Predicting White Matter Hyperintensity: Leveraging Portable Magnetic Resonance Imaging for Accessible Brain Health Screening.

Ian P Johnson, Hailey Brigger, Joel Smith, Emma Peasley, Alison Champagne, Lauren Littig, Dheeraj Lalwani, Gordon Sze, Seyedmehdi Payabvash, Basmah Safdar, Gail D'Onofrio, Charles Wira, Juan Eugenio Iglesias, Matthew S Rosen, Annabel Sorby-Adams, W Taylor Kimberly, Kevin N Sheth, Adam de Havenon
{"title":"Predicting White Matter Hyperintensity: Leveraging Portable Magnetic Resonance Imaging for Accessible Brain Health Screening.","authors":"Ian P Johnson, Hailey Brigger, Joel Smith, Emma Peasley, Alison Champagne, Lauren Littig, Dheeraj Lalwani, Gordon Sze, Seyedmehdi Payabvash, Basmah Safdar, Gail D'Onofrio, Charles Wira, Juan Eugenio Iglesias, Matthew S Rosen, Annabel Sorby-Adams, W Taylor Kimberly, Kevin N Sheth, Adam de Havenon","doi":"10.3174/ajnr.A8734","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and purpose: </strong>Portable MRI (pMRI) has emerged as a cost-effective and accessible tool for the identification of white matter hyperintensities (WMH), an independent risk factor for stroke and dementia. Our objective was to confirm that pMRI can produce accurate WMH measurements and to develop and validate a risk model to predict WMH on pMRI for the purpose of identifying patients who may benefit from pMRI screening.</p><p><strong>Materials and methods: </strong>The development (N=143) and validation (N=127) cohorts included patients without acute neurologic pathology who received a pMRI at a tertiary care hospital between May 2020 and July 2024. The development cohort included pMRIs collected as part of a prospective WMH screening pilot program in the emergency department. The validation cohort was a retrospective collection of pMRIs obtained for separate research purposes. Conventional MRIs (cMRIs) in the validation cohort obtained within 3 months of pMRIs were used for additional validation and device agreement. The primary outcome was WMH burden greater than 10 mL, assessed via an axial T2-FLAIR sequence acquired on a 0.064 T pMRI and quantified using a WMH segmentation software developed to process sequences of any resolution. We used backwards selection to screen candidate variables and report the area under the curve of the resulting model.</p><p><strong>Results: </strong>The final model, which included age, systolic blood pressure >140, atrial fibrillation, and tobacco use, achieved an AUC of 0.83 (95% CI 0.75-0.90) in the development cohort (N=143, 62.4±12.6 years, 44% female, 36% non-white race) and 0.85 (95% CI 0.77-0.92) in the validation cohort (N=127, 65.2±16.8 years, 51% female, 34% non-white race), with similar results using WMH measurements derived from cMRI (N=120, p=0.98, AUC=0.86, 95% CI 0.77-0.93). Additionally, we confirmed agreement in WMH volumes between pMRI and cMRI (N=120, r=0.93, 95% CI 0.90-0.95, p<0.001).</p><p><strong>Conclusions: </strong>The WMH risk score demonstrated accurate performance and reproducibility across cohorts, supporting its potential as a screening tool for identifying patients at risk of significant WMH burden. Appropriately targeted pMRI screening in high-risk individuals could allow providers and patients to proactively manage vascular risk factors and improve neurological outcomes.</p><p><strong>Abbreviations: </strong>pMRI = portable magnetic resonance imaging; cMRI = conventional magnetic resonance imaging; WMH = white matter hyperintensity; hypertension = HTN; diabetes = DM; atrial fibrillation = AFib; systolic blood pressure = SBP; hyperlipidemia = HLD; area under the curve = AUC; receiver operating characteristic = ROC.</p>","PeriodicalId":93863,"journal":{"name":"AJNR. American journal of neuroradiology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AJNR. American journal of neuroradiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3174/ajnr.A8734","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background and purpose: Portable MRI (pMRI) has emerged as a cost-effective and accessible tool for the identification of white matter hyperintensities (WMH), an independent risk factor for stroke and dementia. Our objective was to confirm that pMRI can produce accurate WMH measurements and to develop and validate a risk model to predict WMH on pMRI for the purpose of identifying patients who may benefit from pMRI screening.

Materials and methods: The development (N=143) and validation (N=127) cohorts included patients without acute neurologic pathology who received a pMRI at a tertiary care hospital between May 2020 and July 2024. The development cohort included pMRIs collected as part of a prospective WMH screening pilot program in the emergency department. The validation cohort was a retrospective collection of pMRIs obtained for separate research purposes. Conventional MRIs (cMRIs) in the validation cohort obtained within 3 months of pMRIs were used for additional validation and device agreement. The primary outcome was WMH burden greater than 10 mL, assessed via an axial T2-FLAIR sequence acquired on a 0.064 T pMRI and quantified using a WMH segmentation software developed to process sequences of any resolution. We used backwards selection to screen candidate variables and report the area under the curve of the resulting model.

Results: The final model, which included age, systolic blood pressure >140, atrial fibrillation, and tobacco use, achieved an AUC of 0.83 (95% CI 0.75-0.90) in the development cohort (N=143, 62.4±12.6 years, 44% female, 36% non-white race) and 0.85 (95% CI 0.77-0.92) in the validation cohort (N=127, 65.2±16.8 years, 51% female, 34% non-white race), with similar results using WMH measurements derived from cMRI (N=120, p=0.98, AUC=0.86, 95% CI 0.77-0.93). Additionally, we confirmed agreement in WMH volumes between pMRI and cMRI (N=120, r=0.93, 95% CI 0.90-0.95, p<0.001).

Conclusions: The WMH risk score demonstrated accurate performance and reproducibility across cohorts, supporting its potential as a screening tool for identifying patients at risk of significant WMH burden. Appropriately targeted pMRI screening in high-risk individuals could allow providers and patients to proactively manage vascular risk factors and improve neurological outcomes.

Abbreviations: pMRI = portable magnetic resonance imaging; cMRI = conventional magnetic resonance imaging; WMH = white matter hyperintensity; hypertension = HTN; diabetes = DM; atrial fibrillation = AFib; systolic blood pressure = SBP; hyperlipidemia = HLD; area under the curve = AUC; receiver operating characteristic = ROC.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Concordance between Centiloid quantification and visual interpretation of amyloid PET scans across the Alzheimer's disease continuum. Erratum. Dissociation of Structural and Functional Connectivity and Metabolism in the Neocortex of Idiopathic Generalized Epilepsy: A Simultaneous PET/MRI Multimodal Study. Language and Memory Network Alterations in Temporal Lobe Epilepsy: A Functional and Structural Connectivity Study. Large core trial: State of Practice.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1