In silico trials for treatment of acute ischemic stroke: Design and implementation

Miller, Claire; Padmos, Raymond M.; Kolk, Max van der; Józsa, Tamás; Samuels, Noor; Xue, Yidan; Payne, Stephen J.; Hoekstra, Alfons G.

doi:10.1016/j.compbiomed.2021.104802

Cited by 22 publications

(27 citation statements)

References 77 publications

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“…As part of the INSIST project [ 64 ], we are developing computational models of AIS at multiple scales to aid in optimising AIS treatments and developing medical devices. The micro-scale models presented here and in previous works [ 37 , 40 ] can in future be coupled with organ-scale models of AIS [ 65 – 67 ] and play a key role in predicting the secondary tissue damage caused by microthrombi after an unsuccessful thrombectomy [ 68 – 70 ].…”

Section: Discussionmentioning

confidence: 99%

Quantification of hypoxic regions distant from occlusions in cerebral penetrating arteriole trees

et al. 2022

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The microvasculature plays a key role in oxygen transport in the mammalian brain. Despite the close coupling between cerebral vascular geometry and local oxygen demand, recent experiments have reported that microvascular occlusions can lead to unexpected distant tissue hypoxia and infarction. To better understand the spatial correlation between the hypoxic regions and the occlusion sites, we used both in vivo experiments and in silico simulations to investigate the effects of occlusions in cerebral penetrating arteriole trees on tissue hypoxia. In a rat model of microembolisation, 25 μm microspheres were injected through the carotid artery to occlude penetrating arterioles. In representative models of human cortical columns, the penetrating arterioles were occluded by simulating the transport of microspheres of the same size and the oxygen transport was simulated using a Green’s function method. The locations of microspheres and hypoxic regions were segmented, and two novel distance analyses were implemented to study their spatial correlation. The distant hypoxic regions were found to be present in both experiments and simulations, and mainly due to the hypoperfusion in the region downstream of the occlusion site. Furthermore, a reasonable agreement for the spatial correlation between hypoxic regions and occlusion sites is shown between experiments and simulations, which indicates the good applicability of in silico models in understanding the response of cerebral blood flow and oxygen transport to microemboli.

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Section: Discussionmentioning

confidence: 99%

Quantification of hypoxic regions distant from occlusions in cerebral penetrating arteriole trees

et al. 2022

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“…The cerebral perfusion model is defined by a set of input parameters required to solve Equation (1) subject to the boundary condition Equations ( 4)- (6). The proposed computational perfusion model generation method integrates clinical data to set up simulations accordingly, as depicted in Figure 1.…”

Section: Computational Perfusion Model Generationmentioning

confidence: 99%

“…Thrombolysis [2] and thrombectomy [1] revolutionised stroke treatment but up to 66% of patients remain functionally dependent [3,4]. The IN Silico clinical trials for the treatment of acute Ischaemic STroke (INSIST) consortium [5,6] set out to improve existing stroke treatments based on computational models [7][8][9][10][11]. In AIS, perfusion shortage is the primary driver of infarct formation associated with irreversible brain tissue and function loss.…”

Section: Introductionmentioning

confidence: 99%

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MRI-based computational model generation for cerebral perfusion simulations in health and ischaemic stroke

Jozsa

Petr

Barkhof

et al. 2022

Preprint

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Cerebral perfusion models were found to be promising research tools to predict the impact of acute ischaemic stroke and related treatments on cerebral blood flow (CBF) linked to patients' functional outcome. To provide insights relevant to clinical trials, perfusion simulations need to become suitable for group-level investigations, but computational studies to date have been limited to a few patient-specific cases. This study set out to overcome issues related to automated parameter inference, that restrict the sample size of perfusion simulations, by integrating neuroimaging data. Seventy-five brain models were generated using measurements from a cohort of 75 healthy elderly individuals to model resting state CBF distributions. Computational perfusion model geometries were adjusted using healthy reference subjects' T1-weighted MRI. Haemodynamic model parameters were determined from CBF measurements corresponding to arterial spin labelling perfusion MRI. Thereafter, perfusion simulations were conducted for 150 acute ischaemic stroke cases by simulating an occlusion and cessation of blood flow in the left and right middle cerebral arteries. The anatomical (geometrical) fitness of the brain models was evaluated by comparing the simulated grey and white matter (GM and WM) volumes to measurements in healthy reference subjects. Statistically significant, strong positive correlations were found in both cases (GM: Pearson's r 0.74, P-value< 0.001; WM: Pearson's r 0.84, P-value< 0.001). Haemodynamic parameter tuning was verified by comparing total volumetric blood flow rate to the brain in reference subjects and simulations resulting in Pearson's r 0.89, and P-value< 0.001. In acute ischaemic stroke cases, the simulated infarct volume using a perfusion-based proxy was 197±25 ml. Computational results showed excellent agreement with anatomical and haemodynamic literature data corresponding to T1-weighted, T2-weighted, and phase-contrast MRI measurements both in healthy scenarios and in acute ischaemic stroke cases. Simulation results represented solely worst-case stroke scenarios with large infarcts because compensatory mechanisms, e.g. collaterals, were neglected. The established computational brain model generation framework provides a foundation for population-level cerebral perfusion simulations and for in silico clinical stroke trials which could assist in medical device and drug development.

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“…Miller et al [18] and Konduri et al [19] have previously published a framework for designing and implementing an IST for AIS. In this study, we present and integrate a novel surrogate model, based on logistic regression trained on outcomes from a finite-element model of thrombectomy, into our IST framework [18,19] and validate the model using the MR CLEAN trial [1,20] .…”

Section: Introductionmentioning

confidence: 99%

In silico thrombectomy trials for acute ischemic stroke

Miller

Konduri

Bridio

et al. 2023

Computer Methods and Programs in Biomedicine

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In silico trials for treatment of acute ischemic stroke: Design and implementation

Cited by 22 publications

References 77 publications

Quantification of hypoxic regions distant from occlusions in cerebral penetrating arteriole trees

Quantification of hypoxic regions distant from occlusions in cerebral penetrating arteriole trees

MRI-based computational model generation for cerebral perfusion simulations in health and ischaemic stroke

In silico thrombectomy trials for acute ischemic stroke

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