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Purpose Admission infarct core lesion size is an important determinant of management and outcome in acute (<9 hrs) stroke. Our purpose was to: (1) determine the optimal CT perfusion (CTP) parameter to define infarct core using various post-processing platforms, and (2) establish the degree of variability in threshold values between these different platforms. Methods We evaluated 48 consecutive cases with vessel occlusion and admission CTP and DWI within 3 hours of each other. CTP was acquired with a “second-generation” 66-second biphasic cine protocol, and post-processed using “standard” (from two vendors, “A-std” and “B-std”) and “delay-corrected” (from one vendor, “A-dc”) commercial software. ROC curve analysis was performed comparing each CTP parameter - both absolute and normalized to the contralateral uninvolved hemisphere - between infarcted and non-infarcted regions, as defined by co-registered DWI. Results Cerebral blood flow (CBF) had the highest accuracy (ROC “area under curve”, AUC), for all three platforms (p<0.01). The maximal AUC's for each parameter were: absolute CBF 0.88, CBV 0.81, and MTT 0.82, and relative CBF 0.88, CBV 0.83, and MTT 0.82. Optimal ROC operating point thresholds varied significantly between different platforms (Friedman test, p<0.01). Conclusion Admission absolute and normalized “second-generation” cine acquired CT-CBF lesion volumes correlate more closely with DWI defined infarct core than do those of CT-CBV or MTT. Although limited availability of DWI for some patients creates impetus to develop alternative methods of estimating core, the marked variability in quantification amongst different post-processing software limits generalizability of parameter map thresholds between platforms.

Background and Purpose-The purpose of this study was to determine whether acute diffusion-weighted imaging (DWI) and mean transit time (MTT) lesion volumes and presenting National Institutes of Health Stroke Scale (NIHSS) can identify patients with acute ischemic stroke who will have a high probability of good and poor outcomes. Methods-Fifty-four patients with acute ischemic stroke who had MRI within 9 hours of symptom onset and 3-month follow-up with modified Rankin scale were evaluated. Acute DWI and MTT lesion volumes and baseline NIHSS scores were calculated. Clinical outcomes were considered good if the modified Rankin Scale was 0 to 2. Results-The 33 of 54 (61%) patients with good outcomes had significantly smaller DWI lesion volumes (Pϭ0.0001), smaller MTT lesion volumes (PϽ0.0001), and lower NIHSS scores (PϽ0.0001) compared with those with poor outcomes. Receiver operating characteristic curves for DWI, MTT, and NIHSS relative to poor outcome had areas under the curve of 0.889, 0.854, and 0.930, respectively, which were not significantly different. DWI and MTT lesion volumes predicted outcome better than mismatch volume or percentage mismatch. All patients with a DWI volume Ͼ72 mL (13 of 54) and an NIHSS score Ͼ20 (6 of 54) had poor outcomes. All patients with an MTT volume of Ͻ47 mL (16 of 54) and an NIHSS score Ͻ8 (17 of 54) had good outcomes. Combining clinical and imaging thresholds improved prognostic yield (70%) over clinical (43%) or imaging (54%) thresholds alone (Pϭ0.01). Conclusions-Combining quantitative DWI and MTT with NIHSS predicts good and poor outcomes with high probability and is superior to NIHSS alone. (Stroke. 2010;41:1728-1735.)

BACKGROUND AND PURPOSE:To safeguard patient health, there is great interest in CT radiation-dose reduction. The purpose of this study was to evaluate the impact of an iterative-reconstruction algorithm, ASIR, on image-quality measures in reduced-dose head CT scans for adult patients.

Persistence of mismatch after 9 hours is common and occurs most often in patients with PAO.

BACKGROUND AND PURPOSE Various CTP parameters have been used to identify ischemic penumbra. The purpose of this study was to determine the optimal CTP parameter and threshold to distinguish true “at-risk” penumbra from benign oligemia in acute stroke patients without reperfusion. MATERIALS AND METHODS Consecutive stroke patients were screened and 23 met the following criteria: 1) admission scanning within 9 hours of onset, 2) CTA confirmation of large vessel occlusion, 3) no late clinical or radiographic evidence of reperfusion, 4) no thrombolytic therapy, 5) DWI imaging within 3 hours of CTP, and 6) either CT or MR follow-up imaging. CTP was postprocessed with commercial software packages, using standard and delay-corrected deconvolution algorithms. Relative cerebral blood flow, volume, and mean transit time (rCBF, rCBV and rMTT) values were obtained by normalization to the uninvolved hemisphere. The admission DWI and final infarct were transposed onto the CTP maps and receiver operating characteristic curve analysis was performed to determine optimal thresholds for each perfusion parameter in defining penumbra destined to infarct. RESULTS Relative and absolute MTT identified penumbra destined to infarct more accurately than CBF or CBV*CBF (P < .01). Absolute and relative MTT thresholds for defining penumbra were 12s and 249% for the standard and 13.5s and 150% for the delay-corrected algorithms, respectively. CONCLUSIONS Appropriately thresholded absolute and relative MTT-CTP maps optimally distinguish “at-risk” penumbra from benign oligemia in acute stroke patients with large-vessel occlusion and no reperfusion. The precise threshold values may vary, however, depending on the postprocessing technique used for CTP map construction.

Background and Purpose-Our purpose was to determine (1) the correlation between quantitative CT and MR measurements of infarct core, penumbra, and mismatch; and (2) whether the difference between these measurements would alter patient selection for stroke clinical trials. Methods-We studied 45 patients with acute middle cerebral artery stroke imaged a mean of 3.

Purpose To construct a multivariate model for prediction of early aphasia improvement in stroke patients using admission CT perfusion (CTP) and CT angiography (CTA). Methods Fifty-eight consecutive patients with aphasia due to first-time ischemic stroke of the left hemisphere were included. Language function was assessed based on patients’ admission and discharge NIHSS and clinical records. All patients had brain CTP and CTA within 9 hours of symptom onset. For image analysis, all CTPs were automatically coregistered to MNI-152 brain space and parcellated into mirrored cortical and subcortical regions. Multiple logistic regression analysis was used to find independent imaging and clinical predictors of language recovery. Results By the time of discharge, 21 (36%) patients demonstrated improvement of language. Independent factors predicting improvement in language included relative cerebral blood flow of angular gyrus gray matter (Brodmann’s area 39) and lower third of insular ribbon, proximal cerebral artery occlusion on admission CTA, and aphasia score on admission NIHSS exam. Using these 4 variables, we developed a multivariate logistic regression model that could estimate the probability of early improvement in stroke patients presenting with aphasia and predict functional outcome with 91% accuracy. Conclusion An imaging-based location weighted multivariate model is developed to predict early language improvement of aphasic patients using admission data collected within 9-hours of stroke onset. This pilot model should be validated in a larger, prospective study; however, the semi-automated atlas-based analysis of brain CTP, along with the statistical approach, could be generalized for prediction of other outcome measures in stroke patients.