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Multiparametric MRI and CT models of infarct core and favorable penumbral imaging patterns in acute ischemic stroke.

ABSTRACT: Objective imaging methods to identify optimal candidates for late recanalization therapies are needed. The study goals were (1) to develop magnetic resonance imaging (MRI) and computed tomography (CT) multiparametric, voxel-based predictive models of infarct core and penumbra in acute ischemic stroke patients, and (2) to develop patient-level imaging criteria for favorable penumbral pattern based on good clinical outcome in response to successful recanalization.An analysis of imaging and clinical data was performed on 2 cohorts of patients (one screened with CT, the other with MRI) who underwent successful treatment for large vessel, anterior circulation stroke. Subjects were divided 2:1 into derivation and validation cohorts. Pretreatment imaging parameters independently predicting final tissue infarct and final clinical outcome were identified.The MRI and CT models were developed and validated from 34 and 32 patients, using 943 320 and 1 236 917 voxels, respectively. The derivation MRI and 2-branch CT models had an overall accuracy of 74% and 80%, respectively, and were independently validated with an accuracy of 71% and 79%, respectively. The imaging criteria of (1) predicted infarct core ?90 mL and (2) ratio of predicted infarct tissue within the at-risk region ?70% identified patients as having a favorable penumbral pattern with 78% to 100% accuracy.Multiparametric voxel-based MRI and CT models were developed to predict the extent of infarct core and overall penumbral pattern status in patients with acute ischemic stroke who may be candidates for late recanalization therapies. These models provide an alternative approach to mismatch in predicting ultimate tissue fate.

SUBMITTER: Kidwell CS

PROVIDER: S-EPMC3558033 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Multiparametric MRI and CT models of infarct core and favorable penumbral imaging patterns in acute ischemic stroke.

Kidwell Chelsea S CS Wintermark Max M De Silva Deidre A DA Schaewe Timothy J TJ Jahan Reza R Starkman Sidney S Jovin Tudor T Hom Jason J Jumaa Mouhammad M Schreier Jeffrie J Gornbein Jeffrey J Liebeskind David S DS Alger Jeffry R JR Saver Jeffrey L JL

Stroke 20121211 1

<h4>Background and purpose</h4>Objective imaging methods to identify optimal candidates for late recanalization therapies are needed. The study goals were (1) to develop magnetic resonance imaging (MRI) and computed tomography (CT) multiparametric, voxel-based predictive models of infarct core and penumbra in acute ischemic stroke patients, and (2) to develop patient-level imaging criteria for favorable penumbral pattern based on good clinical outcome in response to successful recanalization.<h4 ...[more]

PMID: 23233383

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Project description:In stroke care, the extent of irreversible brain injury, termed infarct core, plays a key role in determining eligibility for acute treatments, such as intravenous thrombolysis and endovascular reperfusion therapies. Many of the pivotal randomized clinical trials testing those therapies used MRI Diffusion-Weighted Imaging (DWI) or CT Perfusion (CTP) to define infarct core. Unfortunately, these modalities are not available 24/7 outside of large stroke centers. As such, there is a need for accurate infarct core determination using faster and more widely available imaging modalities including Non-Contrast CT (NCCT) and CT Angiography (CTA). Prior studies have suggested that CTA provides improved predictions of infarct core relative to NCCT; however, this assertion has never been numerically quantified by automatic medical image computing pipelines using acquisition protocols not confounded by different scanner manufacturers, or other protocol settings such as exposure times, kilovoltage peak, or imprecision due to contrast bolus delays. In addition, single-phase CTA protocols are at present designed to optimize contrast opacification in the arterial phase. This approach works well to maximize the sensitivity to detect vessel occlusions, however, it may not be the ideal timing to enhance the ischemic infarct core signal (ICS). In this work, we propose an image analysis pipeline on CT-based images of 88 acute ischemic stroke (AIS) patients drawn from a single dynamic acquisition protocol acquired at the acute ischemic phase. We use the first scan at the time of the dynamic acquisition as a proxy for NCCT, and the rest of the scans as a proxy for CTA scans, with bolus imaged at different brain enhancement phases. Thus, we use the terms "NCCT" and "CTA" to refer to them. This pipeline enables us to answer the questions "Does the injection of bolus enhance the infarct core signal?" and "What is the ideal bolus timing to enhance the infarct core signal?" without being influenced by aforementioned factors such as scanner model, acquisition settings, contrast bolus delay, and human reader errors. We use reference MRI DWI images acquired after successful recanalization acting as our gold standard for infarct core. The ICS is quantified by calculating the difference in intensity distribution between the infarct core region and its symmetrical healthy counterpart on the contralateral hemisphere of the brain using a metric derived from information theory, the Kullback-Leibler divergence (KL divergence). We compare the ICS provided by NCCT and CTA and retrieve the optimal timing of CTA bolus to maximize the ICS. In our experiments, we numerically confirm that CTAs provide greater ICS compared to NCCT. Then, we find that, on average, the ideal CTA acquisition time to maximize the ICS is not the current target of standard CTA protocols, i.e., during the peak of arterial enhancement, but a few seconds afterward (median of 3 s; 95% CI [1.5, 3.0]). While there are other studies comparing the prediction potential of ischemic infarct core from NCCT and CTA images, to the best of our knowledge, this analysis is the first to perform a quantitative comparison of the ICS among CT based scans, with and without bolus injection, acquired using the same scanning sequence and a precise characterization of the bolus uptake, hence, reducing potential confounding factors.

Project description:PurposeTo test whether the relationship between acute ischemic infarct size on concurrent computed tomographic (CT) angiography source images and diffusion-weighted (DW) magnetic resonance images is dependent on the parameters of CT angiography acquisition protocols.Materials and methodsThis retrospective study had institutional review board approval, and all records were HIPAA compliant. Data in 100 patients with anterior-circulation acute ischemic stroke and large vessel occlusion who underwent concurrent CT angiography and DW imaging within 9 hours of symptom onset were analyzed. Measured areas of hyperintensity at acute DW imaging were used as the standard of reference for infarct size. Information regarding lesion volumes and CT angiography protocol parameters was collected for each patient. For analysis, patients were divided into two groups on the basis of CT angiography protocol differences (patients in group 1 were imaged with the older, slower protocol). Intermethod agreement for infarct size was evaluated by using the Wilcoxon signed rank test, as well as by using Spearman correlation and Bland-Altman analysis. Multivariate analysis was performed to identify predictors of marked (?20%) overestimation of infarct size on CT angiography source images.ResultsIn group 1 (n=35), median hypoattenuation volumes on CT angiography source images were slightly underestimated compared with DW imaging hyperintensity volumes (33.0 vs 41.6 mL, P=.01; ratio=0.83), with high correlation (?=0.91). In group 2 (n=65), median volume on CT angiography source images was much larger than that on DW images (94.8 vs 17.8 mL, P<.0001; ratio=3.5), with poor correlation (?=0.49). This overestimation on CT angiography source images would have inappropriately excluded from reperfusion therapy 44.4% or 90.3% of patients eligible according to DW imaging criteria on the basis of a 100-mL absolute threshold or a 20% or greater mismatch threshold, respectively. Atrial fibrillation and shorter time from contrast material injection to image acquisition were independent predictors of marked (?20%) infarct size overestimation on CT angiography source images.ConclusionCT angiography protocol changes designed to speed imaging and optimize arterial opacification are associated with significant overestimation of infarct size on CT angiography source images.

Project description:ObjectiveTo develop and validate a model based on the radiomics features of the infarct areas on non-contrast-enhanced CT to predict hemorrhagic transformation (HT) in acute ischemic stroke.Materials and methodsA total of 118 patients diagnosed with acute ischemic stroke in two centers from January 2019 to February 2022 were included. The radiomics features of infarcted areas on non-contrast-enhanced CT were extracted using 3D-Slicer. A univariate analysis and the least absolute shrinkage and selection operator (LASSO) were used to select features, and the radiomics score (Rad-score) was then constructed. The predictive model of HT was constructed by analyzing the Rad-score and clinical and imaging features in the training cohort, and it was verified in the validation cohort. The model was evaluated with the receiver operating characteristic curve, calibration curve and decision curve, and the prediction performance of the model in different scenarios was further discussed hierarchically.ResultsOf the 118 patients, 52 developed HT, including 21 cases of hemorrhagic infarct (HI) and 31 cases of parenchymal hematoma (PH). The Rad-score was constructed from five radiomics features and was the only independent predictor for HT. The predictive model was constructed from the Rad-score. The area under the curve (AUCs) of the model for predicting HT in the training and validation cohorts were 0.845 and 0.750, respectively. Calibration curve and decision curve analyses showed that the model performed well. Further analysis found that the model predicted HT for different infarct sizes or treatment methods in the training and validation cohorts with 78.3 and 71.4% accuracy, respectively. For all samples, the model predicted an AUC of 0.754 for HT in patients within 4.5 h since stroke onset, and predicted an AUC of 0.648 for PH.ConclusionThis model, which was based on CT radiomics features, could help to predict HT in the setting of acute ischemic stroke for any infarct size and provide guiding suggestions for clinical treatment and prognosis evaluation.

Dataset Information

Multiparametric MRI and CT models of infarct core and favorable penumbral imaging patterns in acute ischemic stroke.

Publications

Multiparametric MRI and CT models of infarct core and favorable penumbral imaging patterns in acute ischemic stroke.

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