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Spatiotemporal dynamic simulation of acute perfusion/diffusion ischemic stroke lesions evolution: a pilot study derived from longitudinal MR patient data.

ABSTRACT: The spatiotemporal evolution of stroke lesions, from acute injury to final tissue damage, is complex. Diffusion-weighted (DWI) and perfusion-weighted (PWI) imaging is commonly used to detect early ischemic changes and attempts to distinguish between permanently damaged and salvageable tissues. To date, 2D and 3D measures of diffusion/perfusion regions at individual timepoints have been widely used but may underestimate the true lesion spatio-temporal dynamics. Currently there is no spatio-temporal 4D dynamic model that simulates the continuous evolution of ischemic stroke from MR images. We determined whether a 4D current-based diffeomorphic model, developed in the field of statistical modeling for measuring the variability of anatomical surfaces, could estimate patient-specific spatio-temporal continuous evolution for MR PWI (measured as mean transit time, (MTT)) and DWI lesions. In our representative pilot sample, the model fitted the data well. Our dynamic analysis of lesion evolution showed different patterns; for example, some DWI/PWI dynamic changes corresponded with DWI lesion expansion into PWI lesions, but other patterns were much more complex and diverse. There was wide variation in the time when the final tissue damage was reached after stroke for DWI and MTT.

SUBMITTER: Rekik I

PROVIDER: S-EPMC3703431 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Spatiotemporal dynamic simulation of acute perfusion/diffusion ischemic stroke lesions evolution: a pilot study derived from longitudinal MR patient data.

Rekik Islem I Allassonnière Stéphanie S Durrleman Stanley S Carpenter Trevor T Wardlaw Joanna J

Computational and mathematical methods in medicine 20130618

The spatiotemporal evolution of stroke lesions, from acute injury to final tissue damage, is complex. Diffusion-weighted (DWI) and perfusion-weighted (PWI) imaging is commonly used to detect early ischemic changes and attempts to distinguish between permanently damaged and salvageable tissues. To date, 2D and 3D measures of diffusion/perfusion regions at individual timepoints have been widely used but may underestimate the true lesion spatio-temporal dynamics. Currently there is no spatio-tempor ...[more]

PMID: 23853669

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Project description:ObjectivesCerebral blood flow (CBF) measurements after endovascular therapy (EVT) for acute ischemic stroke are important to distinguish early secondary injury related to persisting ischemia from that related to reperfusion when considering clinical response and infarct growth.MethodsWe compare reperfusion quantified by the modified Thrombolysis in Cerebral Infarction Score (mTICI) with perfusion measured by MRI dynamic contrast-enhanced perfusion within 5 h of EVT anterior circulation stroke. MR perfusion (rCBF, rCBV, rTmax, rT0) and mTICI scores were included in a predictive model for change in NIHSS at 24 h and diffusion-weighted imaging (DWI) lesion growth (acute to 24 h MRI) using a machine learning RRELIEFF feature selection coupled with a support vector regression.ResultsFor all perfusion parameters, mean values within the acute infarct for the TICI-2b group (considered clinically good reperfusion) were not significantly different from those in the mTICI <2b (clinically poor reperfusion). However, there was a statistically significant difference in perfusion values within the acute infarct region of interest between the mTICI-3 group versus both mTICI-2b and <2b (p = 0.02). The features that made up the best predictive model for change in NIHSS and absolute DWI lesion volume change was rT0 within acute infarct ROI and admission CTA collaterals respectively. No other variables, including mTICI scores, were selected for these best models. The correlation coefficients (Root mean squared error) for the cross-validation were 0.47 (13.7) and 0.51 (5.7) for change in NIHSS and absolute DWI lesion volume change.ConclusionMR perfusion following EVT provides accurate physiological approach to understanding the relationship of CBF, clinical outcome, and DWI growth.Advances in knowledgeMR perfusion CBF acquired is a robust, objective reperfusion measurement providing following recanalization of the target occlusion which is critical to distinguish potential therapeutic harm from the failed technical success of EVT as well as improve the responsiveness of clinical trial outcomes to disease modification.

Project description:Although advanced magnetic resonance imaging (MRI) techniques provide useful information for the differential diagnosis of intra-axial mass-like lesions, the specific diagnostic role of multimodal MRI over conventional magnetic resonance imaging (CMRI) alone in the differential diagnosis of mass-like lesions from a large heterogeneous cohort has not been studied. In this study, we aimed to determine the added value of a joint approach of diffusion-weighted imaging (DWI) and dynamic-susceptibility-contrast perfusion imaging (DSC-PWI) for diagnosis of intra-axial mass-like lesions, comparing them with CMRI alone. Furthermore, we performed these evaluations in a manner simulating clinical practice. Our institutional review board approved this retrospective study and waived the requirement for informed consent. A total of 1038 patients with intra-axial mass-like lesions were retrospectively recruited according to their histological and clinico-radiological diagnoses made between January 2005 and December 2014. All patients underwent CMRI, DWI and DSC-PWI. The diagnostic accuracy and confidence in diagnosing each type of intra-axial mass-like lesions, and for differentiating the intra-axial brain tumors from non-neoplastic lesions, were compared according to the MRI protocols. The disease-specific sensitivity of joint approach differed according to specific disease entities in diagnosing each disease category. Joint approach provided the best diagnostic accuracy for discriminating intra-axial brain tumors from non-neoplastic lesions, with high diagnostic accuracy (95.3-96.7%), specificity (82-84.0%), positive-predictive-value (97.0-97.3%), and negative-predictive-value (84.8-92.7%), with the reader's confidence values being significantly improved over those on CMRI alone (all p-values < 0.001). In conclusion, joint approach of DWI, DSC-PWI to CMRI helps to differentiate non-neoplastic lesions from intra-axial brain tumors, and improves diagnostic confidence compared with CMRI alone. The benefit from the combined imaging differs for each disease category; thus joint approach needs to be customized according to clinical suspicion.

Project description:ObjectiveTransient ischemic attacks (TIA) predict future stroke. However, there are no sensitive and specific diagnostic criteria for TIA and interobserver agreement regarding the diagnosis is poor. Diffusion-weighted MRI (DWI) demonstrates acute ischemic lesions in approximately 30% of TIA patients; the yield of perfusion-weighted MRI (PWI) is unclear.MethodsWe prospectively performed both DWI and PWI within 48 hours of symptom onset in consecutive patients admitted with suspected hemispheric TIAs of <24 hours symptom duration. Two independent raters, blinded to clinical features, assessed the presence and location of acute DWI and PWI lesions. Lesions were correlated with suspected clinical localization and baseline characteristics. Clinical features predictive of a PWI lesion were assessed.ResultsForty-three patients met the inclusion criteria. Thirty-three percent had a PWI lesion and 35% had a DWI lesion. Seven patients (16%) had both PWI and DWI lesions and 7 (16%) had only PWI lesions. The combined yield for identification of either a PWI or a DWI was 51%. DWI lesions occurred in the clinically suspected hemisphere in 93% of patients; PWI lesions in 86%. PWI lesions occurred more frequently when the MRI was performed within 12 hours of symptom resolution, in patients with symptoms of speech impairment, and among individuals younger than 60 years.ConclusionsThe combination of early diffusion-weighted MRI and perfusion-weighted MRI can document the presence of a cerebral ischemic lesion in approximately half of all patients who present with a suspected hemispheric transient ischemic attack (TIA). MRI has the potential to improve the accuracy of TIA diagnosis. ACA = anterior cerebral artery; CI = confidence interval; DWI = diffusion-weighted MRI; ICA = internal carotid artery; MCA = middle cerebral artery; MRA = magnetic resonance angiography; MTT = mean transit time; OR = odds ratios; PCA = posterior cerebral artery; PWI = perfusion-weighted MRI; RR = risk ratios; TIA = transient ischemic attacks; TOAST = Trial of Org 10172 in Acute Stroke Treatment.

Project description:Magnetic resonance (MR) imaging (MRI) is commonly used to diagnose, assess and monitor stroke. Accurate and timely segmentation of stroke lesions provides the anatomico-structural information that can aid physicians in predicting prognosis, as well as in decision making and triaging for various rehabilitation strategies. To segment stroke lesions, MR protocols, including diffusion-weighted imaging (DWI) and T2-weighted fluid attenuated inversion recovery (FLAIR) are often utilized. These imaging sequences are usually acquired with different spatial resolutions due to time constraints. Within the same image, voxels may be anisotropic, with reduced resolution along slice direction for diffusion scans in particular. In this study, we evaluate the ability of 2D and 3D U-Net Convolutional Neural Network (CNN) architectures to segment ischemic stroke lesions using single contrast (DWI) and dual contrast images (T2w FLAIR and DWI). The predicted segmentations correlate with post-stroke motor outcome measured by the National Institutes of Health Stroke Scale (NIHSS) and Fugl-Meyer Upper Extremity (FM-UE) index based on the lesion loads overlapping the corticospinal tracts (CST), which is a neural substrate for motor movement and function. Although the four methods performed similarly, the 2D multimodal U-Net achieved the best results with a mean Dice of 0.737 (95% CI: 0.705, 0.769) and a relatively high correlation between the weighted lesion load and the NIHSS scores (both at baseline and at 90 days). A monotonically constrained quintic polynomial regression yielded R2 = 0.784 and 0.875 for weighted lesion load versus baseline and 90-Days NIHSS respectively, and better corrected Akaike information criterion (AICc) scores than those of the linear regression. In addition, using the quintic polynomial regression model to regress the weighted lesion load to the 90-Days FM-UE score results in an R2 of 0.570 with a better AICc score than that of the linear regression. Our results suggest that the multi-contrast information enhanced the accuracy of the segmentation and the prediction accuracy for upper extremity motor outcomes. Expanding the training dataset to include different types of stroke lesions and more data points will help add a temporal longitudinal aspect and increase the accuracy. Furthermore, adding patient-specific data may improve the inference about the relationship between imaging metrics and functional outcomes.

Dataset Information

Spatiotemporal dynamic simulation of acute perfusion/diffusion ischemic stroke lesions evolution: a pilot study derived from longitudinal MR patient data.

Publications

Spatiotemporal dynamic simulation of acute perfusion/diffusion ischemic stroke lesions evolution: a pilot study derived from longitudinal MR patient data.

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