Fabian Flottmann

Multivariate dynamic prediction of ischemic infarction and tissue salvage as a function of time and degree of recanalization

Benefit of endovascular recanalization beyond established treatment time windows likely exists in select stroke patients. However, there is currently no imaging model that predicts infarction adjusting for elapsed time between the pathologic snapshot of admission imaging until endovascular recanalization. We trained and cross validated a multivariate generalized linear model (GLM) that uses computer tomography perfusion and clinical data to quantify patient-specific dynamic change of tissue infarction depending on degree and time of recanalization. Multicenter data of 161 patients with proximal anterior circulation occlusion undergoing endovascular therapy were included. Multivariate voxelwise infarct probability was calculated within the GLM. The effect of increasing time to treatment and degree of recanalization on voxelwise infarction was calculated in each patient. Tissue benefit of successful relative to unsuccessful recanalization was shown up to 15 hours after onset in individual patients and decreased nonlinearly with time. On average, the relative reduction of infarct volume at the treatment interval of 5 hours was 53% and this salvage effect decreased by 5% units per hour to <5% after 10 additional hours to treatment. Treatment time-adjusted multivariate prediction of infarction by perfusion and clinical status may identify patients who benefit from extended time to recanalization therapy.

CT-perfusion stroke imaging: a threshold free probabilistic approach to predict infarct volume compared to traditional ischemic thresholds

The aim was to evaluate a novel method of threshold-free prediction of brain infarct from computed tomography perfusion (CTP) imaging in comparison to conventional ischemic thresholds. In a multicenter cohort of 161 patients with acute large vessel occlusion who received endovascular therapy, brain infarction was predicted by CTP using (1) optimized parameter cut-off values determined by ROC curve analysis and (2) probabilistic logistic regression threshold-free analysis. Predicted infarct volumes and prediction errors based on four perfusion parameter maps were compared against observed infarcts. In 93 patients with successful recanalization, the mean observed infarct volume was 35.7 ± 61.9 ml (the reference for core infarct not savable by reperfusion). Optimal parameter thresholds predicted mean infarct volumes between 53.2 ± 44.4 and 125.0 ± 95.4 ml whereas threshold-free analysis predicted mean volumes between 35.9 ± 28.5 and 36.1 ± 29.0 ml. In 68 patients with persistent occlusion, the mean observed infarct volume was 113.4 ± 138.3 ml (the reference to define penumbral infarct savable by reperfusion). Predicted mean infarct volumes by parameter thresholds ranged from 91.4 ± 81.5 to 163.8 ± 135.7 ml, by threshold-free analysis from 113.2 ± 89.9 to 113.5 ± 89.0 ml. Threshold-free prediction of infarct volumes had a higher precision and lower patient-specific prediction error than conventional thresholding. Penumbra to core lesion mismatch estimate may therefore benefit from threshold-free CTP analysis.

Age-Related Measurements of the Myelin Water Fraction derived from 3D multi-echo GRASE reflect Myelin Content of the Cerebral White Matter

Myelin Water Fraction (MWF) measurements derived from quantitative Myelin Water Imaging (MWI) may detect demyelinating changes of the cerebral white matter (WM) microstructure. Here, we investigated age-related alterations of the MWF in normal aging brains of healthy volunteers utilizing two fast and clinically feasible 3D gradient and spin echo (GRASE) MWI sequences with 3 mm and 5 mm isotropic voxel size. In 45 healthy subjects (age range: 18–79 years), distinct regions of interest (ROI) were defined in the cerebral WM including corticospinal tracts. For the 3 mm sequence, significant correlations of the mean MWF with age were found for most ROIs (r < −0.8 for WM ROIs; r = −0.55 for splenium of corpus callosum; r = −0.75 for genu of corpus callosum; p < 0.001 for all ROIs). Similar correlations with age were found for the ROIs of the 5 mm sequence. No significant correlations were found for the corticospinal tract and the occipital WM (p > 0.05). Mean MWF values obtained from the 3 mm and 5 mm sequences were strongly comparable. The applied 3D GRASE MWI sequences were found to be sensitive for age-dependent myelin changes of the cerebral WM microstructure. The reported MWF values might be of substantial use as reference for further investigations in patient studies.

‘Drip-and-drive’: shipping the neurointerventionalist to provide mechanical thrombectomy in primary stroke centers

Background To satisfy the increasing demand of mechanical thrombectomy (MT) for acute ischemic stroke treatment, new organizational concepts for patient care are required. This study evaluates time intervals of acute stroke management in two stroke care models, including one based on transportation of the interventionalist from a comprehensive stroke center (CSC) to treat patients in two primary stroke centers (PSC). We hypothesized that time intervals were not inferior for the ‘drip-and-drive’ concept compared with the traditional ‘drip-and-ship’ concept. Methods Patients treated with MT at the PSC (‘drip-and-drive’, ‘D+D group’) were compared with patients transferred from PSC to CSC for MT (‘drip-and-ship’, ‘D+S group’) with regard to time delays. Time intervals assessed were: symptom onset to initial CT, to angiography, and to recanalization; time from initial CT to telephone call activation, to arrival, and to angiography; and time from telephone call activation to arrival and from arrival to angiography. Results 42 patients were treated at the PSC after transfer of the interventionalist, and 32 patients were transferred to the CSC for MT. The groups did not differ with regard to median Onset–CT and CT–Phone times. Significant differences between the groups were found for the primary outcome measure CT–Arrival time (‘D+D group’: median 121 (IQR 108–134) min vs 181 (157–219) min for the ‘D+S group’; P<0.001). Time difference between the groups increased to more than 2 hours for median CT–Angio times (median 123 (IQR 93–147) min vs 252 (228–275) min; P<0.001). Conclusion Time intervals for the ‘D+D group’ were not inferior to those of the ‘D+S group’. Moreover, under certain conditions, the ‘drip-and-drive’ concept might even be superior.

Comparison of classification methods for voxel-based prediction of acute ischemic stroke outcome following intra-arterial intervention

Voxel-based tissue outcome prediction in acute ischemic stroke patients is highly relevant for both clinical routine and research. Previous research has shown that features extracted from baseline multi-parametric MRI datasets have a high predictive value and can be used for the training of classifiers, which can generate tissue outcome predictions for both intravenous and conservative treatments. However, with the recent advent and popularization of intra-arterial thrombectomy treatment, novel research specifically addressing the utility of predictive classi- fiers for thrombectomy intervention is necessary for a holistic understanding of current stroke treatment options. The aim of this work was to develop three clinically viable tissue outcome prediction models using approximate nearest-neighbor, generalized linear model, and random decision forest approaches and to evaluate the accuracy of predicting tissue outcome after intra-arterial treatment. Therefore, the three machine learning models were trained, evaluated, and compared using datasets of 42 acute ischemic stroke patients treated with intra-arterial thrombectomy. Classifier training utilized eight voxel-based features extracted from baseline MRI datasets and five global features. Evaluation of classifier-based predictions was performed via comparison to the known tissue outcome, which was determined in follow-up imaging, using the Dice coefficient and leave-on-patient-out cross validation. The random decision forest prediction model led to the best tissue outcome predictions with a mean Dice coefficient of 0.37. The approximate nearest-neighbor and generalized linear model performed equally suboptimally with average Dice coefficients of 0.28 and 0.27 respectively, suggesting that both non-linearity and machine learning are desirable properties of a classifier well-suited to the intra-arterial tissue outcome prediction problem.

Iterative Reconstruction Improves Both Objective and Subjective Image Quality in Acute Stroke CTP

Purpose Computed tomography perfusion (CTP) imaging in acute ischemic stroke (AIS) suffers from measurement errors due to image noise. The purpose of this study was to investigate if iterative reconstruction (IR) algorithms can be used to improve the diagnostic value of standard-dose CTP in AIS. Methods Twenty-three patients with AIS underwent CTP with standardized protocol and dose. Raw data were reconstructed with filtered back projection (FBP) and IR with intensity levels 3, 4, 5. Image quality was objectively (quantitative perfusion values, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) and subjectively (overall image quality) assessed. Ischemic core and perfusion mismatch were visually rated. Discriminative power for tissue outcome prediction was determined by the area under the receiver operating characteristic curve (AUC) resulting from the overlap between follow-up infarct lesions and stepwise thresholded CTP maps. Results With increasing levels of IR, objective image quality (SNR and CNR in white matter and gray matter, elimination of error voxels) and subjective image quality improved. Using IR, mean transit time (MTT) was higher in ischemic lesions, while there was no significant change of cerebral blood volume (CBV) and cerebral blood flow (CBF). Visual assessments of perfusion mismatch changed in 4 patients, while the ischemic core remained constant in all cases. Discriminative power for infarct prediction as represented by AUC was not significantly changed in CBV, but increased in CBF and MTT (mean (95% CI)): 0.72 (0.67–0.76) vs. 0.74 (0.70–0.78) and 0.65 (0.62–0.67) vs 0.67 (0.64–0.70). Conclusion In acute stroke patients, IR improves objective and subjective image quality when applied to standard-dose CTP. This adds to the overall confidence of CTP in acute stroke triage.