A three-dimensional blind deconvolution technique for improving contrast recovery in SPECT brain blood flow studies

Summary Aim: We demonstrate the heterogeneity of regional cerebral blood flow using a fractal approach and singlephoton emission computed tomography (SPECT). Method: Tc-99m-labelled ethylcysteine dimer was injected intravenously in 10 healthy controls and in 10 patients with dementia of frontal lobe type. The head was imaged with a gamma camera and transaxial, sagittal and coronal slices were reconstructed. Two hundred fifty-six symmetrical regions of interest (ROIs) were drawn onto each hemisphere of functioning brain matter. Fractal analysis was used to examine the spatial heterogeneity of blood flow as a function of the number of ROIs. Results: Relative dispersion (= coefficient of variation of the regional flows) was fractal-like in healthy subjects and could be characterized by a fractal dimension of 1.17 ± 0.05 (mean ± SD) for the left hemisphere and 1.15 ± 0.04 for the right hemisphere, respectively. The fractal dimension of 1.0 reflects completely homogeneous blood flow and 1.5 indicates a random blood flow distribution. Patients with dementia of frontal lobe type had a significantly lower fractal dimension of 1.04 ± 0.03 than in healthy controls. Conclusion: Within the limits of spatial resolution of SPECT, the heterogeneity of brain blood flow is well characterized by a fractal dimension. Fractal analysis may help brain scientists to assess age-, sex- and laterality-related anatomic and physiological changes of brain blood flow and possibly to improve precision of diagnostic information available for patient care.

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Faculty Opinions recommendation of Integrative regulation of human brain blood flow.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718229914.793509992 ◽

2015 ◽

Author(s):

Klaus Ulrich Klein

Keyword(s):

Blood Flow ◽

Human Brain ◽

Brain Blood Flow

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High-speed volumetric two-photon fluorescence imaging of neurovascular dynamics

Nature Communications ◽

10.1038/s41467-020-19851-1 ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Jiang Lan Fan ◽

Jose A. Rivera ◽

Wei Sun ◽

John Peterson ◽

Henry Haeberle ◽

...

Keyword(s):

Blood Flow ◽

High Speed ◽

Laser Scanning ◽

Three Dimensional ◽

Laser Scanning Microscopy ◽

Fluorescence Signal ◽

Imaging Method ◽

Spatiotemporal Resolution ◽

Two Photon

AbstractUnderstanding the structure and function of vasculature in the brain requires us to monitor distributed hemodynamics at high spatial and temporal resolution in three-dimensional (3D) volumes in vivo. Currently, a volumetric vasculature imaging method with sub-capillary spatial resolution and blood flow-resolving speed is lacking. Here, using two-photon laser scanning microscopy (TPLSM) with an axially extended Bessel focus, we capture volumetric hemodynamics in the awake mouse brain at a spatiotemporal resolution sufficient for measuring capillary size and blood flow. With Bessel TPLSM, the fluorescence signal of a vessel becomes proportional to its size, which enables convenient intensity-based analysis of vessel dilation and constriction dynamics in large volumes. We observe entrainment of vasodilation and vasoconstriction with pupil diameter and measure 3D blood flow at 99 volumes/second. Demonstrating high-throughput monitoring of hemodynamics in the awake brain, we expect Bessel TPLSM to make broad impacts on neurovasculature research.

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Modeling of aortic valve stenosis using fluid-structure interaction method

Perfusion ◽

10.1177/0267659121998549 ◽

2021 ◽

pp. 026765912199854

Author(s):

Mohammad Javad Ghasemi Pour ◽

Kamran Hassani ◽

Morteza Khayat ◽

Shahram Etemadi Haghighi

Keyword(s):

Blood Flow ◽

Aortic Valve ◽

Fluid Structure Interaction ◽

Three Dimensional ◽

Fluid Structure ◽

Structure Interaction ◽

Relaxation Phase ◽

Exercise Condition ◽

Time Dependent Domain ◽

Comparison Of The Results

Background and objectives: Fluid structure interaction (FSI) is defined as interaction of the structures with contacting fluids. The aortic valve experiences the interaction with blood flow in systolic phase. In this study, we have tried to predict the hemodynamics of blood flow through a normal and stenotic aortic valve in two relaxation and exercise conditions using a three-dimensional FSI method. Methods: The aorta valve was modeled as a three-dimensional geometry including a normal model and two others with 25% and 50% stenosis. The geometry of the aortic valve was extracted from CT images and the models were generated by MMIMCS software and then they were implemented in ANSYS software. The pulsatile flow rate was used for all cases and the numerical simulations were conducted based on a time-dependent domain. Results: The obtained results including the velocity, pressure, and shear stress contours in different systolic time sequences were explained and discussed. The maximum blood flow velocity in relaxation phase was obtained 1.62 m/s (normal valve), 3.78 m/s (25% stenosed valve), and 4.73 m/s (50% stenosed valve). In exercise condition, the maximum velocities are 2.86, 4.32, and 5.42 m/s respectively. The maximum blood pressure in relaxation phase was calculated 111.45 mmHg (normal), 148.66 mmHg (25% stenosed), and 164.21 mmHg (50% stenosed). However, the calculated values in exercise situation were 129.57, 163.58, and 191.26 mmHg. The validation of the predicted results was also conducted using existing literature. Conclusions: We believe that such model are useful tools for biomechanical experts. The further studies should be done using experimental data and the data are implemented on the boundary conditions for better comparison of the results.

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