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... Show moreThe 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. Show less
Bouts, M.J.; Tiebosch, I.A.; Rudrapatna, U.S.; Toorn, A. van der; Wu, O.; Dijkhuizen, R.M. 2017
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... Show moreEstimation 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. Show less
Dreier, J.P.; Fabricius, M.; Ayata, C.; Sakowitz, O.W.; Shuttleworth, C.W.; Dohmen, C.; ... ; Hartings, J.A. 2017
