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Accuracy of thin-slice model-based iterative reconstruction designed for brain CT to diagnose acute ischemic stroke in the middle cerebral artery territory: a multicenter study
Purpose Model-based iterative reconstruction (MBIR) yields higher spatial resolution and a lower image noise than conventional reconstruction methods. We hypothesized that thin-slice MBIR designed for brain CT could improve the detectability of acute ischemic stroke in the middle cerebral artery (MC...
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Published in: | Neuroradiology 2021-12, Vol.63 (12), p.2013-2021 |
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Main Authors: | , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Purpose
Model-based iterative reconstruction (MBIR) yields higher spatial resolution and a lower image noise than conventional reconstruction methods. We hypothesized that thin-slice MBIR designed for brain CT could improve the detectability of acute ischemic stroke in the middle cerebral artery (MCA) territory.
Methods
Included were 41 patients with acute ischemic stroke in the MCA territory; they were seen at 4 medical centers. The controls were 39 subjects without acute stroke. Images were reconstructed with hybrid IR and with MBIR designed for brain CT at slice thickness of 2 mm. We measured the image noise in the ventricle and compared the contrast-to-noise ratio (CNR) in the ischemic lesion. We analyzed the ability of reconstructed images to detect ischemic lesions using receiver operating characteristics (ROC) analysis; 8 observers read the routine clinical hybrid IR with 5 mm-thick images, while referring to 2 mm-thick hybrid IR images or MBIR images.
Results
The image noise was significantly lower on MBIR- than hybrid IR images (1.2 vs. 3.4,
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ISSN: | 0028-3940 1432-1920 |
DOI: | 10.1007/s00234-021-02745-4 |