Dataset Information

Visualization and molecular characterization of whole-brain vascular networks with capillary resolution.

ABSTRACT: Structural elucidation and molecular scrutiny of cerebral vasculature is crucial for understanding the functions and diseases of the brain. Here, we introduce SeeNet, a method for near-complete three-dimensional visualization of cerebral vascular networks with high signal-to-noise ratios compatible with molecular phenotyping. SeeNet employs perfusion of a multifunctional crosslinker, vascular casting by temperature-controlled polymerization of hybrid hydrogels, and a bile salt-based tissue-clearing technique optimized for observation of vascular connectivity. SeeNet is capable of whole-brain visualization of molecularly characterized cerebral vasculatures at the single-microvessel level. Moreover, SeeNet reveals a hitherto unidentified vascular pathway bridging cerebral and hippocampal vessels, thus serving as a potential tool to evaluate the connectivity of cerebral vasculature.

SUBMITTER: Miyawaki T

PROVIDER: S-EPMC7046771 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Visualization and molecular characterization of whole-brain vascular networks with capillary resolution.

Miyawaki Takeyuki T Morikawa Shota S Susaki Etsuo A EA Nakashima Ai A Takeuchi Haruki H Yamaguchi Shun S Ueda Hiroki R HR Ikegaya Yuji Y

Nature communications 20200227 1

Structural elucidation and molecular scrutiny of cerebral vasculature is crucial for understanding the functions and diseases of the brain. Here, we introduce SeeNet, a method for near-complete three-dimensional visualization of cerebral vascular networks with high signal-to-noise ratios compatible with molecular phenotyping. SeeNet employs perfusion of a multifunctional crosslinker, vascular casting by temperature-controlled polymerization of hybrid hydrogels, and a bile salt-based tissue-clear ...[more]

PMID: 32107377

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Project description:ObjectiveTo verify the visibility of physiological 18F-fluorodeoxyglucose (18F-FDG) uptake in nuclei in and around the brainstem by a whole-body (WB) silicon photomultiplier positron emission tomography (SiPM-PET) scanner with point-spread function (PSF) reconstruction using various iteration numbers.MethodsTen healthy subjects (5 men, 5 women; mean age, 56.0 ± 5.0 years) who underwent 18F-FDG PET/CT using a WB SiPM-PET scanner and magnetic resonance imaging (MRI) of the brain including a spin-echo three-dimensional sampling perfection with application-optimized contrasts using different flip angle evolutions fluid-attenuated inversion recovery (3D-FLAIR) and a 3D-T1 magnetization-prepared rapid gradient-echo (T1-MPRAGE) images were enrolled. Each acquired PET image was reconstructed using ordered-subset expectation maximization (OSEM) with iteration numbers of 4, 16, 64, and 256 (subset 5 fixed) + time-of-flight (TOF) + PSF. The reconstructed PET images and 3D-FLAIR images for each subject were registered to individual T1-MPRAGE volumes using normalized mutual information criteria. For each MR-coregistered individual PET image, the pattern of FDG uptake in the inferior olivary nuclei (ION), dentate nuclei (DN), midbrain raphe nuclei (MRN), inferior colliculi (IC), mammillary bodies (MB), red nuclei (RN), subthalamic nuclei (STN), lateral geniculate nuclei (LGN), medial geniculate nuclei (MGN), and superior colliculi (SC) was visually classified into the following three categories: good, clearly distinguishable FDG accumulation; fair, obscure contour of FDG accumulation; poor, FDG accumulation indistinguishable from surrounding uptake.ResultsAmong individual 18F-FDG PET images with OSEM iterations of 4, 16, 64, and 256 + TOF + PSF, the iteration numbers that showed the best visibility in each structure were as follows: ION, MRN, LGN, MGN, and SC, iteration 64; DN, iteration 16; IC, iterations 16, 64, and 256; MB, iterations 64 and 256; and RN and STN, iterations 16 and 64, respectively. Of the four iterations, the 18F-FDG PET image of iteration 64 visualized FDG accumulation in small structures in and around the brainstem most clearly (good, 98 structures; fair, 2 structures).ConclusionsA clinically available WB SiPM-PET scanner is useful for visualizing physiological FDG uptake in small brain nuclei, using a sufficiently high number of iterations for OSEM with TOF and PSF reconstructions.

Project description:We present the first evidence for vascular regulation driving fMRI signals in specific functional brain networks. Using concurrent neuronal and vascular stimuli, we collected 30 BOLD fMRI datasets in 10 healthy individuals: a working memory task, flashing checkerboard stimulus, and CO2 inhalation challenge were delivered in concurrent but orthogonal paradigms. The resulting imaging data were averaged together and decomposed using independent component analysis, and three "neuronal networks" were identified as demonstrating maximum temporal correlation with the neuronal stimulus paradigms: Default Mode Network, Task Positive Network, and Visual Network. For each of these, we observed a second network component with high spatial overlap. Using dual regression in the original 30 datasets, we extracted the time-series associated with these network pairs and calculated the percent of variance explained by the neuronal or vascular stimuli using a normalized R2 parameter. In each pairing, one network was dominated by the appropriate neuronal stimulus, and the other was dominated by the vascular stimulus as represented by the end-tidal CO2 time-series recorded in each scan. We acquired a second dataset in 8 of the original participants, where no CO2 challenge was delivered and CO2 levels fluctuated naturally with breathing variations. Although splitting of functional networks was not robust in these data, performing dual regression with the network maps from the original analysis in this new dataset successfully replicated our observations. Thus, in addition to responding to localized metabolic changes, the brain's vasculature may be regulated in a coordinated manner that mimics (and potentially supports) specific functional brain networks. Multi-modal imaging and advances in fMRI acquisition and analysis could facilitate further study of the dual nature of functional brain networks. It will be critical to understand network-specific vascular function, and the behavior of a coupled vascular-neural network, in future studies of brain pathology.

Dataset Information

Visualization and molecular characterization of whole-brain vascular networks with capillary resolution.

Publications

Visualization and molecular characterization of whole-brain vascular networks with capillary resolution.

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