Early and late infarct growth rate in ischemic stroke patients after successful endovascular treatment in early time window: correlation of imaging and clinical factors with clinical outcome

0574833 - PSÚ 2024 RIV CN eng J - Journal Article
Malíková, H. - Křemenová, K. - Lukavský, Jiří - Holešta, M. - Lauer, D. - Koznar, B. - Weichet, J.
Early and late infarct growth rate in ischemic stroke patients after successful endovascular treatment in early time window: correlation of imaging and clinical factors with clinical outcome.
Quantitative Imaging and Surgery. Roč. 13, č. 9 (2023), s. 5770-5782. ISSN 2223-4292. E-ISSN 2223-4306
Institutional support: RVO:68081740
Keywords : computed tomography perfusion (CTP) * core * infarction * progressors
OECD category: Psychology (including human - machine relations)
Impact factor: 2.9, year: 2022
Method of publishing: Open access
https://qims.amegroups.org/article/view/116200/pdf

Background: The prospective study assessed infarct growth rate (IGR) in acute ischemic stroke (AIS) with large vessel occlusion (LVO) after recanalization in early time window. Early IGR (EIGR) and late IGR (LIGR) were correlated with imaging and clinical data, we searched for outcome predictors.Methods: We included 71 consecutive patients. Subjects underwent computed tomography perfusion (CTP) for ischemic core volume assessment at 99.0 minutes (median) from stroke onset, recanalization was performed at 78.0 minutes (median) from CTP. Final infarct volume (FIV) was measured on 24 & PLUSMN, 2 hours imaging follow-up. EIGR was calculated as the core volume/time between stroke onset and CTP, LIGR was calculated as FIV/time between CTP and imaging follow-up. Twenty-two subjects were assessed as poor outcome, 49 as good outcome. Group differences were tested by Mann-Whitney test and & chi,2 test. Bayesian logistic regression models were used to predict clinical outcome, Pearson correlations for the log transformed predictors.Results: Subjects with poor outcome were older, median age 78.0 [interquartile range (IQR): 71.8, 83.8] versus 68.0 (IQR: 57.0, 73.0) years, 95% confidence interval (CI): 6.00 to 16.00, P<0.001. Their stroke severity scale was higher, median 19.0 (IQR: 16.0, 20.0) versus 15.5 (IQR: 10.8, 18.0), 95% CI: 1.00 to 6.00, P<0.001. They had higher EIGR, median 23.9 (IQR: 6.4, 104.0) versus 6.7 (IQR: 1.7, 13.0) mL/h, 95% CI: 3.26 to 53.68, P=0.002, and larger core, median 52.5 (IQR: 13.1, 148.5) versus 10.0 (IQR: 1.4, 20.0) mL, 95% CI: 11.00 to 81.00, P<0.001. In subjects with poor outcome, infarct growth continued after thrombectomy with LIGR 2.0 (IQR: 1.2, 9.7) versus 0.3 (IQR: 0.0, 0.7) mL/h, 95% CI: 1.10 to 6.10, P<0.001, resulting in larger FIV, median 186.5 (IQR: 49.3, 280.8) versus 18.5 (IQR: 8.0, 34.0) mL, 95% CI: 55.30 to 214.00, P<0.001. Strong correlations among predictors were found e.g., core and EIGR (r=0.942), LIGR and FIV (r=0.779), core and FIV (r=0.761). Clinical outcome was best predicted using data from later measurements as FIV and LIGR.Conclusions: Data from later measurements were more predictive, there was no major benefit to use growth over volume data.
Permanent Link: https://hdl.handle.net/11104/0344780