Search

Background: In acute stroke, the magnetic resonance (MR) imaging-based mismatch concept is used to select patients with tissue at risk of infarction for reperfusion therapies. There is however a controversy if non-deconvolved or deconvolved perfusion weighted (PW) parameter maps perform better in tissue at risk prediction and which parameters and thresholds should be used to guide treatment decisions., Methods: In a group of 22 acute stroke patients with consecutive MR and quantitative positron emission tomography (PET) imaging, non-deconvolved parameters were validated with the gold standard for penumbral-flow (PF) detection 15O-water PET. Performance of PW parameters was assessed by a receiver operating characteristic curve analysis to identify the accuracy of each PWI map to detect the -upper PF threshold as defined by PET cerebral blood flow <20 mL/100 g/min., Results: Among normalized non-deconvolved parameters, PW-first moment without delay correction (FM without DC) > 3.6 s (area under the curve [AUC] = 0.89, interquartile range [IQR] 0.85-0.94), PW-maximum of the concentration curve (Cmax) < 0.66 (AUC = 0.92, IQR 0.84-0.96) and PW-time to peak (TTP) > 4.0 s (AUC = 0.92, IQR 0.87-0.94) perform significantly better than other non-deconvolved parameters to detect the PF threshold as defined by PET., Conclusions: Non-deconvolved parameters FM without DC, Cmax and TTP are an observer-independent alternative to established deconvolved parameters (e.g., Tmax) to guide treatment decisions in acute stroke., (© 2018 S. Karger AG, Basel.)

Background and Purpose: Identification of salvageable penumbra tissue by dynamic susceptibility contrast magnetic resonance imaging is a valuable tool for acute stroke patient stratification for treatment. However, prior studies have not attempted to combine the different perfusion maps into a predictive model. In this study, we established a multiparametric perfusion imaging model and cross-validated it using positron emission tomography perfusion for detection of penumbral flow., Methods: In a retrospective analysis of 17 subacute stroke patients with consecutive magnetic resonance imaging and H2O15 positron emission tomography scans, perfusion maps of cerebral blood flow, cerebral blood volume, mean transit time, time-to-maximum, and time-to-peak were constructed and combined using a generalized linear model (GLM). Both the GLM maps and the single perfusion maps alone were cross-validated with positron emission tomography-cerebral blood flow scans to predict penumbral flow on a voxel-wise level. Performance was tested by receiver-operating characteristics curve analysis, that is, the area under the curve, and the models' fits were compared using the likelihood ratio test., Results: The GLM demonstrated significantly improved model fit compared with each of the single perfusion maps ( P <1×e-5) and demonstrated higher performance, with an area under the curve of 0.91. However, the absolute difference between the performance of GLM and the best-performing single perfusion parameter (time-to-maximum) was relatively low (area under the curve difference =0.04)., Conclusions: Our results support a dynamic susceptibility contrast magnetic resonance imaging-based GLM as an improved model for penumbral flow prediction in stroke patients. With given perfusion maps, this model is a straightforward and observer-independent alternative for therapy stratification., (© 2017 American Heart Association, Inc.)

Background and Purpose: In acute stroke, the DWI-FLAIR mismatch allows for the allocation of patients to the thrombolysis window (<4.5 hours). FLAIR-lesions, however, may be challenging to assess. In comparison, DWI may be a useful bio-marker owing to high lesion contrast. We investigated the performance of a relative DWI signal intensity (rSI) threshold to predict the presence of FLAIR-lesions in acute stroke and analyzed its association with time-from-stroke-onset., Methods: In a retrospective, dual-center MR-imaging study we included patients with acute stroke and time-from-stroke-onset ≤12 hours (group A: n = 49, 1.5T; group B: n = 48, 3T). DW- and FLAIR-images were coregistered. The largest lesion extent in DWI defined the slice for further analysis. FLAIR-lesions were identified by 3 raters, delineated as regions-of-interest (ROIs) and copied on the DW-images. Circular ROIs were placed within the DWI-lesion and labeled according to the FLAIR-pattern (FLAIR+ or FLAIR-). ROI-values were normalized to the unaffected hemisphere. Adjusted and nonadjusted receiver-operating-characteristics (ROC) curve analysis on patient level was performed to analyze the ability of a DWI- and ADC-rSI threshold to predict the presence of FLAIR-lesions. Spearman correlation and adjusted linear regression analysis was performed to assess the relationship between DWI-intensity and time-from-stroke-onset., Results: DWI-rSI performed well in predicting lesions in FLAIR-imaging (mean area under the curve (AUC): group A: 0.84; group B: 0.85). An optimal mean DWI-rSI threshold was identified (A: 162%; B: 161%). ADC-maps performed worse (mean AUC: A: 0.58; B: 0.77). Adjusted regression models confirmed the superior performance of DWI-rSI. Correlation coefficents and linear regression showed a good association with time-from-stroke-onset for DWI-rSI, but not for ADC-rSI., Conclusion: An easily assessable DWI-rSI threshold identifies the presence of lesions in FLAIR-imaging with good accuracy and is associated with time-from-stroke-onset in acute stroke. This finding underlines the potential of a DWI-rSI threshold as a marker of lesion age.

Background and Purpose: Perfusion-weighted (PW) MRI is increasingly used to identify the tissue at risk. The adequate PW-MRI map and threshold remain controversial due to a considerable individual variation of values. By comparative positron emission tomography, we evaluated a simple MR-based and positron emission tomography-validated calibration of PW maps., Methods: PW-MRI and quantitative positron emission tomography (15O-water) of patients with acute stroke were used to calculate averaged as well as individual thresholds of penumbral flow (positron emission tomography cerebral blood flow (<20 mL/100 g/min) for maps of time to peak, mean transit time, cerebral blood flow, and cerebral blood volume. A linear regression analysis studied the variability of the individual thresholds using 3 different PW reference regions (hemispheric, white matter, gray matter). The best model was used for volumetric analysis to compare averaged and scaled individual thresholds and to calculate look-up tables for PW maps., Results: In 26 patients, the averaged thresholds were (median/interquartile range): cerebral blood flow 21.7 mL/100 g/min (19.9 to 32); cerebral blood volume 1.5 mL/100 g (0.9 to 1.8); mean transit time seconds 5.2 (3.9 to 6.9); and relative time to peak 4.2 seconds (2.8 to 5.8). The large individual variability was best explained by the mean value of the hemispheric reference derived from a region of interest on a level with the basal ganglia of the unaffected hemisphere (R(2): cerebral blood flow 0.76, cerebral blood volume 0.55, mean transit time 0.83, time to peak 0.95). Hemispheric reference-corrected thresholds clearly improved the detection of penumbral flow. Look-up tables were calculated to identify the individual thresholds according to the hemispheric reference value., Conclusions: The individual variation of PW values, even if calculated by deconvolution, remains a major obstacle in quantitative PW imaging and can be significantly improved by a simple MR-based calibration. Easily applicable look-up tables identify the individual best threshold for each PW map to optimize mismatch detection.

Background and Purpose: Perfusion-weighted imaging maps are used to identify hypoperfusion in acute ischemic stroke. We evaluated maps of cerebral blood flow (CBF), cerebral blood volume, mean transit time, and time to peak (TTP) in acute stroke by comparison with positron emission tomography., Methods: Perfusion-weighted imaging and positron emission tomography were performed in 26 patients with acute ischemic stroke (median 18.5 hours after stroke onset, 65 minutes between MRI and positron emission tomography). The perfusion-weighted imaging-derived maps of CBF, cerebral blood volume, mean transit time, and TTP delay were compared with quantitative positron emission tomography CBF. A receiver-operating characteristic curve analysis identified the best perfusion-weighted imaging map and threshold to identify hypoperfusion <20 mL/100 g/min, a widely used measure of penumbral flow., Results: Individual regression analysis of positron emission tomography CBF and perfusion-weighted imaging values were strong for CBF and TTP delay and weaker for mean transit time and cerebral blood volume, but the pooled analysis showed a large variance. Receiver-operating characteristic curve analysis identified TTP and CBF maps as most predictive (median area under the curve=0.94 and 0.93). Penumbral flow thresholds were <21.7 mL/100 g/min (CBF), <1.5 mL/100 g (cerebral blood volume), >5.3 seconds (mean transit time), and >4.2 seconds (TTP). TTP and CBF maps reached sensitivity/specificity values of 91%/82% and 89%/87%., Conclusions: In our sample, maps of CBF, TTP, and mean transit time yielded a good estimate of penumbral flow. The performance of TTP maps was equivalent to deconvolution techniques using an arterial input function. For all maps, the application of a predefined threshold is mandatory and calibration studies will enhance their use in acute stroke therapy as well as in clinical stroke trials.

Objective: Accurate identification of the ischemic penumbra, the therapeutic target in acute clinical stroke, is of critical importance to identify patients who might benefit from reperfusion therapies beyond the established time windows. Therefore, we aimed to validate magnetic resonance imaging (MRI) mismatch–based penumbra detection against full quantitative positron emission tomography (15O‐PET), the gold standard for penumbra detection in acute ischemic stroke. Methods: Ten patients (group A) with acute and subacute ischemic stroke underwent perfusion‐weighted (PW)/diffusion‐weighted MRI and consecutive full quantitative 15O‐PET within 48 hours of stroke onset. Penumbra as defined by 15O‐PET cerebral blood flow (CBF), oxygen extraction fraction, and oxygen metabolism was used to validate a wide range of established PW measures (eg, time‐to‐maximum [Tmax]) to optimize penumbral tissue detection. Validation was carried out using a voxel‐based receiver‐operating‐characteristic curve analysis. The same validation based on penumbra as defined by quantitative 15O‐PET CBF was performed for comparative reasons in 23 patients measured within 48 hours of stroke onset (group B). Results: The PW map Tmax (area‐under‐the‐curve = 0.88) performed best in detecting penumbral tissue up to 48 hours after stroke onset. The optimal threshold to discriminate penumbra from oligemia was Tmax >5.6 seconds with a sensitivity and specificity of >80%. Interpretation: The performance of the best PW measure Tmax to detect the upper penumbral flow threshold in ischemic stroke is excellent. Tmax >5.6 seconds–based penumbra detection is reliable to guide treatment decisions up to 48 hours after stroke onset and might help to expand reperfusion treatment beyond the current time windows. ANN NEUROL 2019;85:875–886. [ABSTRACT FROM AUTHOR]

Background: With regard to acute stroke, patients with unknown time from stroke onset are not eligible for thrombolysis. Quantitative diffusion weighted imaging (DWI) and fluid attenuated inversion recovery (FLAIR) MRI relative signal intensity (rSI) biomarkers have been introduced to predict eligibility for thrombolysis, but have shown heterogeneous results in the past. In the present work, we investigated whether the inclusion of easily obtainable clinical-radiological parameters would improve the prediction of the thrombolysis time window by rSIs and compared their performance to the visual DWI-FLAIR mismatch. Methods: In a retrospective study, patients from 2 centers with proven stroke with onset <12 h were included. The DWI lesion was segmented and overlaid on ADC and FLAIR images. rSI mean and SD, were calculated as follows: (mean ROI value/mean value of the unaffected hemisphere). Additionally, the visual DWI-FLAIR mismatch was evaluated. Prediction of the thrombolysis time window was evaluated by the area-under-thecurve (AUC) derived from receiver operating characteristic (ROC) curve analysis. Factors such as the association of age, National Institutes of Health Stroke Scale, MRI field strength, lesion size, vessel occlusion and Wahlund-Score with rSI were investigated and the models were adjusted and stratified accordingly. Results: In 82 patients, the unadjusted rSI measures DWI-mean and -SD showed the highest AUCs (AUC 0.86-0.87). Adjustment for clinical-radiological covariates significantly improved the performance of FLAIR-mean (0.91) and DWI-SD (0.91). The best prediction results based on the AUC were found for the final stratified and adjusted models of DWI-SD (0.94) and FLAIR-mean (0.96) and a multivariable DWI-FLAIR model (0.95). The adjusted visual DWIFLAIR mismatch did not perform in a significantly worse manner (0.89). ADC-rSIs showed fair performance in all models. Conclusions: Quantitative DWI and FLAIR MRI biomarkers as well as the visual DWI-FLAIR mismatch provide excellent prediction of eligibility for thrombolysis in acute stroke, when easily obtainable clinical-radiological parameters are included in the prediction models. [ABSTRACT FROM AUTHOR]