Towards real-time detection of seizures in awake rats with GPU-accelerated diffuse optical tomography

Three-dimensional optical imaging of brain activation during transcranial magnetic stimulation

Repetitive transcranial magnetic stimulation (rTMS) of the brain is an effective clinical treatment for psychiatric disorders. Noninvasive neuroimaging during rTMS allows visualization of cortical brain activations and responses, and it is a potential tool for investigating the neurophysiological response occurring actively during stimulation. In this paper, we present a fast diffuse optical tomography (DOT) approach for three-dimensional brain mapping of hemodynamics during rTMS. Eight healthy subjects were enrolled in the study. These subjects received 10 Hz stimulation with 80%and 100%of resting motor threshold (rMT), respectively, for 4 seconds for each stimulation. Significant hemodynamic activation was observed in all cases with the strongest response when 100%rMT stimulation was applied. This work demonstrates that fast DOT has the potential to become a powerful tool for noninvasive three-dimensional imaging of the brain during rTMS.

Fast noninvasive functional diffuse optical tomography for brain imaging

Advances in epilepsy studies have shown that specific changes in hemodynamics precede and accompany seizure onset and propagation. However, it has been challenging to noninvasively detect these changes in real time and in humans, due to the lack of fast functional neuroimaging tools. In this study, we present a functional diffuse optical tomography (DOT) method with the guidance of an anatomical human head atlas for 3-dimensionally mapping the brain in real time. Central to our DOT system is a human head interface coupled with a technique that can incorporate topological information of the brain surface into the DOT image reconstruction. The performance of the DOT system was tested by imaging motor tasks-involved brain activities on N = 6 subjects (3 epilepsy patients and 3 healthy controls). We observed diffuse areas of activations from the reconstructed [HbT] images of patients, relative to more focal activations for healthy subjects. Moreover, significant pretask hemodynamic activations were also seen in the motor cortex of patients, which indicated abnormal activities persistent in the brain of an epilepsy patient. This work demonstrates that fast functional DOT is a valuable tool for noninvasive 3-dimensional mapping of brain hemodynamics.

Toward real-time diffuse optical tomography: accelerating light propagation modeling employing parallel computing on GPU and CPU

Parameter recovery in diffuse optical tomography is a computationally expensive algorithm, especially when used for large and complex volumes, as in the case of human brain functional imaging. The modeling of light propagation, also known as the forward problem, is the computational bottleneck of the recovery algorithm, whereby the lack of a real-time solution is impeding practical and clinical applications. The objective of this work is the acceleration of the forward model, within a diffusion approximation-based finite-element modeling framework, employing parallelization to expedite the calculation of light propagation in realistic adult head models. The proposed methodology is applicable for modeling both continuous wave and frequency-domain systems with the results demonstrating a 10-fold speed increase when GPU architectures are available, while maintaining high accuracy. It is shown that, for a very high-resolution finite-element model of the adult human head with ∼600,000 nodes, consisting of heterogeneous layers, light propagation can be calculated at ∼0.25  s/excitation source.

GPU-based acceleration and mesh optimization of finite-element-method-based quantitative photoacoustic tomography: a step towards clinical applications

Finite element method (FEM)-based time-domain quantitative photoacoustic tomography (TD-qPAT) is a powerful approach, as it provides highly accurate quantitative imaging capability by recovering absolute tissue absorption coefficients for functional imaging. However, this approach is extremely computationally demanding, and requires days for the reconstruction of one set of images, making it impractical to be used in clinical applications, where a large amount of data needs to be processed in a limited time scale. To address this challenge, here we present a graphic processing unit (GPU)-based parallelization method to accelerate the image reconstruction using FEM-based TD-qPAT. In addition, to further optimize FEM-based TD-qPAT reconstruction, an adaptive meshing technique, along with mesh density optimization, is adopted. Phantom experimental data are used in our study to evaluate the GPU-based TD-qPAT algorithm, as well as the adaptive meshing technique. The results show that our new approach can considerably reduce the computation time by at least 136-fold over the current central processing unit (CPU)-based algorithm. The quality of image reconstruction is also improved significantly when adaptive meshing and mesh density optimization are applied.

Image reconstruction of oxidized cerebral cytochrome C oxidase changes from broadband near-infrared spectroscopy data

In diffuse optical tomography (DOT), overlapping and multidistance measurements are required to reconstruct depth-resolved images of oxy- ([Formula: see text]) and deoxy- (HHb) hemoglobin concentration changes occurring in the brain. These can be considered an indirect measure of brain activity, under the assumption of intact neurovascular coupling. Broadband systems also allow changes in the redox state of cytochrome c oxidase (oxCCO) to be measured, which can be an important biomarker when neurovascular coupling is impaired. We used DOT to reconstruct images of [Formula: see text], [Formula: see text], and [Formula: see text] from data acquired with a broadband system. Four healthy volunteers were measured while performing a visual stimulation task (4-Hz inverting checkerboard). The broadband system was configured to allow multidistance and overlapping measurements of the participants' visual cortex with 32 channels. A multispectral approach was employed to reconstruct changes in concentration of the three chromophores during the visual stimulation. A clear and focused activation was reconstructed in the left occipital cortex of all participants. The difference between the residuals of the three-chromophore model and of the two-chromophore model (recovering only [Formula: see text] and [Formula: see text]) exhibits a spectrum similar to that of oxCCO. These results form a basis for further studies aimed to further optimize image reconstruction of [Formula: see text].

Planar implantable sensor for in vivo measurement of cellular oxygen metabolism in brain tissue

BACKGROUND

Brain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation.

NEW METHOD

We tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation.

RESULTS

Sensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor.

COMPARISON WITH EXISTING METHOD

Oxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application.

CONCLUSIONS

The planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution.

Wearable 3-D Photoacoustic Tomography for Functional Brain Imaging in Behaving Rats

Understanding the relationship between brain function and behavior remains a major challenge in neuroscience. Photoacoustic tomography (PAT) is an emerging technique that allows for noninvasive in vivo brain imaging at micrometer-millisecond spatiotemporal resolution. In this article, a novel, miniaturized 3D wearable PAT (3D-wPAT) technique is described for brain imaging in behaving rats. 3D-wPAT has three layers of fully functional acoustic transducer arrays. Phantom imaging experiments revealed that the in-plane X-Y spatial resolutions were ~200 μm for each acoustic detection layer. The functional imaging capacity of 3D-wPAT was demonstrated by mapping the cerebral oxygen saturation via multi-wavelength irradiation in behaving hyperoxic rats. In addition, we demonstrated that 3D-wPAT could be used for monitoring sensory stimulus-evoked responses in behaving rats by measuring hemodynamic responses in the primary visual cortex during visual stimulation. Together, these results show the potential of 3D-wPAT for brain study in behaving rodents.

Parallel Solver for Diffuse Optical Tomography on Realistic Head Models With Scattering and Clear Regions

Diffuse optical tomography is an imaging technique, based on evaluation of how light propagates within the human head to obtain the functional information about the brain. Precision in reconstructing such an optical properties map is highly affected by the accuracy of the light propagation model implemented, which needs to take into account the presence of clear and scattering tissues. We present a numerical solver based on the radiosity-diffusion model, integrating the anatomical information provided by a structural MRI. The solver is designed to run on parallel heterogeneous platforms based on multiple GPUs and CPUs. We demonstrate how the solver provides a 7 times speed-up over an isotropic-scattered parallel Monte Carlo engine based on a radiative transport equation for a domain composed of 2 million voxels, along with a significant improvement in accuracy. The speed-up greatly increases for larger domains, allowing us to compute the light distribution of a full human head ( ≈ 3 million voxels) in 116 s for the platform used.

Evaluating real-time image reconstruction in diffuse optical tomography using physiologically realistic test data

In diffuse optical tomography (DOT), real-time image reconstruction of oxy- and deoxy-haemoglobin changes occurring in the brain could give valuable information in clinical care settings. Although non-linear reconstruction techniques could provide more accurate results, their computational burden makes them unsuitable for real-time applications. Linear techniques can be employed under the assumption that the expected change in absorption is small. Several approaches exist, differing primarily in their handling of regularization and the noise statistics. In real experiments, it is impossible to compute the true noise statistics, because of the presence of physiological oscillations in the measured data. This is even more critical in real-time applications, where no off-line filtering and averaging can be performed to reduce the noise level. Therefore, many studies substitute the noise covariance matrix with the identity matrix. In this paper, we examined two questions: does using the noise model with realistic, imperfect data yield an improvement in image quality compared to using the identity matrix; and what is the difference in quality between online and offline reconstructions. Bespoke test data were created using a novel process through which simulated changes in absorption were added to real resting-state DOT data. A realistic multi-layer head model was used as the geometry for the reconstruction. Results validated our assumptions, highlighting the validity of computing the noise statistics from the measured data for online image reconstruction, which was performed at 2 Hz. Our results can be directly extended to a real application where real-time imaging is required.

Noninvasive high-speed photoacoustic tomography of cerebral hemodynamics in awake-moving rats

We present a noninvasive method of photoacoustic tomography (PAT) for imaging cerebral hemodynamics in awake-moving rats. The wearable PAT (wPAT) system has a size of 15 mm in height and 33 mm in diameter, and a weight of ~8 g (excluding cabling). The wPAT achieved an imaging rate of 3.33 frames/s with a lateral resolution of 243 μm. Animal experiments were designed to show wPAT feasibility for imaging cerebral hemodynamics on awake-moving animals. Results showed that the cerebral oxy-hemoglobin and deoxy-hemoglobin changed significantly in response to hyperoxia; and, after the injection of pentylenetetrazol (PTZ), cerebral blood volume changed faster over time and larger in amplitude for rats in awake-moving state compared with rats under anesthesia. By providing a light-weight, high-resolution technology for in vivo monitoring of cerebral hemodynamics in awake-behaving animals, it will be possible to develop a comprehensive understanding on how activity alters hemodynamics in normal and diseased states.