Background It is uncertain if endovascular stroke therapy leads to improved clinical outcomes due to a paucity of data from randomized placebo-controlled trials. The aim of this study was to determine if MRI can be used to identify patients who are most likely to benefit from endovascular reperfusion. Methods Consecutive patients, scheduled to undergo endovascular therapy within 12 hours of stroke onset, were enrolled in a multi-center prospective cohort study. Aided by an automated image analysis software program, investigators interpreted the baseline MRI. They determined, prior to endovascular treatment, if the patient had an MRI profile (Target Mismatch) that suggested salvageable tissue was present. Reperfusion was assessed on an early follow-up MRI and defined as a >50% reduction in the volume of the baseline perfusion lesion. A favorable clinical response was defined as a ≥8 point improvement on the NIH Stroke Scale (NIHSS) between baseline and day 30 or an NIHSS score of 0–1 at 30 days. Findings Following endovascular therapy reperfusion occurred in 46 of 78 (59%) Target Mismatch patients and in 12 of 21 (57%) No Target Mismatch patients. The adjusted odds ratio for favorable clinical response associated with reperfusion was 8·5 (95% CI 2·6 – 28) in the Target Mismatch group and 0·2 (95% CI 0·0 – 1·6) in the No Target Mismatch group (p=0·003 for difference between odds ratios). Reperfusion was associated with an increased odds of good functional outcome at 90 days (OR is 5.2, 95% CI 1.4–19) and attenuation of infarct growth at 5 days (30 ml of median growth with reperfusion vs. 73 ml without reperfusion, p=0·01) in the Target Mismatch group but not in patients without Target Mismatch. Interpretation Target Mismatch patients who achieved early reperfusion following endovascular stroke therapy had more favorable clinical outcomes and less infarct growth. No association between reperfusion and favorable outcomes was present in patients without Target Mismatch. These data support a randomized controlled trial of endovascular treatment in patients with the Target Mismatch profile.

Diffusion-perfusion mismatch can be used to identify acute stroke patients that could benefit from reperfusion therapies. Early assessment of the mismatch facilitates necessary diagnosis and treatment decisions in acute stroke. We developed the RApid processing of PerfusIon and Diffusion (RAPID) for unsupervised, fully automated processing of perfusion and diffusion data for the purpose of expedited routine clinical assessment. The RAPID system computes quantitative perfusion maps (cerebral blood volume, CBV; cerebral blood flow, CBF; mean transit time, MTT; and the time until the residue function reaches its peak, T max ) using deconvolution of tissue and arterial signals. Diffusion-weighted imaging/perfusionweighted imaging (DWI/PWI) mismatch is automatically determined using infarct core segmentation of ADC maps and perfusion deficits segmented from T max maps. The performance of RAPID was evaluated on 63 acute stroke cases, in which diffusion and perfusion lesion volumes were outlined by both a human reader and the RAPID system. The correlation of outlined lesion volumes obtained from both methods was r 2 ¼ 0.99 for DWI and r 2 ¼ 0.96 for PWI. For mismatch identification, RAPID showed 100% sensitivity and 91% specificity. The mismatch information is made available on the hospital's PACS within 5-7 min. Results indicate that the automated system is sufficiently accurate and fast enough to be used for routine care as well as in clinical trials.

Background and Purpose We evaluate associations between the severity of magnetic resonance perfusion-weighted imaging abnormalities, as assessed by the hypoperfusion intensity ratio (HIR), on infarct progression and functional outcome in the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution Study 2 (DEFUSE 2). Methods Diffusion-weighted magnetic resonance imaging and perfusion-weighted imaging lesion volumes were determined with the RAPID software program. HIR was defined as the proportion of TMax >6 s lesion volume with a Tmax >10 s delay and was dichotomized based on its median value (0.4) into low versus high subgroups as well as quartiles. Final infarct volumes were assessed at day 5. Initial infarct growth velocity was calculated as the baseline diffusion-weighted imaging (DWI) lesion volume divided by the delay from symptom onset to baseline magnetic resonance imaging. Total Infarct growth was determined by the difference between final infarct and baseline DWI volumes. Collateral flow was assessed on conventional angiography and dichotomized into good and poor flow. Good functional outcome was defined as modified Rankin Scale ≤2 at 90 days. Results Ninety-nine patients were included; baseline DWI, perfusion-weighted imaging, and final infarct volumes increased with HIR quartiles (P<0.01). A high HIR predicted poor collaterals with an area under the curve of 0.73. Initial infarct growth velocity and total infarct growth were greater among patients with a high HIR (P<0.001). After adjustment for age, DWI volume, and reperfusion, a low HIR was associated with good functional outcome: odds ratio=4.4 (95% CI, 1.3–14.3); P=0.014. Conclusions HIR can be easily assessed on automatically processed perfusion maps and predicts the rate of collateral flow, infarct growth, and clinical outcome.

Diffusion-weighted imaging (DWI) is commonly used to assess irreversibly infarcted tissue but its accuracy is challenged by reports of diffusion lesion reversal (DLR). We investigated the frequency and implications for mismatch classification of DLR using imaging from the EPITHET (Echoplanar Imaging Thrombolytic Evaluation Trial) and DEFUSE (Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution) studies. In 119 patients (83 treated with IV tissue plasminogen activator), follow-up images were coregistered to acute diffusion images and the lesions manually outlined to their maximal visual extent in diffusion space. Diffusion lesion reversal was defined as voxels of acute diffusion lesion that corresponded to normal brain at follow-up (i.e., final infarct, leukoaraiosis, and cerebrospinal fluid (CSF) voxels were excluded from consideration). The appearance of DLR was visually checked for artifacts, the volume calculated, and the impact of adjusting baseline diffusion lesion volume for DLR volume on perfusion-diffusion mismatch analyzed. Median DLR volume reduced from 4.4 to 1.5 mL after excluding CSF/leukoaraiosis. Visual inspection verified 8/119 (6.7%) with true DLR, median volume 2.33 mL. Subtracting DLR from acute diffusion volume altered perfusion-diffusion mismatch (T max > 6 seconds, ratio > 1.2) in 3/119 (2.5%) patients. Diffusion lesion reversal between baseline and 3 to 6 hours DWI was also uncommon (7/65, 11%) and often transient. Clinically relevant DLR is uncommon and rarely alters perfusion-diffusion mismatch. The acute diffusion lesion is generally a reliable signature of the infarct core.

Differences in research methodology have hampered the optimization of Computer Tomography Perfusion (CTP) for identification of the ischemic core. We aim to optimize CTP core identification using a novel benchmarking tool. The benchmarking tool consists of an imaging library and a statistical analysis algorithm to evaluate the performance of CTP. The tool was used to optimize and evaluate an in-house developed CTP-software algorithm. Imaging data of 103 acute stroke patients were included in the benchmarking tool. Median time from stroke onset to CT was 185 min (IQR 180-238), and the median time between completion of CT and start of MRI was 36 min (IQR 25-79). Volumetric accuracy of the CTP-ROIs was optimal at an rCBF threshold of <38%; at this threshold, the mean difference was 0.3 ml (SD 19.8 ml), the mean absolute difference was 14.3 (SD 13.7) ml, and CTP was 67% sensitive and 87% specific for identification of DWI positive tissue voxels. The benchmarking tool can play an important role in optimizing CTP software as it provides investigators with a novel method to directly compare the performance of alternative CTP software packages.

In this study, a spin- and gradient-echo echo-planar imaging (SAGE EPI) MRI pulse sequence is presented that allows simultaneous measurements of gradient-echo and spin-echo dynamic susceptibility-contrast perfusion-weighted imaging (DSC-PWI) data. Following signal excitation, five EPI readout trains were acquired using SAGE EPI, all of them with echo times of less than 100 ms. Contrast agent concentrations in brain tissue were determined based on absolute R2* and R2 estimates rather than relative changes in the signals of individual echo trains, producing T1-independent DSC-PWI data. Moreover, this acquisition technique enabled vessel size imaging through the simultaneous quantification of R2* and R2, without an increase in acquisition time. In this work, the concepts of the SAGE EPI pulse sequence and results in stroke and tumor imaging are presented. Overall, SAGE EPI combined the advantages of higher sensitivity of gradient-echo DSC-PWI acquisitions to the contrast agent passage with the better selectivity of spin-echo DSC-PWI measurements to the microvasculature.

Head motion is a fundamental problem in brain MRI. The problem is further compounded in diffusion tensor imaging because of long acquisition times, and the sensitivity of the tensor computation to even small misregistration. To combat motion artifacts in diffusion tensor imaging, a novel real-time prospective motion correction method was introduced using an in-bore monovision system. The system consists of a camera mounted on the head coil and a self-encoded checkerboard marker that is attached to the patient's forehead. Our experiments showed that optical prospective motion correction is more effective at removing motion artifacts compared to image-based retrospective motion correction. Statistical analysis revealed a significant improvement in similarity between diffusion data acquired at different time points when prospective correction was used compared to retrospective correction (P < 0.001). Magn Reson Med 66:366-378,

Background MRI-based selection of patients for acute stroke interventions requires rapid accurate estimation of the infarct core on diffusion-weighted MRI (DWI). Typically used manual methods to delineate DWI lesions are subjective and time-consuming. These limitations would be overcome by a fully automated method that can rapidly and objectively delineate the ischemic core. An automated method would require pre-defined criteria to identify the ischemic core. Aim To determine Apparent Diffusion Coefficient (ADC) based criteria that can be implemented in a fully automated software solution for identification of the ischemic core. Methods Imaging data from patients enrolled in the DEFUSE study who had early revascularization following tPA treatment, was included. The patients’ baseline DWI and 30-day FLAIR lesions were manually delineated after co-registration. Parts of the DWI lesion that corresponded with 30-day infarct were considered ischemic core, whereas parts that corresponded with normal brain parenchyma at 30 days were considered non-core. The optimal ADC threshold to discriminate core from non-core voxels was determined by voxel-based ROC analysis using the Youden index. Results 51045 DWI positive voxels from 14 patients who met eligibility criteria were analyzed. The mean DWI lesion volume was 24(±23) mL. Of this, 18(±22) mL was ischemic core and 3(±5) mL was non-core. The remainder corresponded to pre-existing gliosis, CSF, or was lost to post-infarct atrophy. The ADC of core was lower than that of non-core voxels (p<0.0001). The optimal threshold for identification of ischemic core was an ADC ≤620 ×10−6 mm2/s (sensitivity 69% and specificity 78%). Conclusions Our data suggests the ischemic core can be identified with an absolute ADC threshold. This threshold can be implemented in image analysis software for fully automated segmentation of the ischemic core.