ArticleLa Radiologia medica2021
Comparison of a Bayesian estimation algorithm and singular value decomposition algorithms for 80-detector row CT perfusion in patients with acute ischemic stroke.
Article in La Radiologia medica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 14 citations in OpenAlex.
- Understanding CT Perfusion in Acute Ischemic Stroke: How Algorithms Shape Perfusion Maps.Diagnostics (Basel, Switzerland) · 2026Review
- Time series-derived fractal dimension of CT perfusion in acute ischemic stroke: a promising marker for hypoperfused tissue quantification.International journal of computer assisted radiology and surgery · 2026Article
- Differentiating effective salvage from ineffective delayed compensation in anterior circulation stroke: a dynamic quantitative collateral index.Frontiers in medicine · 2026Article
- Investigation of the hyperperfusion phenomenon following carotid artery stenting using preoperative computed tomography perfusion imaging.Acta neurochirurgica · 2025Article
- Deep learning-based correction for time truncation in cerebral computed tomography perfusion.Radiological physics and technology · 2024Article
- Cerebral hemodynamics in symptomatic anterior circulation intracranial stenosis measured by angiography-based quantitative flow ratio: association with CT perfusion.European radiology · 2023Article
- Correlation between pretreatment and follow-up infarct volume using CT perfusion imaging: the Bayesian versus singular value decomposition method.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023Article
- Artificial Intelligence and Machine Learning in the Diagnosis and Management of Stroke: A Narrative Review of United States Food and Drug Administration-Approved Technologies.Journal of clinical medicine · 2023Review
- A Narrative Review on LI-RADS Algorithm in Liver Tumors: Prospects and Pitfalls.Diagnostics (Basel, Switzerland) · 2022Review
- Imaging Features of Post Main Hepatectomy Complications: The Radiologist Challenging.Diagnostics (Basel, Switzerland) · 2022Review
- Conventional, functional and radiomics assessment for intrahepatic cholangiocarcinoma.Infectious agents and cancer · 2022Article
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3 authors at 1 institution in 1 country.
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Abstract
purposeA variety of postprocessing algorithms for CT perfusion are available, with substantial differences in terms of quantitative maps. Although potential advantages of a Bayesian estimation algorithm are suggested, direct comparison with other algorithms in clinical settings remains scarce. We aimed to compare performance of a Bayesian estimation algorithm and singular value decomposition (SVD) algorithms for the assessment of acute ischemic stroke using an 80-detector row CT perfusion.
methodsCT perfusion data of 36 patients with acute ischemic stroke were analyzed using the Vitrea implemented a standard SVD algorithm, a reformulated SVD algorithm and a Bayesian estimation algorithm. Correlations and statistical differences between affected and contralateral sides of quantitative parameters (cerebral blood volume [CBV], cerebral blood flow [CBF], mean transit time [MTT], time to peak [TTP] and delay) were analyzed. Agreement of the CT perfusion-estimated and the follow-up diffusion-weighted imaging-derived infarct volume were evaluated by nonparametric Passing-Bablok regression analysis.
resultsCBF and MTT of the Bayesian estimation algorithm were substantially different and showed a better correlation with the standard SVD algorithm (ρ = 0.78 and 0.80, p < 0.001) than with the reformulated SVD algorithm (ρ = 0.59 and 0.39, p < 0.001). There is no significant difference in MTT only when using the reformulated SVD algorithm (p = 0.217). Regarding the regression lines, the slope and intercept were nearly ideal with the Bayesian estimation algorithm (y = 2.42 x-6.51; ρ = 0.60, p < 0.001) in comparison with the SVD algorithms.
conclusionsThe Bayesian estimation algorithm can lead to a better performance compared with the SVD algorithms in the assessment of acute ischemic stroke because of better delineation of abnormal perfusion areas and accurate estimation of infarct volume.
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