{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T23:00:59Z","timestamp":1789340459206,"version":"build-2803163510"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T00:00:00Z","timestamp":1702252800000},"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. Microbiol."],"abstract":"<jats:p>Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.<\/jats:p>","DOI":"10.3389\/fmicb.2023.1308149","type":"journal-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T09:50:29Z","timestamp":1702288229000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":23,"title":["MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations"],"prefix":"10.3389","volume":"14","author":[{"given":"Xingyu","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fanxuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenglong","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoqiang","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanchan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yinda","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jincen","family":"Shuai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yilei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenyue","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luhuan","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enna","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiamin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengjing","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqian","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darong","family":"Hai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wangzheng","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengxi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shichao","family":"Quan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feifei","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,12,11]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.4103\/0028-3886.349627","article-title":"Cerebrospinal fluid flow analysis in tuberculous meningitis using phase contrast technique on 3 tesla MRI: a new paradigm and our initial experience","volume":"70","author":"Ashta","year":"2022","journal-title":"Neurol. 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Ed.)"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1007\/s00234-021-02678-y","article-title":"MR vessel wall imaging in tubercular meningitis","volume":"63","author":"Choudhary","year":"2021","journal-title":"Neuroradiology"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1016\/j.jmir.2019.09.005","article-title":"Machine learning and deep learning in medical imaging: intelligent imaging","volume":"50","author":"Currie","year":"2019","journal-title":"J. Med. Imaging Radiat. Sci."},{"key":"ref10","doi-asserted-by":"publisher","first-page":"S293","DOI":"10.1093\/cid\/ciy611","article-title":"Levofloxacin pharmacokinetics\/pharmacodynamics, dosing, susceptibility breakpoints, and artificial intelligence in the treatment of multidrug-resistant tuberculosis","volume":"67","author":"Deshpande","year":"2018","journal-title":"Clin. Infect. 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Med."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s11910-017-0796-0","article-title":"Tuberculous meningitis in children and adults: new insights for an ancient foe","volume":"17","author":"Mezochow","year":"2017","journal-title":"Curr. Neurol. Neurosci. Rep."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"793","DOI":"10.1148\/radiol.2018182619","article-title":"Perinodular Radiomic features to assess nodule microenvironment: does it help to distinguish malignant versus benign lung nodules?","volume":"290","author":"Nishino","year":"2019","journal-title":"Radiology"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"59","DOI":"10.3969\/J.ISSN.1672-8270.2019.10.017","article-title":"Risk factors analysis of abnormal magnetic resonance angiography in patients with tuberculous meningitis","volume":"16","author":"Pei","year":"2019","journal-title":"Chin. Med. 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Dis."},{"key":"ref36","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1093\/bmb\/ldv003","article-title":"Tuberculous meningitis: advances in diagnosis and treatment","volume":"113","author":"T\u00f6r\u00f6k","year":"2015","journal-title":"Br. Med. Bull."},{"key":"ref37","doi-asserted-by":"publisher","first-page":"OD03-05","DOI":"10.7860\/JCDR\/2015\/13885.6497","article-title":"Immunologic cerebral vasculitis and extrapulmonary tuberculosis: an uncommon association","volume":"9","author":"Wang","year":"2015","journal-title":"J. Clin. Diagn. Res."},{"key":"ref38","doi-asserted-by":"publisher","first-page":"106464","DOI":"10.1016\/j.compbiomed.2022.106464","article-title":"Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism","volume":"153","author":"Wang","year":"2023","journal-title":"Comput. Biol. Med."},{"key":"ref39","doi-asserted-by":"publisher","first-page":"bbac463","DOI":"10.1093\/bib\/bbac463","article-title":"Predicting the potential human lncRNA-miRNA interactions based on graph convolution network with conditional random field","volume":"23","author":"Wang","year":"2022","journal-title":"Brief. Bioinform."},{"key":"ref40","doi-asserted-by":"publisher","first-page":"3009","DOI":"10.1007\/s00415-019-09523-6","article-title":"Clinical features, outcomes and prognostic factors of tuberculous meningitis in adults worldwide: systematic review and meta-analysis","volume":"266","author":"Wen","year":"2019","journal-title":"J. Neurol."},{"key":"ref41","year":"2023"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1038\/nrneurol.2017.120","article-title":"Tuberculous meningitis","volume":"13","author":"Wilkinson","year":"2017","journal-title":"Nat. Rev. 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