Literature DB >> 35981763

Optimizing the Definition of Ischemic Core in CT Perfusion: Influence of Infarct Growth and Tissue-Specific Thresholds.

A Rodríguez-Vázquez1, C Laredo1, A Renú1,2,3, S Rudilosso1,2, L Llull1,2,3, S Amaro1,2,3, V Obach1,2,3, V Vera1, A Páez4, L Oleaga4, X Urra5,2,3, Á Chamorro1,2,3.   

Abstract

BACKGROUND AND
PURPOSE: CTP allows estimating ischemic core in patients with acute stroke. However, these estimations have limited accuracy compared with MR imaging. We studied the effect of applying WM- and GM-specific thresholds and analyzed the infarct growth from baseline imaging to reperfusion.
MATERIALS AND METHODS: This was a single-center cohort of consecutive patients (n = 113) with witnessed strokes due to proximal carotid territory occlusions with baseline CT perfusion, complete reperfusion, and follow-up DWI. We segmented GM and WM, coregistered CTP with DWI, and compared the accuracy of the different predictions for each voxel on DWI through receiver operating characteristic analysis. We assessed the yield of different relative CBF thresholds to predict the final infarct volume and an estimated infarct growth-corrected volume (subtracting the infarct growth from baseline imaging to complete reperfusion) for a single relative CBF threshold and GM- and WM-specific thresholds.
RESULTS: The fixed threshold underestimated lesions in GM and overestimated them in WM. Double GM- and WM-specific thresholds of relative CBF were superior to fixed thresholds in predicting infarcted voxels. The closest estimations of the infarct on DWI were based on a relative CBF of 25% for a single threshold, 35% for GM, and 20% for WM, and they decreased when correcting for infarct growth: 20% for a single threshold, 25% for GM, and 15% for WM. The combination of 25% for GM and 15% for WM yielded the best prediction.
CONCLUSIONS: GM- and WM-specific thresholds result in different estimations of ischemic core in CTP and increase the global accuracy. More restrictive thresholds better estimate the actual extent of the infarcted tissue.
© 2022 by American Journal of Neuroradiology.

Entities:  

Year:  2022        PMID: 35981763      PMCID: PMC9451632          DOI: 10.3174/ajnr.A7601

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   4.966


  33 in total

1.  Time-Dependent Computed Tomographic Perfusion Thresholds for Patients With Acute Ischemic Stroke.

Authors:  Christopher D d'Esterre; Mari E Boesen; Seong Hwan Ahn; Pooneh Pordeli; Mohamed Najm; Priyanka Minhas; Paniz Davari; Enrico Fainardi; Marta Rubiera; Alexander V Khaw; Andrea Zini; Richard Frayne; Michael D Hill; Andrew M Demchuk; Tolulope T Sajobi; Nils D Forkert; Mayank Goyal; Ting Y Lee; Bijoy K Menon
Journal:  Stroke       Date:  2015-10-29       Impact factor: 7.914

2.  Comparison of CT perfusion summary maps to early diffusion-weighted images in suspected acute middle cerebral artery stroke.

Authors:  John Benson; Seyedmehdi Payabvash; Pascal Salazar; Bharathi Jagadeesan; Christopher S Palmer; Charles L Truwit; Alexander M McKinney
Journal:  Eur J Radiol       Date:  2015-01-12       Impact factor: 3.528

3.  Influence of Recanalization and Time of Cerebral Ischemia on Tissue Outcome after Endovascular Stroke Treatment on Computed Tomography Perfusion.

Authors:  Anselm Angermaier; Alexander V Khaw; Michael Kirsch; Christof Kessler; Soenke Langner
Journal:  J Stroke Cerebrovasc Dis       Date:  2015-07-15       Impact factor: 2.136

4.  Time is brain--quantified.

Authors:  Jeffrey L Saver
Journal:  Stroke       Date:  2005-12-08       Impact factor: 7.914

Review 5.  Automated CT perfusion imaging for acute ischemic stroke: Pearls and pitfalls for real-world use.

Authors:  Achala Vagal; Max Wintermark; Kambiz Nael; Andrew Bivard; Mark Parsons; Aaron W Grossman; Pooja Khatri
Journal:  Neurology       Date:  2019-10-21       Impact factor: 9.910

6.  Artificial Neural Network Computer Tomography Perfusion Prediction of Ischemic Core.

Authors:  Aimen S Kasasbeh; Søren Christensen; Mark W Parsons; Bruce Campbell; Gregory W Albers; Maarten G Lansberg
Journal:  Stroke       Date:  2019-05-16       Impact factor: 7.914

7.  Aggressive mechanical clot disruption: a safe adjunct to thrombolytic therapy in acute stroke?

Authors:  Elizabeth A Noser; Hashem M Shaltoni; Christiana E Hall; Andrei V Alexandrov; Zsolt Garami; Edwin D Cacayorin; Joon K Song; James C Grotta; Morgan S Campbell
Journal:  Stroke       Date:  2004-12-29       Impact factor: 7.914

8.  Optimal perfusion computed tomographic thresholds for ischemic core and penumbra are not time dependent in the clinically relevant time window.

Authors:  Yujie Qiao; Guangming Zhu; James Patrie; Wenjun Xin; Patrik Michel; Ashraf Eskandari; Tudor Jovin; Max Wintermark
Journal:  Stroke       Date:  2014-03-13       Impact factor: 7.914

9.  Evaluation of hyperacute infarct volume using ASPECTS and brain CT perfusion core volume.

Authors:  Jelle Demeestere; Carlos Garcia-Esperon; Pablo Garcia-Bermejo; Fouke Ombelet; Patrick McElduff; Andrew Bivard; Mark Parsons; Christopher Levi
Journal:  Neurology       Date:  2017-05-17       Impact factor: 9.910

10.  Volumetric and Spatial Accuracy of Computed Tomography Perfusion Estimated Ischemic Core Volume in Patients With Acute Ischemic Stroke.

Authors:  Jan W Hoving; Henk A Marquering; Charles B L M Majoie; Nawaf Yassi; Gagan Sharma; David S Liebeskind; Aad van der Lugt; Yvo B Roos; Wim van Zwam; Robert J van Oostenbrugge; Mayank Goyal; Jeffrey L Saver; Tudor G Jovin; Gregory W Albers; Antoni Davalos; Michael D Hill; Andrew M Demchuk; Serge Bracard; Francis Guillemin; Keith W Muir; Philip White; Peter J Mitchell; Geoffrey A Donnan; Stephen M Davis; Bruce C V Campbell
Journal:  Stroke       Date:  2018-10       Impact factor: 7.914

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