Prediction of hemorrhagic transformation after experimental ischemic stroke using MRI-based algorithms.

Estimation of hemorrhagic transformation (HT) risk is crucial for treatment decision-making after acute ischemic stroke. We aimed to determine the accuracy of multiparametric MRI-based predictive algorithms in calculating probability of HT after stroke. Spontaneously, hypertensive rats were subjected to embolic stroke and, after 3 h treated with tissue plasminogen activator (Group I: n = 6) or vehicle (Group II: n = 7). Brain MRI measurements of T2, T2*, diffusion, perfusion, and blood-brain barrier permeability were obtained at 2, 24, and 168 h post-stroke. Generalized linear model and random forest (RF) predictive algorithms were developed to calculate the probability of HT and infarction from acute MRI data. Validation against seven-day outcome on MRI and histology revealed that highest accuracy of hemorrhage prediction was achieved with a RF-based model that included spatial brain features (Group I: area under the receiver-operating characteristic curve (AUC) = 0.85 ± 0.14; Group II: AUC = 0.89 ± 0.09), with significant improvement over perfusion- or permeability-based thresholding methods. However, overlap between predicted and actual tissue outcome was significantly lower for hemorrhage prediction models (maximum Dice's Similarity Index (DSI) = 0.20 ± 0.06) than for infarct prediction models (maximum DSI = 0.81 ± 0.06). Multiparametric MRI-based predictive algorithms enable early identification of post-ischemic tissue at risk of HT and may contribute to improved treatment decision-making after acute ischemic stroke.Multivariate analysis of psychological dat

Magnetic resonance imaging of local and remote vascular remodelling after experimental stroke.

The pattern of vascular remodelling in relation to recovery after stroke remains largely unclear. We used steady-state contrast-enhanced magnetic resonance imaging to assess the development of cerebral blood volume and microvascular density in perilesional and exofocal areas from (sub)acutely to chronically after transient stroke in rats. Microvascular density was verified histologically after infusion with Evans Blue dye. At day 1, microvascular cerebral blood volume and microvascular density were reduced in and around the ischemic lesion (intralesional borderzone: microvascular cerebral blood volume = 72 ± 8%; microvascular density = 76 ± 8%) (P < 0.05), while total cerebral blood volume remained relatively unchanged. Perilesional microvascular cerebral blood volume and microvascular density subsequently normalized (day 7) and remained relatively stable (day 70). In remote ipsilateral areas in the thalamus and substantia nigra - not part of the ischemic lesion - microvascular density gradually increased between days 1 and 70 (thalamic ventral posterior nucleus: microvascular density = 119 ± 9%; substantia nigra: microvascular density = 122 ± 8% (P < 0.05)), which was confirmed histologically. Our data indicate that initial microvascular collapse, with maintained collateral flow in larger vessels, is followed by dynamic revascularization in perilesional tissue. Furthermore, progressive neovascularization in non-ischemic connected areas may offset secondary neuronal degeneration and/or contribute to non-neuronal tissue remodelling. The complex spatiotemporal pattern of vascular remodelling, involving regions outside the lesion territory, may be a critical endogenous process to promote post-stroke brain reorganization.FSW – Publicaties zonder aanstelling Universiteit Leide

Acquisition, estimation, and interpretation of diffusion- and relaxation-based cerebral MRI contrasts

From the past few years, Magnetic Resonance Imaging has significantly enhanced our understanding of brain structure and function. In particular, developments in Diffusion MRI are providing unique contrast mechanisms heretofore unavailable from other imaging modalities. Although predominantly used for structural imaging, current research is hinting at their suitability for functional imaging too. The aim of research conducted as part of this thesis was to further our understanding of some of the recently proposed strucutral and functional diffusion contrast mechanisms. This work involved aspects of MRI sequence development, data modeling and interpretation. The possible role of diffusion MRI in functional imaging was explored in the first study described in this thesis. The main contribution of this work was to provide an alternative explanation for an important observation that formed the basis of one class of functional diffusion contrasts. This work highlights the possible confounds (statistical and physiological) that can affect potential functional diffusion contrasts. In the second study, we report about two alternative MRI contrast mechanisms for visualizing spreading depolarizations, a pathophysiological condition implicated in acute ischemic stroke, migraine with aura, and in delayed cerebral ischemia after subarachnoid hemorrhage. Apart from cross-comparing three MR contrast mechanisms, the key contribution of this work was to highlight the possibility of simultaneously obtaining complementary MRI contrasts (T2 and apparent diffusion coefficient) for furthering our understanding of spreading depolarizations. In the third study, we sought to gain deeper insight into the contrast mechanisms underlying the recently proposed Diffusion Kurtosis Imaging (DKI), an extension to widely used Diffusion Tensor imaging (DTI), in the framework of chronic experimental stroke. For this, comparisons between DKI and DTI changes following stroke were performed not only on select few regions of interest, as commonly pursued, but also using a machine-learning approach. Moreover, to understand the underlying histopathological changes driving post-stroke diffusion parameter changes, we compared various immunohistochemical data with diffusion parameter changes in two quantitative ways. Results from this study indicate that the combined range of microstructural sensitivity provided by DKI parameters forms a superset of that provided by DTI parameters and thus offer greater insight into tissue (re)organization after stroke. However, the non-specificity of diffusion-based parameters vis-a-vis the underlying biological processes was highlighted by aspecific correlation between MRI diffusion contrasts and histopathology. This calls for greater caution in interpreting diffusion imaging results. In the final part of the thesis we report about the advantages of using complex-valued MR data for estimation of basic MRI parameters (T1, T2 and T2*), unlike the commonly used strategy of using magnitude MRI data. Through simulations and with acquired data we demonstrate that fitting to complex-valued data can yield unbiased estimates and lower variance in comparison with estimates obtained with even the most accurate data models that use magnitude data. Similar extensions can perhaps be made for other MR estimation problems too, including mapping diffusion parameters

Valproate Reduces Delayed Brain Injury in a Rat Model of Subarachnoid Hemorrhage

BACKGROUND AND PURPOSE: Spreading depolarizations (SDs) may contribute to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). We tested whether SD-inhibitor valproate reduces brain injury in an SAH rat model with and without experimental SD induction. METHODS: Rats were randomized in a 2×2 design and pretreated with valproate (200 mg/kg) or vehicle for 4 weeks. SAH was induced by endovascular puncture of the right internal carotid bifurcation. One day post-SAH, brain tissue damage was measured with T2-weighted magnetic resonance imaging, followed by cortical application of 1 mol/L KCl (to induce SDs) or NaCl (no SDs). Magnetic resonance imaging was repeated on day 3 followed by histology to confirm neuronal death. Neurological function was measured with an inclined slope test. RESULTS: In the groups with KCl application, lesion growth between days 1 and 3 was 57±73 mm3 in the valproate-treated versus 237±232 mm3 in the vehicle-treated group. In the groups without SD induction, lesion growth in the valproate- and vehicle-treated groups was 8±20 mm3 versus 27±52 mm3. On fitting a 2-way analysis of variance model, we found a significant interaction effect between treatment and KCl/NaCl application of 161 mm3 (P=0.04). Number and duration of SDs, mortality, and neurological function were not statistically significantly different between groups. Lesion growth on magnetic resonance imaging correlated to histological infarct volume (Spearman's rho =0.83; P=0.0004), with areas of lesion growth exhibiting reduced neuronal death compared with primary lesions. CONCLUSIONS: In our rat SAH model, valproate treatment significantly reduced brain lesion growth after KCl application. Future studies are needed to confirm that this protective effect is based on SD inhibition

Valproate Reduces Delayed Brain Injury in a Rat Model of Subarachnoid Hemorrhage

BACKGROUND AND PURPOSE: Spreading depolarizations (SDs) may contribute to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). We tested whether SD-inhibitor valproate reduces brain injury in an SAH rat model with and without experimental SD induction. METHODS: Rats were randomized in a 2×2 design and pretreated with valproate (200 mg/kg) or vehicle for 4 weeks. SAH was induced by endovascular puncture of the right internal carotid bifurcation. One day post-SAH, brain tissue damage was measured with T2-weighted magnetic resonance imaging, followed by cortical application of 1 mol/L KCl (to induce SDs) or NaCl (no SDs). Magnetic resonance imaging was repeated on day 3 followed by histology to confirm neuronal death. Neurological function was measured with an inclined slope test. RESULTS: In the groups with KCl application, lesion growth between days 1 and 3 was 57±73 mm3 in the valproate-treated versus 237±232 mm3 in the vehicle-treated group. In the groups without SD induction, lesion growth in the valproate- and vehicle-treated groups was 8±20 mm3 versus 27±52 mm3. On fitting a 2-way analysis of variance model, we found a significant interaction effect between treatment and KCl/NaCl application of 161 mm3 (P=0.04). Number and duration of SDs, mortality, and neurological function were not statistically significantly different between groups. Lesion growth on magnetic resonance imaging correlated to histological infarct volume (Spearman's rho =0.83; P=0.0004), with areas of lesion growth exhibiting reduced neuronal death compared with primary lesions. CONCLUSIONS: In our rat SAH model, valproate treatment significantly reduced brain lesion growth after KCl application. Future studies are needed to confirm that this protective effect is based on SD inhibition