Multimodal reconstruction of microvascular-flow distributions using combined two-photon microscopy and Doppler optical coherence tomography

One contribution of 15 to a Theo Murphy meeting issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. LG, 0000-0001-7202-5176Hypercapnic-calibrated fMRI allows the estimation of the relative changes in the cerebral metabolic rate of oxygen (rCMRO 2 ) from combined BOLD and arterial spin labelling measurements during a functional task, and promises to permit more quantitative analyses of brain activity patterns. The estimation relies on a macroscopic model of the BOLD effect that balances oxygen delivery and consumption to predict haemoglobin oxygenation and the BOLD signal. The accuracy of calibrated fMRI approaches has not been firmly established, which is limiting their broader adoption. We use our recently developed microscopic vascular anatomical network model in mice as a ground truth simulator to test the accuracy of macroscopic, lumped-parameter BOLD models. In particular, we investigate the original Davis model and a more recent heuristic simplification. We find that these macroscopic models are inaccurate using the originally defined parameters, but that the accuracy can be significantly improved by redefining the model parameters to take on new values. In particular, we find that the parameter a that relates cerebral blood-volume changes to cerebral blood-flow changes is significantly smaller than typically assumed and that the optimal value changes with magnetic field strength. The results are encouraging in that they support the use of simple BOLD models to quantify BOLD signals, but further work is needed to understand the physiological interpretation of the redefined model parameters. This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

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“…The six reconstructed vascular stacks are illustrated in figure 2. Part of these stacks was previously published in Gagnon et al [39].…”

Section: (D) the Simple Heuristic Modelmentioning

confidence: 99%

Validation and optimization of hypercapnic-calibrated fMRI from oxygen-sensitive two-photon microscopy

Gagnon

Sakadžić

Lesage

et al. 2016

Phil. Trans. R. Soc. B

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“…The 6 angiogram constructs built in Gagnon et al [8], [21] were used as the substrates for the simulations. These constructs, referred here as Ai, i=1,…,6, were derived from measurements in the mouse somatosensory cortex using two-photon microscopy (2PH) and optical coherence tomography (OCT).…”

Section: Methodsmentioning

confidence: 99%

“…They were stored as volumes (3-dimensional arrays) with 1 μm isotropic resolution. Their total volumes were 0.27 ± 0.05 mm 3 (see [8], [21] for details). The vessel type (artery, vein, capillary) as well as oxygen saturation were provided by experimental measurements with a PO 2 sensitive molecular probe for these angiograms [6], [22].…”

Section: Methodsmentioning

confidence: 99%

“…Will the vMRF results depend on the underlying angiograms? Thus herein, we propose using a more precise calculation of the MR signal following our recent work [8], [9], by using Monte Carlo simulations of a large number of water protons diffusing in time in the imaging voxel. Another improvement is to base the calculations on realistic models of the vasculature obtained from three-dimensional high-resolution angiograms of the mouse cortex, instead of the simpler but far-from-realistic two-dimensional model of cylinders used in [2].…”

Section: Introductionmentioning

confidence: 99%

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Magnetic resonance fingerprinting based on realistic vasculature in mice

et al. 2017

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Magnetic resonance fingerprinting (MRF) was recently proposed as a novel strategy for MR data acquisition and analysis. A variant of MRF called vascular MRF (vMRF) followed, that extracted maps of three parameters of physiological importance: cerebral oxygen saturation (SatO2), mean vessel radius and cerebral blood volume (CBV). However, this estimation was based on idealized 2-dimensional simulations of vascular networks using random cylinders and the empirical Bloch equations convolved with a diffusion kernel. Here we focus on studying the vascular MR fingerprint using real mouse angiograms and physiological values as the substrate for the MR simulations. The MR signal is calculated ab initio with a Monte Carlo approximation, by tracking the accumulated phase from a large number of protons diffusing within the angiogram. We first study the identifiability of parameters in simulations, showing that parameters are fully estimable at realistically high signal-to-noise ratios (SNR) when the same angiogram is used for dictionary generation and parameter estimation, but that large biases in the estimates persist when the angiograms are different. Despite these biases, simulations show that differences in parameters remain estimable. We then applied this methodology to data acquired using the GESFIDE sequence with SPIONs injected into 9 young wild type and 9 old atherosclerotic mice. Both the pre injection signal and the ratio of post-to-pre injection signals were modeled, using 5-dimensional dictionaries. The vMRF methodology extracted significant differences in SatO2, mean vessel radius and CBV between the two groups, consistent across brain regions and dictionaries. Further validation work is essential before vMRF can gain wider application.

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“…In this paper, we aim to solely study the effect of fractional flow rate on plasma skimming. For this reason, same hematocrit cut-off conditions are applied to [28,29]. Also, relative hematocrit distribution along with vessel diameters at the microvascular network model.…”

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Effect of fractional blood flow on plasma skimming in the microvasculature

2017

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Although redistribution of red blood cells at bifurcated vessels is highly dependent on flow rate, it is still challenging to quantitatively express the dependency of flow rate in plasma skimming due to nonlinear cellular interactions. We suggest a plasma skimming model that can involve the effect of fractional blood flow at each bifurcation point. For validating the new model, it is compared with in vivo data at single bifurcation points, as well as microvascular network systems. In the simulation results, the exponential decay of plasma skimming parameter, M , along fractional flow rate shows the best performance in both cases.Red blood cells (RBCs) in microvessels are concentrated on the vessel core. Subsequently, a cell-free layer (CFL) with a few micrometer thickness is observed on the vessel wall. The CFL leads asymmetric redistribution of hematocrit at each bifurcation, called plasma skimming effect. As a continuous process of plasma skimming in microvascular networks, the average hematocrit in capillary beds is lower than the systemic hematocrit as reported in many previous studies [1][2][3][4][5][6][7][8]. Interestingly, the plasma skimming is recently revisited to develop new microchannels for detecting specific DNAs, proteins and cells by efficiently separating plasma from whole blood [9][10][11]. Also, it has been highlighted to accurately predict drug carrier distribution in the microvasculature [12][13][14][15][16][17][18]. For utilizing the plasma skimming to new applications in vitro and in vivo, it is crucial to quantitatively predict the redistribution of RBCs and plasma at bifurcations.From the early 70s, several experiments for quantifying the plasma skimming were performed [2,[19][20][21][22][23] In this paper, we aim to mathematically model fractional blood flow in a simple and generalized manner in order to computationally study its significance in plasma skimming, and also to accurately predict plasma skimming in the microvasculature. For this task, a recently developed plasma skimming model [26] is taken, and extended to take into account the effect of fractional blood flow. This new model is then validated with experimental data at single bifurcation level, and also at microvascular network level.While there are other plasma skimming models [25,27], the model developed by Gould and Linninger [26] is considered due to its easy extensibility. The model is as follows:where H is the hematocrit, M is the plasma skimming parameter, ζ is the hematocrit change coefficient due to plasma skimming, Q is the flow rate, A is the crosssectional area of each vessel, and subscript 0, 1, and 2 indicate the parent, and two daughter vessels, respectively. Specifically, the plasma skimming parameter M is related to the cross-sectional distribution of RBCs near bifurcation. Small M represents that RBCs are highly concentrated on the vessel core. In other words, plasma dominant region, or CFL, is developed on the near wall region. The two separated regions, expressed as RBCs and plasma areas, lead to strong...

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Multimodal reconstruction of microvascular-flow distributions using combined two-photon microscopy and Doppler optical coherence tomography

Cited by 28 publications

References 34 publications

Validation and optimization of hypercapnic-calibrated fMRI from oxygen-sensitive two-photon microscopy

Validation and optimization of hypercapnic-calibrated fMRI from oxygen-sensitive two-photon microscopy

Magnetic resonance fingerprinting based on realistic vasculature in mice

Effect of fractional blood flow on plasma skimming in the microvasculature

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