Improved parametric mapping of CT perfusion in acute ischemic stroke

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dc.contributor.authorWu, Qi
dc.contributor.authorWolsztynski, Eric
dc.contributor.authorHuang, Jian
dc.contributor.authorChen, X.
dc.contributor.authorWu, R.
dc.contributor.authorMou, Tian
dc.contributor.funderScience Foundation Ireland (SFI), 12/RC/2289-P2
dc.contributor.funderNational Natural Science Foundation of China (NSFC), 82202246
dc.contributor.funderGuangDong Basic and Applied Basic Research Foundation, 2023A1515011481
dc.date.accessioned2026-03-11T12:50:01Z
dc.date.available2026-03-11T12:50:01Z
dc.date.issued2025
dc.description.abstractComputed Tomography Perfusion (CTP) imaging is crucial for assessing cerebral blood flow in acute ischemic stroke, but traditional deconvolution methods like Singular Value Decomposition (SVD) often lack physiological accuracy and are sensitive to noise. This study introduces a clustering-based deconvolution framework integrated with the Adiabatic Approximation to Tissue Homogeneity (AATH) model to address these limitations. By grouping voxels with similar timedensity curves and applying the AATH model, our method incorporates physiological constraints and reduces noise, leading to more accurate estimates of perfusion parameters such as cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to maximum (Tmax). Simulations showed that the approach outperforms the SVD method, particularly in recovering accurate parameter maps even under mismatched model assumptions. The method's robustness and potential for improved clinical outcomes, such as better differentiation between salvageable and irreversibly damaged tissue, highlight its value for precision diagnostics in cerebrovascular diseases.en
dc.description.sponsorshipThis work was supported in part by Science Foundation Ireland (12/RC/2289-P2) at the Insight SFI Research Centre for Data Analytics at UCC, the National Natural Science Foundation of China (82202246), the Stable Support Project of Shenzhen (20231121094305001) and the GuangDong Basic and Applied Basic Research Foundation (2023A1515011481).
dc.description.versionAccepted Version
dc.format.extent1
dc.format.mimetypeapplication/pdfen
dc.identifier.authororcidWu, Qi
dc.identifier.authororcidWolsztynski, Eric§0000-0001-9770-9769
dc.identifier.authororcidHuang, Jian§0000-0002-0862-1384
dc.identifier.authororcidChen, X.
dc.identifier.authororcidWu, R.
dc.identifier.authororcidMou, Tian
dc.identifier.citationWu, Q, Wolsztynski, E, Huang, J, Chen, X, Wu, R & Mou, T 2025, Improved parametric mapping of CT perfusion in acute ischemic stroke. in 2025 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). IEEE. https://doi.org/10.1109/NSS/MIC/RTSD57106.2025.11286508
dc.identifier.doi10.1109/NSS/MIC/RTSD57106.2025.11286508
dc.identifier.isbn978-1-6654-7768-0
dc.identifier.isbn978-1-6654-7767-3
dc.identifier.otherORCID: /0000-0002-0862-1384/work/208199697
dc.identifier.otherORCID: /0000-0001-9770-9769/work/208200010
dc.identifier.urihttps://hdl.handle.net/10468/18623
dc.language.isoen
dc.publisherIEEE
dc.relation.urihttps://ieeexplore.ieee.org/document/11286508
dc.rights© 2025, IEEE.
dc.rights.accessrightsopen access
dc.statusPeer reviewed
dc.subjectAcute ischemic stroke
dc.subjectPerfusion imaging
dc.subjectCerebrovascular disease
dc.subjectCerebral blood flow
dc.subjectSingular value decomposition
dc.subjectCerebral blood volume
dc.subjectAdiabatic approximation
dc.subjectMean transit time
dc.subject[Maths]
dc.titleImproved parametric mapping of CT perfusion in acute ischemic strokeen
dc.typeConference item
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