Academic Journal

Artificial Intelligence for Automated DWI/FLAIR Mismatch Assessment on Magnetic Resonance Imaging in Stroke: A Systematic Review

التفاصيل البيبلوغرافية
العنوان: Artificial Intelligence for Automated DWI/FLAIR Mismatch Assessment on Magnetic Resonance Imaging in Stroke: A Systematic Review
المؤلفون: Cecilie Mørck Offersen, Jens Sørensen, Kaining Sheng, Jonathan Frederik Carlsen, Annika Reynberg Langkilde, Akshay Pai, Thomas Clement Truelsen, Michael Bachmann Nielsen
المصدر: Diagnostics, Vol 13, Iss 12, p 2111 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Medicine (General)
مصطلحات موضوعية: MR DWI/FLAIR mismatch, artificial intelligence, machine learning, wake-up stroke, Medicine (General), R5-920
الوصف: We conducted this Systematic Review to create an overview of the currently existing Artificial Intelligence (AI) methods for Magnetic Resonance Diffusion-Weighted Imaging (DWI)/Fluid-Attenuated Inversion Recovery (FLAIR)—mismatch assessment and to determine how well DWI/FLAIR mismatch algorithms perform compared to domain experts. We searched PubMed Medline, Ovid Embase, Scopus, Web of Science, Cochrane, and IEEE Xplore literature databases for relevant studies published between 1 January 2017 and 20 November 2022, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We assessed the included studies using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Five studies fit the scope of this review. The area under the curve ranged from 0.74 to 0.90. The sensitivity and specificity ranged from 0.70 to 0.85 and 0.74 to 0.84, respectively. Negative predictive value, positive predictive value, and accuracy ranged from 0.55 to 0.82, 0.74 to 0.91, and 0.73 to 0.83, respectively. In a binary classification of ±4.5 h from stroke onset, the surveyed AI methods performed equivalent to or even better than domain experts. However, using the relation between time since stroke onset (TSS) and increasing visibility of FLAIR hyperintensity lesions is not recommended for the determination of TSS within the first 4.5 h. An AI algorithm on DWI/FLAIR mismatch assessment focused on treatment eligibility, outcome prediction, and consideration of patient-specific data could potentially increase the proportion of stroke patients with unknown onset who could be treated with thrombolysis.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2075-4418
Relation: https://www.mdpi.com/2075-4418/13/12/2111; https://doaj.org/toc/2075-4418
DOI: 10.3390/diagnostics13122111
URL الوصول: https://doaj.org/article/98021e52f48549fcae3ba7a3498d085a
رقم الانضمام: edsdoj.98021e52f48549fcae3ba7a3498d085a
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20754418
DOI:10.3390/diagnostics13122111