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Lv B, Ran Y, Lv J, Lou X, Tian C. Individualized interpretation for the clinical significance of fluid-attenuated inversion recovery vessel hyperintensity in ischemic stroke and transient ischemic attack: A systematic narrative review. Eur J Radiol 2023; 166:111010. [PMID: 37523872 DOI: 10.1016/j.ejrad.2023.111010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/09/2023] [Accepted: 07/23/2023] [Indexed: 08/02/2023]
Abstract
Fluid-attenuated inversion recovery (FLAIR) vessel hyperintensity(FVH)refers to the hyperintensity corresponding to the arteries in the subarachnoid space. It is caused by critically slowed blood flow and is commonly encountered in patients with large artery steno-occlusions. Quite a few studies have focused on the clinical significance of FLAIR vessel hyperintensity in terms of its relationship to the prognosis of transient ischemic attack (TIA), baseline severity or infarction volume, early neurological deterioration or infarction growth, and functional outcomes in acute ischemic stroke (AIS). However, inconsistent or conflicting findings were common in these studies and caused confusion in the clinical decision-making process guided by this imaging marker. Through reviewing the available studies on the etiologic mechanism of FVH and investigating findings on its clinical significance in AIS and TIA, this review aims to elucidate the key factors for interpreting the clinical significance of FVH individually.
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Affiliation(s)
- Bin Lv
- Department of Neurology, The First Medical Center, Chinese PLA General Hospital, No.28, Fuxing Road, Beijing 100853, China
| | - Ye Ran
- Department of Neurology, The First Medical Center, Chinese PLA General Hospital, No.28, Fuxing Road, Beijing 100853, China
| | - Jinhao Lv
- Department of Radiology, The First Medical Center, Chinese PLA General Hospital, No.28, Fuxing Road, Beijing 100853, China
| | - Xin Lou
- Department of Radiology, The First Medical Center, Chinese PLA General Hospital, No.28, Fuxing Road, Beijing 100853, China.
| | - Chenglin Tian
- Department of Neurology, The First Medical Center, Chinese PLA General Hospital, No.28, Fuxing Road, Beijing 100853, China.
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Yearley AG, Goedmakers CMW, Panahi A, Doucette J, Rana A, Ranganathan K, Smith TR. FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval. Artif Intell Med 2023; 143:102607. [PMID: 37673576 DOI: 10.1016/j.artmed.2023.102607] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 05/30/2023] [Accepted: 06/05/2023] [Indexed: 09/08/2023]
Abstract
Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingly prevalent in the medical field. In the United States, the Food and Drug Administration (FDA) is responsible for regulating AI algorithms as "medical devices" to ensure patient safety. However, recent work has shown that the FDA approval process may be deficient. In this study, we evaluate the evidence supporting FDA-approved neuroalgorithms, the subset of machine learning algorithms with applications in the central nervous system (CNS), through a systematic review of the primary literature. Articles covering the 53 FDA-approved algorithms with applications in the CNS published in PubMed, EMBASE, Google Scholar and Scopus between database inception and January 25, 2022 were queried. Initial searches identified 1505 studies, of which 92 articles met the criteria for extraction and inclusion. Studies were identified for 26 of the 53 neuroalgorithms, of which 10 algorithms had only a single peer-reviewed publication. Performance metrics were available for 15 algorithms, external validation studies were available for 24 algorithms, and studies exploring the use of algorithms in clinical practice were available for 7 algorithms. Papers studying the clinical utility of these algorithms focused on three domains: workflow efficiency, cost savings, and clinical outcomes. Our analysis suggests that there is a meaningful gap between the FDA approval of machine learning algorithms and their clinical utilization. There appears to be room for process improvement by implementation of the following recommendations: the provision of compelling evidence that algorithms perform as intended, mandating minimum sample sizes, reporting of a predefined set of performance metrics for all algorithms and clinical application of algorithms prior to widespread use. This work will serve as a baseline for future research into the ideal regulatory framework for AI applications worldwide.
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Affiliation(s)
- Alexander G Yearley
- Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA; Computational Neuroscience Outcomes Center (CNOC), Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA.
| | - Caroline M W Goedmakers
- Computational Neuroscience Outcomes Center (CNOC), Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA; Department of Neurosurgery, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, Netherlands
| | - Armon Panahi
- The George Washington University School of Medicine and Health Sciences, 2300 I St NW, Washington, DC 20052, USA
| | - Joanne Doucette
- Computational Neuroscience Outcomes Center (CNOC), Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA; School of Pharmacy, MCPHS University, 179 Longwood Ave, Boston, MA 02115, USA
| | - Aakanksha Rana
- Computational Neuroscience Outcomes Center (CNOC), Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA; Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
| | - Kavitha Ranganathan
- Division of Plastic Surgery, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115, USA
| | - Timothy R Smith
- Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA; Computational Neuroscience Outcomes Center (CNOC), Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA
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Fang X, Liao T, Chen J, Wu J, Xu B. The Feasibility Mechanism of Nerve Interventional Thrombectomy for Occlusion of Cranial Artery M1 and M2 Segments. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:6350033. [PMID: 35844440 PMCID: PMC9279091 DOI: 10.1155/2022/6350033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 05/29/2022] [Accepted: 06/01/2022] [Indexed: 11/30/2022]
Abstract
This study was aimed at exploring the feasibility and clinical efficacy of nerve interventional thrombectomy (NIT) to treat occlusion of cranial artery M1 and M2 segments. 80 patients were selected and rolled into a control group (intravenous thrombolysis) and an experimental group (NIT). Patients' vascular recanalization rates following therapy were compared, and the National Institutes of Health Stroke Scale (NIHSS) was used to measure neurological function. The improvement in hemodynamics and the occurrence of adverse responses were compared. The results showed that the experimental group's recanalization rate was up to 74.23%, which was significantly greater than the control group's (P < 0.05). One week after treatment, the neurological function scores in both groups decreased, and the score in the experimental group was only 15.23, which was much lower than that in the control group (P < 0.05). The peak systolic flow rates of the basilar artery, internal carotid artery, and common carotid artery in the experimental group were 132 cm/s, 147 cm/s, and 114 cm/s, respectively, which were lower greatly than those in the control group (P < 0.05). There was no significant difference in incidence of adverse reactions between the two groups (P > 0.05). In summary, NIT showed a significant therapeutic effect on cranial artery occlusion of M1 and M2 segments, can dredge the occluded blood vessels, and effectively improve the neurological deficits of patients, showing reliable feasibility.
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Affiliation(s)
- Xiang Fang
- Division 1 Department of Neurology, Nanping First Hospital, Nanping, 353000 Fujian Province, China
| | - Taijian Liao
- Division 1 Department of Neurology, Nanping First Hospital, Nanping, 353000 Fujian Province, China
| | - Junhui Chen
- Division 1 Department of Neurology, Nanping First Hospital, Nanping, 353000 Fujian Province, China
| | - Juan Wu
- Division 1 Department of Neurology, Nanping First Hospital, Nanping, 353000 Fujian Province, China
| | - Biyu Xu
- Division 1 Department of Neurology, Nanping First Hospital, Nanping, 353000 Fujian Province, China
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