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0.23-Tesla MRI to differentiate between ischaemic and haemorrhagic strokes within 24 hours of onset: a combined experimental-clinical study. | LitMetric

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Article Abstract

Background And Purpose: The low-field MRI is a promising tool to accurately diagnose strokes. We here report our study on the accuracy of a 0.23-Tesla (0.23-T) MRI using the haematoma enhanced inversion recovery (HEIR) sequence to detect acute ischaemic stroke (AIS) and intracerebral haemorrhage (ICH) within 24 hours of symptom onset.

Methods: A novel HEIR sequence based on fluid-attenuated inversion recovery T1-weighted, with a scanning time of 1 min and 17 s, was developed using an ICH and AIS pig model on a 0.23-T MRI. Images of the pig model were obtained hourly for 24 hours in order to monitor value changes on T1/T2 and verify the differential diagnosis of AIS and ICH. Then, 30 patients with AIS and 30 patients with ICH with confirmed diagnoses by 3T-MRI/CT were included. Diagnostic criteria on a 0.23-T MRI for ICH was the hyperintensity signal on both the diffusion-weighted imaging (DWI) and HEIR sequence, while for AIS was the hyperintensity on DWI and isointensity on the HEIR sequence. Two blinded raters independently assessed the images obtained by the 0.23-T MRI for the presence of ICH/AIS.

Results: In the pig model, setting the inversion time to 800 ms enabled clear differentiation of ICH from brain parenchymal tissue and AIS. In real patients, a correct 0.23-T MRI diagnosis of either an AIS or ICH was made in all 60 patients within 24 hours of symptom onset (100% overall accuracy). No adverse events occurred.

Conclusions: The 0.23-T MRI may have the potential to differentiate cerebral haemorrhage from cerebral infarction with both speed and accuracy, making brain MRI scans easier, faster and cheaper. It might be possible to improve the screening imaging process for strokes in the emergency room. Further multicentre studies are needed to validate our findings.

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http://dx.doi.org/10.1136/svn-2024-003592DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12415649PMC

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