Evaluation of rigid registration methods for whole head imaging in diffuse optical tomography

Functional brain imaging has become an important neuroimaging technique for the study of brain organization and development. Compared to other imaging techniques, diffuse optical tomography (DOT) is a portable and low-cost technique that can be applied to infants and hospitalized patients using an atlas-based light model. For DOT imaging, the accuracy of the forward model has a direct effect on the resulting recovered brain function within a field of view and so the accuracy of the spatially normalized atlas-based forward models must be evaluated. Herein, the accuracy of atlas-based DOT is evaluated on models that are spatially normalized via a number of different rigid registration methods on 24 subjects. A multileveled approach is developed to evaluate the correlation of the geometrical and sensitivity accuracies across the full field of view as well as within specific functional subregions. Results demonstrate that different registration methods are optimal for recovery of different sets of functional brain regions. However, the “nearest point to point” registration method, based on the EEG 19 landmark system, is shown to be the most appropriate registration method for image quality throughout the field of view of the high-density cap that covers the whole of the optically accessible cortex

Quantitative evaluation of atlas-based highdensity diffuse optical tomography for imaging of the human visual cortex

Image recovery in diffuse optical tomography (DOT) of the human brain often relies on accurate models of light propagation within the head. In the absence of subject specific models for image reconstruction, the use of atlas based models are showing strong promise. Although there exists some understanding in the use of some limited rigid model registrations in DOT, there has been a lack of a detailed analysis between errors in geometrical accuracy, light propagation in tissue and subsequent errors in dynamic imaging of recovered focal activations in the brain. In this work 11 different rigid registration algorithms, across 24 simulated subjects, are evaluated for DOT studies in the visual cortex. Although there exists a strong correlation (R(2) = 0.97) between geometrical surface error and internal light propagation errors, the overall variation is minimal when analysing recovered focal activations in the visual cortex. While a subject specific mesh gives the best results with a 1.2 mm average location error, no single algorithm provides errors greater than 4.5 mm. This work demonstrates that the use of rigid algorithms for atlas based imaging is a promising route when subject specific models are not available

Fast and efficient image reconstruction for high density diffuse optical imaging of the human brain

Real-time imaging of human brain has become an important technique within neuroimaging. In this study, a fast and efficient sensitivity map generation based on Finite Element Models (FEM) is developed which utilises a reduced sensitivitys matrix taking advantage of sparsity and parallelisation processes. Time and memory efficiency of these processes are evaluated and compared with conventional method showing that for a range of mesh densities from 50000 to 320000 nodes, the required memory is reduced over tenfold and computational time fourfold allowing for near real-time image recovery

Non-invasive Assessment of Cerebral Blood Flow and Oxygen Metabolism in Neonates during Hypothermic Cardiopulmonary Bypass: Feasibility and Clinical Implications

The neonatal brain is extremely vulnerable to injury during periods of hypoxia and/or ischemia. Risk of brain injury is increased during neonatal cardiac surgery, where pre-existing hemodynamic instability and metabolic abnormalities are combined with long periods of low cerebral blood flow and/or circulatory arrest. Our understanding of events associated with cerebral hypoxia-ischemia during cardiopulmonary bypass (CPB) remains limited, largely due to inadequate tools to quantify cerebral oxygen delivery and consumption non-invasively and in real-time. This pilot study aims to evaluate cerebral blood flow (CBF) and oxygen metabolism (CMRO2) intraoperatively in neonates by combining two novel non-invasive optical techniques: frequency-domain near-infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS). CBF and CMRO2 were quantified before, during and after deep hypothermic cardiopulmonary bypass (CPB) in nine neonates. Our results show significantly decreased CBF and CMRO2 during hypothermic CPB. More interestingly, a change of coupling between both variables is observed during deep hypothermic CPB in all subjects. Our results are consistent with previous studies using invasive techniques, supporting the concept of FD-NIRS/DCS as a promising technology to monitor cerebral physiology in neonates providing the potential for individual optimization of surgical management

Atlas-based high-density diffuse optical tomography for imaging the whole human cortex

Diffuse optical tomography (DOT) for brain imaging has the potential to be an alternative human brain mapping technique when MRI imaging is not applicable. It recovers tissue chromophore concentrations of brain tissue through measures of light transmission to monitor for example the resting-state brain dynamics. This imaging technique relies on simulation of the light propagation which can be generated based on a subject-specific model. There has been some study on using rigid atlas models as alternatives for model based DOT when subject-specific anatomical data is not available; but there is still a lack of detailed analysis between geometrical accuracy and internal light propagation in tissue for atlas-based DOT. This work is focused on High-Density DOT (HD-DOT) of the whole cortex based on atlas models from 11 different rigid registration algorithms across 24 subjects, and the results are evaluated in 19 areas of the human head. The correlation between geometrical surface error and internal light propagation errors is strong in most area but varies in different regions from R2 = 0.74 in the region around top of the head to R2 = 0.98 in the region around the temples. In the 11 registration methods, basic-4-landmark registration with 4.2mm average surface error and 50% average internal light propagation errors is shown to be the least accurate registration method whereas full-head landmark with non-iterative point to point with 1.7mm average surface error and 32% average internal light propagation error is shown to be the most accurate registration method for atlas-based DOT.</p

Atlas-based high-density diffuse optical tomography for imaging the whole human cortex

Diffuse optical tomography (DOT) for brain imaging has the potential to be an alternative human brain mapping technique when MRI imaging is not applicable. It recovers tissue chromophore concentrations of brain tissue through measures of light transmission to monitor for example the resting-state brain dynamics. This imaging technique relies on simulation of the light propagation which can be generated based on a subject-specific model. There has been some study on using rigid atlas models as alternatives for model based DOT when subject-specific anatomical data is not available; but there is still a lack of detailed analysis between geometrical accuracy and internal light propagation in tissue for atlas-based DOT. This work is focused on High-Density DOT (HD-DOT) of the whole cortex based on atlas models from 11 different rigid registration algorithms across 24 subjects, and the results are evaluated in 19 areas of the human head. The correlation between geometrical surface error and internal light propagation errors is strong in most area but varies in different regions from R2 = 0.74 in the region around top of the head to R2 = 0.98 in the region around the temples. In the 11 registration methods, basic-4-landmark registration with 4.2mm average surface error and 50% average internal light propagation errors is shown to be the least accurate registration method whereas full-head landmark with non-iterative point to point with 1.7mm average surface error and 32% average internal light propagation error is shown to be the most accurate registration method for atlas-based DOT.</p

Comparison of multi-distance and multi-frequency methods in frequency-domain near-infrared spectroscopy

Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive, non-ionizing imaging tool that can map brain hemodynamics. While not the most common fNIRS approach, frequency-domain NIRS (FD-NIRS) has shown an ability to estimate the absolute optical properties of tissues and, consequently, accurately estimate tissue chromophores concentrations. FD-NIRS can probe different depths in the tissue using multiple source-detector separations (multi-distance) or multiple modulation frequencies (multi-frequency). In this work, through experimental and simulation results, we demonstrate that using multi-distance and multi-frequency FD-NIRS yields similar results when estimating the optical properties of homogeneous and multi-layered tissues with less than ±10% error in estimations. We also examined some parameters that can affect the accuracy of the estimated optical properties, such as using different modulation frequencies in a multi-distance configuration and different source-detector separations for multi-frequency configuration.</p

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n=5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxel-to-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subject-specific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4 +/− 1 mm, significantly less than the average distance between cortical gyri. This specificity demonstrates that HD-DOT has sufficient image quality to be useful as a surrogate for fMRI