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Is CT-Based Perfusion and Collateral Imaging Sensitive to Time Since Stroke Onset?

ABSTRACT: CT-based perfusion and collateral imaging is increasingly used in the assessment of patients with acute stroke. Time of stroke onset is a critical factor in determining eligibility for and benefit from thrombolysis. Animal studies predict that the volume of ischemic penumbra decreases with time. Here, we evaluate if CT is able to detect a relationship between perfusion or collateral status, as assessed by CT, and time since stroke onset.We studied 53 consecutive patients with proximal vessel occlusions, mean (SD) age of 71.3 (14.9) years, at a mean (SD) of 125.2 (55.3) minutes from onset, using whole-brain CT perfusion (CTp) imaging. Penumbra was defined using voxel-based thresholds for cerebral blood flow (CBF) and mean transit time (MTT); core was defined by cerebral blood volume (CBV). Normalized penumbra fraction was calculated as Penumbra volume/(Penumbra volume?+?Core volume) for both CBF and MTT (PenCBF and PenMTT, respectively). Collaterals were assessed on CT angiography (CTA). CTp ASPECTS score was applied visually, lower scores indicating larger lesions. ASPECTS ratios were calculated corresponding to penumbra fractions.Both PenCBF and PenMTT showed decremental trends with increasing time since onset (Kendall's tau-b?=?-0.196, p?=?0.055, and -0.187, p?=?0.068, respectively). The CBF/CBV ASPECTS ratio, which showed a relationship to PenCBF (Kendall's tau-b?=?0.190, p?=?0.070), decreased with increasing time since onset (Kendall's tau-b?=?-0.265, p?=?0.006). Collateral response did not relate to time (Kendall's tau-b?=?-0.039, p?=?0.724).Even within 4.5?h since stroke onset, a decremental relationship between penumbra and time, but not between collateral status and time, may be detected using perfusion CT imaging. The trends that we demonstrate merit evaluation in larger datasets to confirm our results, which may have potential wider applications, e.g., in the setting of strokes of unknown onset time.

SUBMITTER: Agarwal S

PROVIDER: S-EPMC4391339 | biostudies-other | 2015

REPOSITORIES: biostudies-other

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Is CT-Based Perfusion and Collateral Imaging Sensitive to Time Since Stroke Onset?

Agarwal Smriti S Matys Tomasz T Marrapu S Tulasi ST Scoffings Daniel J DJ Mitchell Jennifer J Jones P Simon PS Baron Jean-Claude JC Warburton Elizabeth A EA

Frontiers in neurology 20150409

<h4>Purpose</h4>CT-based perfusion and collateral imaging is increasingly used in the assessment of patients with acute stroke. Time of stroke onset is a critical factor in determining eligibility for and benefit from thrombolysis. Animal studies predict that the volume of ischemic penumbra decreases with time. Here, we evaluate if CT is able to detect a relationship between perfusion or collateral status, as assessed by CT, and time since stroke onset.<h4>Materials and methods</h4>We studied 53 ...[more]

PMID: 25914673

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Project description:BackgroundStroke is a major disease with high morbidity and mortality worldwide. Currently, there is no quantitative method to evaluate the short-term prognosis and length of hospitalization of patients.PurposeWe aimed to develop nomograms as prognosis predictors based on imaging characteristics from non-contrast computed tomography (NCCT) and CT perfusion (CTP) and clinical characteristics for predicting activity of daily living (ADL) and hospitalization time of patients with ischemic stroke.Materials and methodsA total of 476 patients were enrolled in the study and divided into the training set (n = 381) and testing set (n = 95). Each of them owned NCCT and CTP images. We propose to extract imaging features representing as the Alberta stroke program early CT score (ASPECTS) values from NCCT, ischemic lesion volumes from CBF, and TMAX maps from CTP. Based on imaging features and clinical characteristics, we addressed two main issues: (1) predicting prognosis according to the Barthel index (BI)-binary logistic regression analysis was employed for feature selection, and the resulting nomogram was assessed in terms of discrimination capability, calibration, and clinical utility and (2) predicting the hospitalization time of patients-the Cox proportional hazard model was used for this purpose. After feature selection, another specific nomogram was established with calibration curves and time-dependent ROC curves for evaluation.ResultsIn the task of predicting binary prognosis outcome, a nomogram was constructed with the area under the curve (AUC) value of 0.883 (95% CI: 0.781-0.985), the accuracy of 0.853, and F1-scores of 0.909 in the testing set. We further tried to predict discharge BI into four classes. Similar performance was achieved as an AUC of 0.890 in the testing set. In the task of predicting hospitalization time, the Cox proportional hazard model was used. The concordance index of the model was 0.700 (SE = 0.019), and AUCs for predicting discharge at a specific week were higher than 0.80, which demonstrated the superior performance of the model.ConclusionThe novel non-invasive NCCT- and CTP-based nomograms could predict short-term ADL and hospitalization time of patients with ischemic stroke, thus allowing a personalized clinical outcome prediction and showing great potential in improving clinical efficiency.SummaryCombining NCCT- and CTP-based nomograms could accurately predict short-term outcomes of patients with ischemic stroke, including whose discharge BI and the length of hospital stay.Key resultsUsing a large dataset of 1,310 patients, we show a novel nomogram with a good performance in predicting discharge BI class of patients (AUCs > 0.850). The second nomogram owns an excellent ability to predict the length of hospital stay (AUCs > 0.800).

Dataset Information

Is CT-Based Perfusion and Collateral Imaging Sensitive to Time Since Stroke Onset?

Publications

Is CT-Based Perfusion and Collateral Imaging Sensitive to Time Since Stroke Onset?

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