Novel AI-Driven Infant Meningitis Screening from High Resolution Ultrasound Imaging

Hassan Sial, Francesc Carandell, Sara Ajanovic, Javier Jiménez, Rita Quesada, Fabião Santos, W. Chris Buck, Muhammad Sidat, UNITED Study Consortium, Quique Bassat, Beatrice Jobst, Paula Petrone
{"title":"Novel AI-Driven Infant Meningitis Screening from High Resolution Ultrasound Imaging","authors":"Hassan Sial, Francesc Carandell, Sara Ajanovic, Javier Jiménez, Rita Quesada, Fabião Santos, W. Chris Buck, Muhammad Sidat, UNITED Study Consortium, Quique Bassat, Beatrice Jobst, Paula Petrone","doi":"10.1101/2024.08.29.24312709","DOIUrl":null,"url":null,"abstract":"<strong>Background</strong> Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar punctures (LP), to obtain and analyze cerebrospinal fluid (CSF). Despite being standard practice, LPs are invasive, pose risks for the patient and often yield negative results, either because of the contamination with red blood cells derived from the puncture itself, or due to the disease’s relatively low incidence due to the protocolized requirement to do LPs to discard a life-threatening infection in spite its relatively low incidence. Furthermore, in low-income settings, where the incidence is the highest, LPs and CSF exams are rarely feasible, and suspected meningitis cases are generally treated empirically. There’s a growing need for non-invasive, accurate diagnostic methods.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Radiology and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.29.24312709","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 Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar punctures (LP), to obtain and analyze cerebrospinal fluid (CSF). Despite being standard practice, LPs are invasive, pose risks for the patient and often yield negative results, either because of the contamination with red blood cells derived from the puncture itself, or due to the disease’s relatively low incidence due to the protocolized requirement to do LPs to discard a life-threatening infection in spite its relatively low incidence. Furthermore, in low-income settings, where the incidence is the highest, LPs and CSF exams are rarely feasible, and suspected meningitis cases are generally treated empirically. There’s a growing need for non-invasive, accurate diagnostic methods.
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
通过高分辨率超声波成像进行新型人工智能驱动的婴儿脑膜炎筛查
背景 婴儿脑膜炎是一种危及生命的疾病,需要及时准确的诊断,以防止严重后果或死亡。金标准诊断需要进行腰椎穿刺(LP),以获取和分析脑脊液(CSF)。尽管腰椎穿刺是标准做法,但它是侵入性的,对病人有风险,而且结果往往是阴性的,这可能是由于穿刺本身产生的红细胞污染,也可能是由于这种疾病的发病率相对较低,尽管其发病率相对较低,但由于协议要求做腰椎穿刺以排除危及生命的感染。此外,在发病率最高的低收入地区,LP 和 CSF 检查很少可行,疑似脑膜炎病例通常采用经验性治疗。现在越来越需要无创、准确的诊断方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Auto-segmentation of hemi-diaphragms in free-breathing dynamic MRI of pediatric subjects with thoracic insufficiency syndrome Dynamic MR of muscle contraction during electrical muscle stimulation as a potential diagnostic tool for neuromuscular disease Deriving Imaging Biomarkers for Primary Central Nervous System Lymphoma Using Deep Learning Exploring subthreshold functional network alterations in women with phenylketonuria by higher criticism Beyond Algorithms: The Impact of Simplified CNN Models and Multifactorial Influences on Radiological Image Analysis
×
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