2021
DOI: 10.1016/j.wneu.2021.05.103
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Computed Tomography Angiography versus Digital Subtraction Angiography as a Primary Diagnostic Tool in Nontraumatic Subarachnoid Hemorrhage: Cost-Effectiveness Analysis Study

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Cited by 8 publications
(6 citation statements)
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“…The cost of DSA imaging compared with MRI/A has been studied in the context of other vascular pathology, such as subarachnoid hemorrhage, 32,33 but this may be difficult to extrapolate to the moyamoya patient population, where imaging cost is less clear in the literature. Our data show a substantial difference-a 6.5-fold savings by the use of MRI/A over DSA-in the cumulative hospital and professional billing costs between these 2 imaging modalities.…”
Section: Cost Comparisonsmentioning
confidence: 99%
“…The cost of DSA imaging compared with MRI/A has been studied in the context of other vascular pathology, such as subarachnoid hemorrhage, 32,33 but this may be difficult to extrapolate to the moyamoya patient population, where imaging cost is less clear in the literature. Our data show a substantial difference-a 6.5-fold savings by the use of MRI/A over DSA-in the cumulative hospital and professional billing costs between these 2 imaging modalities.…”
Section: Cost Comparisonsmentioning
confidence: 99%
“…97 DSA alone incurs more costs than the non-invasive imaging modalities of CTA or MRA. Despite this, a recent cost-effectiveness analysis of CTA versus DSA as a primary diagnostic tool in nontraumatic subarachnoid hemorrhage concluded that DSA was more cost-effective, especially in the setting of a likely intervention, 98 suggesting that cost considerations are significantly impacted by the clinical scenario.…”
Section: Limitationsmentioning
confidence: 99%
“…DSA is of great significance in the clinical diagnosis of vascular diseases. It is the most effective detection method in the interventional diagnosis and treatment of cardiovascular and cerebrovascular diseases and is the “gold standard” for the diagnosis of vascular diseases [ 11 , 12 ]. In recent years, deep learning has been widely used in the field of image processing by virtue of its ultra-high prediction accuracy in recognition applications, and the use of deep learning to process some tasks is simpler and more effective than other algorithms.…”
Section: Introductionmentioning
confidence: 99%