Association of cerebral metabolic rate following therapeutic hypothermia with 18-month neurodevelopmental outcomes after neonatal hypoxic ischemic encephalopathy.

BACKGROUND: Therapeutic hypothermia (TH) is standard of care for moderate to severe neonatal hypoxic ischemic encephalopathy (HIE) but many survivors still suffer lifelong disabilities and benefits of TH for mild HIE are under active debate. Development of objective diagnostics, with sensitivity to mild HIE, are needed to select, guide, and assess response to treatment. The objective of this study was to determine if cerebral oxygen metabolism (CMRO2) in the days after TH is associated with 18-month neurodevelopmental outcomes as the first step in evaluating CMRO2's potential as a diagnostic for HIE. Secondary objectives were to compare associations with clinical exams and characterise the relationship between CMRO2 and temperature during TH. METHODS: This was a prospective, multicentre, observational, cohort study of neonates clinically diagnosed with HIE and treated with TH recruited from the tertiary neonatal intensive care units (NICUs) of Boston Children's Hospital, Brigham and Women's Hospital, and Beth Israel Deaconess Medical Center between December 2015 and October 2019 with follow-up to 18 months. In total, 329 neonates ≥34 weeks gestational age admitted with perinatal asphyxia and suspected HIE were identified. 179 were approached, 103 enrolled, 73 received TH, and 64 were included. CMRO2 was measured at the NICU bedside by frequency-domain near-infrared and diffuse correlation spectroscopies (FDNIRS-DCS) during the late phases of hypothermia (C), rewarming (RW) and after return to normothermia (NT). Additional variables were body temperature and clinical neonatal encephalopathy (NE) scores, as well as findings from magnetic resonance imaging (MRI) and spectroscopy (MRS). Primary outcome was the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) at 18 months, normed (SD) to 100 (15). FINDINGS: Data quality for 58 neonates was sufficient for analysis. CMRO2 changed by 14.4% per °C (95% CI, 14.2-14.6) relative to its baseline at NT while cerebral tissue oxygen extraction fraction (cFTOE) changed by only 2.2% per °C (95% CI, 2.1-2.4) for net changes from C to NT of 91% and 8%, respectively. Follow-up data for 2 were incomplete, 33 declined and 1 died, leaving 22 participants (mean [SD] postnatal age, 19.1 [1.2] month; 11 female) with mild to moderate HIE (median [IQR] NE score, 4 [3-6]) and 21 (95%) with BSID-III scores >85 at 18 months. CMRO2 at NT was positively associated with cognitive and motor composite scores (ß (SE) = 4.49 (1.55) and 2.77 (1.00) BSID-III points per 10-10 moL/dl × mm2/s, P = 0.009 and P = 0.01 respectively; linear regression); none of the other measures were associated with the neurodevelopmental outcomes. INTERPRETATION: Point of care measures of CMRO2 in the NICU during C and RW showed dramatic changes and potential to assess individual response to TH. CMRO2 following TH outperformed conventional clinical evaluations (NE score, cFTOE, and MRI/MRS) at predicting cognitive and motor outcomes at 18 months for mild to moderate HIE, providing a promising objective, physiologically-based diagnostic for HIE. FUNDING: This clinical study was funded by an NIH grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, United States (R01HD076258).

Patterns of Neural Functional Connectivity in Infants at Familial Risk of Developmental Dyslexia.

Importance: Developmental dyslexia is a heritable learning disability affecting 7% to 10% of the general population and can have detrimental impacts on mental health and vocational potential. Individuals with dyslexia show altered functional organization of the language and reading neural networks; however, it remains unknown how early in life these neural network alterations might emerge. Objective: To determine whether the early emergence of large-scale neural functional connectivity (FC) underlying long-term language and reading development is altered in infants with a familial history of dyslexia (FHD). Design, Setting, and Participants: This cohort study included infants recruited at Boston Children's Hospital between May 2011 and February 2019. Participants underwent structural and resting-state functional magnetic resonance imaging in the Department of Radiology at Boston Children's Hospital. Infants with FHD were matched with infants without FHD based on age and sex. Data were analyzed from April 2019 to June 2021. Exposures: FHD was defined as having at least 1 first-degree relative with a dyslexia diagnosis or documented reading difficulties. Main Outcomes and Measures: Whole-brain FC patterns associated with 20 predefined cerebral regions important for long-term language and reading development were computed for each infant. Multivariate pattern analyses were applied to identify specific FC patterns that differentiated between infants with vs without FHD. For classification performance estimates, 99% CIs were calculated as the classification accuracy minus chance level. Results: A total of 98 infants (mean [SD] age, 8.5 [2.3] months; 51 [52.0%] girls) were analyzed, including 35 infants with FHD and 63 infants without FHD. Multivariate pattern analyses identified distinct FC patterns between infants with vs without FHD in the left fusiform gyrus (classification accuracy, 0.55 [99% CI, 0.046-0.062]; corrected P < .001; Cohen d = 0.76). Connections linking left fusiform gyrus to regions in the frontal and parietal language and attention networks were among the paths with the highest contributions to the classification performance. Conclusions and Relevance: These findings suggest that on the group level, FHD was associated with an early onset of atypical FC of regions important for subsequent word form recognition during reading acquisition. Longitudinal studies linking the atypical functional network and school-age reading abilities will be essential to further elucidate the ontogenetic mechanisms underlying the development of dyslexia.

Functional Connectivity in Infancy and Toddlerhood Predicts Long-Term Language and Preliteracy Outcomes.

Functional connectivity (FC) techniques can delineate brain organization as early as infancy, enabling the characterization of early brain characteristics associated with subsequent behavioral outcomes. Previous studies have identified specific functional networks in infant brains that underlie cognitive abilities and pathophysiology subsequently observed in toddlers and preschoolers. However, it is unknown whether and how functional networks emerging within the first 18 months of life contribute to the development of higher order, complex functions of language/literacy at school-age. This 5-year longitudinal imaging project starting in infancy, utilized resting-state functional magnetic resonance imaging and demonstrated prospective associations between FC in infants/toddlers and subsequent language and foundational literacy skills at 6.5 years old. These longitudinal associations were shown independently of key environmental influences and further present in a subsample of infant imaging data (≤12 months), suggesting early emerged functional networks specifically linked to high-order language and preliteracy skills. Moreover, emergent language skills in infancy and toddlerhood contributed to the prospective associations, implicating a role of early linguistic experiences in shaping the FC correlates of long-term oral language skills. The current results highlight the importance of functional organization established in infancy and toddlerhood as a neural scaffold underlying the learning process of complex cognitive functions.

Global motion detection and censoring in high-density diffuse optical tomography.

Motion-induced artifacts can significantly corrupt optical neuroimaging, as in most neuroimaging modalities. For high-density diffuse optical tomography (HD-DOT) with hundreds to thousands of source-detector pair measurements, motion detection methods are underdeveloped relative to both functional magnetic resonance imaging (fMRI) and standard functional near-infrared spectroscopy (fNIRS). This limitation restricts the application of HD-DOT in many challenging imaging situations and subject populations (e.g., bedside monitoring and children). Here, we evaluated a new motion detection method for multi-channel optical imaging systems that leverages spatial patterns across measurement channels. Specifically, we introduced a global variance of temporal derivatives (GVTD) metric as a motion detection index. We showed that GVTD strongly correlates with external measures of motion and has high sensitivity and specificity to instructed motion-with an area under the receiver operator characteristic curve of 0.88, calculated based on five different types of instructed motion. Additionally, we showed that applying GVTD-based motion censoring on both hearing words task and resting state HD-DOT data with natural head motion results in an improved spatial similarity to fMRI mapping. We then compared the GVTD similarity scores with several commonly used motion correction methods described in the fNIRS literature, including correlation-based signal improvement (CBSI), temporal derivative distribution repair (TDDR), wavelet filtering, and targeted principal component analysis (tPCA). We find that GVTD motion censoring on HD-DOT data outperforms other methods and results in spatial maps more similar to those of matched fMRI data.

Abnormalities in cerebral hemodynamics and changes with surgical intervention in neonates with congenital heart disease.

OBJECTIVE: To use novel optical techniques to measure perioperative cerebral hemodynamics of diverse congenital heart disease (CHD) groups (two-ventricle, d-transposition of the great arteries [TGA], and single ventricle [SV]) and (1) compare CHD groups with healthy controls preoperatively and (2) compare preoperative and postoperative values within each CHD group. METHODS: Frequency-domain near-infrared spectroscopy and diffuse correlation spectroscopy were used to measure cerebral oxygen saturation, cerebral blood volume, cerebral blood flow index, cerebral oxygen extraction fraction (OEF, calculated using arterial oxygen saturation and cerebral oxygen saturation), and an index of cerebral metabolic rate of oxygen consumption in control and CHD neonates. Preoperative CHD measures were compared with controls. Preoperative and postoperative measures were compared within each CHD group. RESULTS: In total, 31 CHD neonates (7 two-ventricle, 11 TGA, 13 SV) and 13 controls were included. Only neonates with SV CHD displayed significantly lower preoperative cerebral blood flow index (P < .04) than controls. TGA and SV groups displayed greater OEF (P < .05) during the preoperative period compared with controls. Compared with the preoperative state, postoperative neonates with TGA had a greater arterial oxygen saturation with lower OEF. CONCLUSIONS: Differences in cerebral hemodynamics and oxygen metabolism were observed in diverse CHD groups compared with controls. Increased OEF appears to be a compensatory mechanism in neonates with TGA and SV. Studies are needed to understand the relationship of these metrics to outcome and their potential to guide interventions to improve outcome.

System-Specific Patterns of Thalamocortical Connectivity in Early Brain Development as Revealed by Structural and Functional MRI.

The normal development of thalamocortical connections plays a critical role in shaping brain connectivity in the prenatal and postnatal periods. Recent studies using advanced magnetic resonance imaging (MRI) techniques in neonates and infants have shown that abnormal thalamocortical connectivity is associated with adverse neurodevelopmental outcomes. However, all these studies have focused on a single neuroimaging modality, overlooking the dynamic relationship between structure and function at this early stage. Here, we study the relationship between structural and functional thalamocortical connectivity patterns derived from healthy full-term infants scanned with diffusion-weighted MRI and resting-state functional MRI within the first weeks of life (mean gestational age = 39.3 ± 1.2 weeks; age at scan = 24.2 ± 7.9 days). Our results show that while there is, in general, good spatial agreement between both MRI modalities, there are regional variations that are system-specific: regions involving primary-sensory cortices exhibit greater structural/functional overlap, whereas higher-order association areas such as temporal and posterior parietal cortices show divergence in spatial patterns of each modality. This variability illustrates the complementarity of both modalities and highlights the importance of multimodal approaches.

Exploring early human brain development with structural and physiological neuroimaging.

Early brain development, from the embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and the important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI. Next, we discuss the basic biology of neuronal circuitry development (synaptic connectivity, i.e. ensemble of direct chemical and electrical connections between neurons), physiology of neurovascular coupling, baseline metabolic needs of the fetus and the infant, and functional connectivity (defined as statistical dependence of low-frequency spontaneous fluctuations seen with functional magnetic resonance imaging (fMRI)). The complementary roles of magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS) are discussed. We include a section on modulators of brain development where we focus on the placenta and emerging placental MRI approaches. In each section we discuss key technical limitations of the imaging modalities and some of the limitations arising due to the biology of the system. Although neuroimaging approaches have contributed significantly to our understanding of early brain development, there is much yet to be done and a dire need for technical innovations and scientific discoveries to realize the future potential of early fetal and infant interventions to avert long term disease.

Lightweight sCMOS-based high-density diffuse optical tomography.

Though optical imaging of human brain function is gaining momentum, widespread adoption is restricted in part by a tradeoff among cap wearability, field of view, and resolution. To increase coverage while maintaining functional magnetic resonance imaging (fMRI)-comparable image quality, optical systems require more fibers. However, these modifications drastically reduce the wearability of the imaging cap. The primary obstacle to optimizing wearability is cap weight, which is largely determined by fiber diameter. Smaller fibers collect less light and lead to challenges in obtaining adequate signal-to-noise ratio. Here, we report on a design that leverages the exquisite sensitivity of scientific CMOS cameras to use fibers with ∼30× smaller cross-sectional area than current high-density diffuse optical tomography (HD-DOT) systems. This superpixel sCMOS DOT (SP-DOT) system uses 200-µm -diameter fibers that facilitate a lightweight, wearable cap. We developed a superpixel algorithm with pixel binning and electronic noise subtraction to provide high dynamic range ( >105 ), high frame rate ( >6 Hz ), and a low effective detectivity threshold ( ∼200 fW/Hz1/2-mm2 ), each comparable with previous HD-DOT systems. To assess system performance, we present retinotopic mapping of the visual cortex ( n=5 subjects). SP-DOT offers a practical solution to providing a wearable, large field-of-view, and high-resolution optical neuroimaging system.

Probabilistic tractography-based thalamic parcellation in healthy newborns and newborns with congenital heart disease.

BACKGROUND: Given the central role of the thalamus in motor, sensory, and cognitive development, methods to study emerging thalamocortical connectivity in early infancy are of great interest. PURPOSE: To determine the feasibility of performing probabilistic tractography-based thalamic parcellation (PTbTP) in typically developing (TD) neonates and to compare the results with a pilot sample of neonates with congenital heart disease (CHD). STUDY TYPE: Institutional Review Board (IRB)-approved cross-sectional study. MODEL: We prospectively recruited 20 TD neonates and five CHD neonates (imaged preoperatively). FIELD STRENGTH/SEQUENCE: MRI was performed at 3.0T including diffusion-weighted imaging (DWI) and 3D magnetization prepared rapid gradient-echo (MPRAGE). ASSESSMENT: A radiologist and trained research assistants segmented the thalamus and seven cortical targets for each hemisphere. Using the thalami as seeds and the cortical labels as targets, FSL library tools were used to generate probabilistic tracts. A Hierarchical Dirichlet Process algorithm was then used for clustering analysis. A radiologist qualitatively assessed the results of clustering. Quantitative analyses were also performed. STATISTICAL TESTS: We summarized the demographic data and results of clustering with descriptive statistics. Linear regressions covarying for gestational age were used to compare groups. RESULTS: In 17 of 20 TD neonates, we identified five connectivity-determined clusters, which correlate with known thalamic nuclei and subnuclei. In four neonates with CHD we observed a spectrum of abnormalities including fewer and disorganized clusters or small supernumerary clusters (up to seven per thalamus). After covarying for differences in corrected gestational age (cGA), the fractional anisotropy (FA), volume, and normalized thalamic volume were significantly lower in CHD neonates (P < 0.01). DATA CONCLUSIONS: Using PTbTP clusters, correlating well with the location and connectivity of known thalamic nuclei, were identified in TD neonates. Differences in thalamic clustering outputs were identified in four neonates with CHD, raising concern for disordered thalamic connectivity. PTbTP is feasible in TD and CHD neonates. Preliminary findings suggest the prenatal origins of altered connectivity in CHD. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;47:1626-1637.

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.

Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography.

While histological studies and conventional magnetic resonance imaging (MRI) investigations have elucidated the trajectory of structural changes in the developing brain, less is known regarding early functional cerebral development. Recent investigations have demonstrated that resting-state functional connectivity MRI (fcMRI) can identify networks of functional cerebral connections in infants. However, technical and logistical challenges frequently limit the ability to perform MRI scans early or repeatedly in neonates, particularly in those at greatest risk for adverse neurodevelopmental outcomes. High-density diffuse optical tomography (HD-DOT), a portable imaging modality, potentially enables early continuous and quantitative monitoring of brain function in infants. We introduce an HD-DOT imaging system that combines advancements in cap design, ergonomics, and data analysis methods to allow bedside mapping of functional brain development in infants. In a cohort of healthy, full-term neonates scanned within the first days of life, HD-DOT results demonstrate strong congruence with those obtained using co-registered, subject-matched fcMRI and reflect patterns of typical brain development. These findings represent a transformative advance in functional neuroimaging in infants, and introduce HD-DOT as a powerful and practical method for quantitative mapping of early functional brain development in normal and high-risk neonates.

Perioperative cerebral hemodynamics and oxygen metabolism in neonates with single-ventricle physiology.

Congenital heart disease (CHD) patients are at risk for neurodevelopmental delay. The etiology of these delays is unclear, but abnormal prenatal cerebral maturation and postoperative hemodynamic instability likely play a role. A better understanding of these factors is needed to improve neurodevelopmental outcome. In this study, we used bedside frequency-domain near infrared spectroscopy (FDNIRS) and diffuse correlation spectroscopy (DCS) to assess cerebral hemodynamics and oxygen metabolism in neonates with single-ventricle (SV) CHD undergoing surgery and compared them to controls. Our goals were 1) to compare cerebral hemodynamics between unanesthetized SV and healthy neonates, and 2) to determine if FDNIRS-DCS could detect alterations in cerebral hemodynamics beyond cerebral hemoglobin oxygen saturation (SO 2). Eleven SV neonates were recruited and compared to 13 controls. Preoperatively, SV patients showed decreased cerebral blood flow (CBFi ), cerebral oxygen metabolism (CMRO 2i ) and SO 2; and increased oxygen extraction fraction (OEF) compared to controls. Compared to preoperative values, unstable postoperative SV patients had decreased CMRO 2i and CBFi , which returned to baseline when stable. However, SO 2 showed no difference between unstable and stable states. Preoperative SV neonates are flow-limited and show signs of impaired cerebral development compared to controls. FDNIRS-DCS shows potential to improve assessment of cerebral development and postoperative hemodynamics compared to SO 2 alone.

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.

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 high-density 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.

Mapping distributed brain function and networks with diffuse optical tomography.

Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available.

Statistical analysis of high density diffuse optical tomography.

High density diffuse optical tomography (HD-DOT) is a noninvasive neuroimaging modality with moderate spatial resolution and localization accuracy. Due to portability and wear-ability advantages, HD-DOT has the potential to be used in populations that are not amenable to functional magnetic resonance imaging (fMRI), such as hospitalized patients and young children. However, whereas the use of event-related stimuli designs, general linear model (GLM) analysis, and imaging statistics are standardized and routine with fMRI, such tools are not yet common practice in HD-DOT. In this paper we adapt and optimize fundamental elements of fMRI analysis for application to HD-DOT. We show the use of event-related protocols and GLM de-convolution analysis in un-mixing multi-stimuli event-related HD-DOT data. Statistical parametric mapping (SPM) in the framework of a general linear model is developed considering the temporal and spatial characteristics of HD-DOT data. The statistical analysis utilizes a random field noise model that incorporates estimates of the local temporal and spatial correlations of the GLM residuals. The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory. These analysis tools provide access to a wide range of experimental designs necessary for the study of the complex brain functions. In addition, they provide a foundation for understanding and interpreting HD-DOT results with quantitative estimates for the statistical significance of detected activation foci.

High-density diffuse optical tomography of term infant visual cortex in the nursery.

Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.

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+/-1mm, 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.