA. Hemorrhage from cavernous malformations of the brain: definition and reporting standards. Angioma Alliance Scientific Advisory Board. Stroke. 2008;39(12):3222\u20133230."},{"issue":"6","key":"b14","series-title":"IEEE Trans Syst, Man, Cybern","first-page":"610","article-title":"Textural features for image classification","volume":"SMC-3","author":"Haralick RM","year":"1973","unstructured":"Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst, Man, Cybern. 1973;SMC-3(6):610-621."},{"key":"b15","first-page":"16012","article-title":"Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA\/TCIA data set","volume":"2","author":"Li H","year":"2016","unstructured":"Li H, Zhu Y, Burnside ES,  Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA\/TCIA data set. NPJ Breast Cancer.2016;2:16012."},{"key":"b16","article-title":"Applied Regression Analysis: Wiley Series in Probability and Statistics","author":"Draper NR","year":"1998","unstructured":"Draper NR, Smith H. Applied Regression Analysis: Wiley Series in Probability and Statistics. 3rd ed. John Wiley & Sons, Inc;1998."},{"issue":"5","key":"b17","series-title":"Am J Public Health","first-page":"726","article-title":"Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods","volume":"86","author":"Aickin M","year":"1996","unstructured":"Aickin M, Gensler H. Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods. Am J Public Health. 1996;86(5):726\u2013728."},{"issue":"4","key":"b18","series-title":"Semin Nucl Med","first-page":"283","article-title":"Basic principles of ROC analysis","volume":"8","author":"Metz CE","year":"1978","unstructured":"Metz CE. Basic principles of ROC analysis. 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