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Abstract The classical amyloid cascade hypothesis postulates that the aggregation of amyloid plaques and the accumulation of intracellular hyperphosphorylated Tau tangles, together, lead to profound neuronal death. However, emerging research has demonstrated that soluble amyloid-β oligomers (SAβOs) accumulate early, prior to amyloid plaque formation. SAβOs induce memory impairment and disrupt cognitive function independent of amyloid-β plaques, and even in the absence of plaque formation. This work describes the development and characterization of a novel anti-SAβO (E3) nanobody generated from an alpaca immunized with SAβO. In-vitro assays and in-vivo studies using 5XFAD mice indicate that the fluorescein (FAM)-labeled E3 nanobody recognizes both SAβOs and amyloid-β plaques. The E3 nanobody traverses across the blood–brain barrier and binds to amyloid species in the brain of 5XFAD mice. Imaging of mouse brains reveals that SAβO and amyloid-β plaques are not only different in size, shape, and morphology, but also have a distinct spatial distribution in the brain. SAβOs are associated with neurons, while amyloid plaques reside in the extracellular matrix. The results of this study demonstrate that the SAβO nanobody can serve as a diagnostic agent with potential theragnostic applications in Alzheimer’s disease.

Abstract Functional MRI (fMRI) of the spinal cord is an expanding area of research with potential to investigate neuronal activity in the central nervous system. We aimed to characterize the functional connectivity features of the human lumbar spinal cord using resting-state fMRI (rs-fMRI) at 3T, using region-based and data-driven analysis approaches. A 3D multi-shot gradient echo resting-state blood oxygenation level dependent-sensitive rs-fMRI protocol was implemented in 26 healthy participants. Average temporal signal-to-noise ratio in the gray matter was 16.35 ± 4.79 after denoising. Evidence of synchronous signal fluctuations in the ventral and dorsal horns with their contralateral counterparts was observed in representative participants using interactive, exploratory seed-based correlations. Group-wise average in-slice Pearson’s correlations were 0.43 ± 0.17 between ventral horns, and 0.48 ± 0.16 between dorsal horns. Group spatial independent component analysis (ICA) was used to identify areas of coherent activity¸ and revealed components within the gray matter corresponding to anatomical regions. Lower-dimensionality ICA revealed bilateral components corresponding to ventral and dorsal networks. Additional separate ICAs were run on two subsets of the participant group, yielding two sets of components that showed visual consistency and moderate spatial overlap. This work shows feasibility of rs-fMRI to probe the functional features and organization of the lumbar spinal cord.

Abstract Seasonal variations have long been observed in various aspects of human life. While there is an abundance of research that has characterized seasonality effects in, for example, cognition, mood, and behavior, including studies of underlying biophysical mechanisms, direct measurements of seasonal variations of brain functional activities have not gained wide attention. We have quantified seasonal effects on functional connectivity as derived from MRI scans. A cohort of healthy human subjects was divided into four groups based on the seasons of their scanning dates as documented in the image database of the Human Connectome Project. Sinusoidal functions were used as regressors to determine whether there were significant seasonal variations in measures of brain activities. We began with the analysis of seasonal variations of the fractional amplitudes of low frequency fluctuations of regional functional signals, followed by the seasonal variations of functional connectivity in both global- and network-level. Furthermore, relevant environmental factors, including average temperature and daylength, were found to be significantly associated with brain functional activities, which may explain how the observed seasonal fluctuations arise. Finally, topological properties of the brain functional network also showed significant variations across seasons. All the observations accumulated revealed seasonality effects of human brain activities in a resting-state, which may have important practical implications for neuroimaging research.

Background: MRI-guided transcranial focused ultrasound (MRgFUS) as a next-generation neuromodulation tool can precisely target and stimulate deep brain regions with high spatial selectivity. Combined with MR-ARFI (acoustic radiation force imaging) and using fMRI BOLD signal as functional readouts, our previous studies have shown that low-intensity FUS can excite or suppress neural activity in the somatosensory cortex. Objective: To investigate whether low-intensity FUS can suppress nociceptive heat stimulation-induced responses in thalamic nuclei during hand stimulation, and to determine how this suppression influences the information processing flow within nociception networks. Findings: BOLD fMRI activations evoked by 47.5 °C heat stimulation of hand were detected in 24 cortical regions, which belong to sensory, affective, and cognitive nociceptive networks. Concurrent delivery of low-intensity FUS pulses (650 kHz, 550 kPa) to the predefined heat nociceptive stimulus-responsive thalamic centromedial_parafascicular (CM_para), mediodorsal (MD), ventral_lateral (VL_ and ventral_lateral_posteroventral (VLpv) nuclei suppressed their heat responses. Off-target cortical areas exhibited reduced, enhanced, or no significant fMRI signal changes, depending on the specific areas. Differentiable thalamocortical information flow during the processing of nociceptive heat input was observed, as indicated by the time to reach 10% or 30% of the heat-evoked BOLD signal peak. Suppression of thalamic heat responses significantly altered nociceptive processing flow and direction between the thalamus and cortical areas. Modulation of contralateral versus ipsilateral areas by unilateral thalamic activity differed. Signals detected in high-order cortical areas, such as dorsal frontal (DFC) and ventrolateral prefrontal (vlPFC) cortices, exhibited faster response latencies than sensory areas. Conclusions: The concurrent delivery of FUS suppressed nociceptive heat response in thalamic nuclei and disrupted the nociceptive network. This study offers new insights into the causal functional connections within the thalamocortical networks and demonstrates the modulatory effects of low-intensity FUS on nociceptive information processing.

Abstract Background It has been shown that tumor microenvironment (TME) hydroxyapatite (HAP) is typically associated with many malignancies and plays a role in tumor progression and growth. Additionally, acidosis in the TME has been reported to play a key role in selecting for a more aggressive tumor phenotype, drug resistance and desensitization to immunotherapy for many types of cancers. TME‐HAP is an attractive target for tumor detection and treatment development since HAP is generally absent from normal soft tissue. We provide strong evidence that dissolution of hydroxyapatite (HAP) within the tumor microenvironment (TME‐HAP) using a novel therapeutic can be used to kill cancer cells both in vitro and in vivo with minimal adverse effects. Methods We developed an injectable cation exchange nano particulate sulfonated polystyrene solution (NSPS) that we engineered to dissolve TME‐HAP, inducing localized acute alkalosis and inhibition of tumor growth and glucose metabolism. This was evaluated in cell culture using 4T1, MDA‐MB‐231 triple negative breast cancer cells, MCF10 normal breast cells, and H292 lung cancer cells, and in vivo using orthotopic mouse models of cancer that contained detectable microenvironment HAP including breast (MMTV‐Neu, 4T1, and MDA‐MB‐231), prostate (PC3) and colon (HCA7) cancer using 18F‐NaF for HAP and 18F‐FDG for glucose metabolism with PET imaging. On the other hand, H292 lung tumor cells that lacked detectable microenvironment HAP and MCF10a normal breast cells that do not produce HAP served as negative controls. Tumor microenvironment pH levels following injection of NSPS were evaluated via Chemical Exchange Saturation (CEST) MRI and via ex vivo methods. Results Within 24 h of adding the small concentration of 1X of NSPS (~7 μM), we observed significant tumor cell death (~ 10%, p

The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22–96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

We have previously shown that focused ultrasound (FUS) pulses in low pressure range exerted bidirectional and brain state-dependent neuromodulation in the nonhuman primate somatosensory cortices by fMRI. Here we aim to gain insights about the proposed neuron selective modulation of FUS and probe feedforward versus feedback interactions by simultaneously quantifying the stimulus (FUS pressures: 925, 425, 250 kPa) and response (% BOLD fMRI changes) function at the targeted area 3a/3b and off-target cortical areas at 7T. In resting-state, lowered intensities of FUS resulted in decreased fMRI signal changes at the target area 3a/3b and off-target area 1/2, S2, MCC, insula and auditory cortex, and no signal difference in thalamic VPL and MD nuclei. In activated states, concurrent high-intensity FUS significantly enhanced touch-evoked signals in area 1/2. Medium- and low-intensity FUS significantly suppressed touch-evoked BOLD signals in all areas except in the auditory cortex, VPL and MD thalamic nuclei. Distinct state dependent and dose-response curves led us to hypothesize that FUS's neuromodulatory effects may be mediated through preferential activation of different populations of neurons. Area 3a/3b may have distinct causal feedforward and feedback interactions with Area 1/2, S2, MCC, insula, and VPL. FUS offers a noninvasive neural stimulation tool for dissecting brain circuits and probing causal functional connections.

IntroductionThe aging brain is characterized by decreases in not only neuronal density but also reductions in myelinated white matter (WM) fibers that provide the essential foundation for communication between cortical regions. Age-related degeneration of WM has been previously characterized by histopathology as well as T2 FLAIR and diffusion MRI. Recent studies have consistently shown that BOLD (blood oxygenation level dependent) effects in WM are robustly detectable, are modulated by neural activities, and thus represent a complementary window into the functional organization of the brain. However, there have been no previous systematic studies of whether or how WM BOLD signals vary with normal aging. We therefore performed a comprehensive quantification of WM BOLD signals across scales to evaluate their potential as indicators of functional changes that arise with aging.MethodsBy using spatial independent component analysis (ICA) of BOLD signals acquired in a resting state, WM voxels were grouped into spatially distinct functional units. The functional connectivities (FCs) within and among those units were measured and their relationships with aging were assessed. On a larger spatial scale, a graph was reconstructed based on the pair-wise connectivities among units, modeling the WM as a complex network and producing a set of graph-theoretical metrics.ResultsThe spectral powers that reflect the intensities of BOLD signals were found to be significantly affected by aging across more than half of the WM units. The functional connectivities (FCs) within and among those units were found to decrease significantly with aging. We observed a widespread reduction of graph-theoretical metrics, suggesting a decrease in the ability to exchange information between remote WM regions with aging.DiscussionOur findings converge to support the notion that WM BOLD signals in specific regions, and their interactions with other regions, have the potential to serve as imaging markers of aging.

Much previous neuroimaging research in Alzheimer’s disease has focused on the roles of amyloid and tau proteins, but recent studies have implicated microvascular changes in white matter as early indicators of damage related to later dementia. We used MRI to derive novel, non-invasive measurements of R1ρ dispersion using different locking fields to characterize variations of microvascular structure and integrity in brain tissues. We developed a non-invasive 3D R1ρ dispersion imaging technique using different locking fields at 3T. We acquired MR images and cognitive assessments of participants with mild cognitive impairment (MCI) and compared them to age-matched healthy controls in a cross-sectional study. After providing informed consent, 40 adults aged 62 to 82 years (n = 17 MCI) were included in this study. White matter ΔR1ρ-fraction measured by R1ρ dispersion imaging showed a strong correlation with the cognitive status of older adults (βstd = −0.4, p-value

A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by convolving the time course of the expected neural activity with a canonical hemodynamic response function (HRF) obtained a priori. The maps of brain activity produced reflect the magnitude of local BOLD responses. However, detecting BOLD signals in white matter (WM) is more challenging as the BOLD signals are weaker and the HRF is different, and may vary more across the brain. Here we propose a model-free approach to detect changes in BOLD signals in WM by measuring task-evoked increases of BOLD signal synchrony in WM fibers. The proposed approach relies on a simple assumption that, in response to a functional task, BOLD signals in relevant fibers are modulated by stimulus-evoked neural activity and thereby show greater synchrony than when measured in a resting state, even if their magnitudes do not change substantially. This approach is implemented in two technical stages. First, for each voxel a fiber-architecture-informed spatial window is created with orientation distribution functions constructed from diffusion imaging data. This provides the basis for defining neighborhoods in WM that share similar local fiber architectures. Second, a modified principal component analysis (PCA) is used to estimate the synchrony of BOLD signals in each spatial window. The proposed approach is validated using a 3T fMRI dataset from the Human Connectome Project (HCP) at a group level. The results demonstrate that neural activity can be reliably detected as increases in fMRI signal synchrony within WM fibers that are engaged in a task with high sensitivities and reproducibility.

Transcranial focused ultrasound (FUS) stimulation under MRI guidance, coupled with functional MRI (fMRI) monitoring of effects, offers a precise, noninvasive technology to dissect functional brain circuits and to modulate altered brain functional networks in neurological and psychiatric disorders. Here we show that ultrasound at moderate intensities modulated neural activity bi-directionally. Concurrent sonication of somatosensory areas 3a/3b with 250 kHz FUS suppressed the fMRI signals produced there by peripheral tactile stimulation, while at the same time eliciting fMRI activation at inter-connected, off-target brain regions. Direct FUS stimulation of the cortex resulted in different degrees of BOLD signal changes across all five off-target regions, indicating that its modulatory effects on active and resting neurons differed. This is the first demonstration of the dual suppressive and excitative modulations of FUS on a specific functional circuit and of ability of concurrent FUS and MRI to evaluate causal interactions between functional circuits with neuron-class selectivity.

Recent studies have demonstrated that the mathematical model used for analyzing and interpreting fMRI data in gray matter (GM) is inappropriate for detecting or describing blood-oxygenation-level-dependent (BOLD) signals in white matter (WM). In particular the hemodynamic response function (HRF) which serves as the regressor in general linear models is different in WM compared to GM. We recently reported measurements of the frequency contents of resting-state signal time courses in WM that showed distinct power spectra which depended on local structural-vascular-functional associations. In addition, multiple studies of GM have revealed how functional connectivity between regions, as measured by the correlation between BOLD time series, varies dynamically over time. We therefore investigated whether and how BOLD signals from WM in a resting state varied over time. We measured voxel-wise spectrograms, which reflect the time-varying spectral patterns of WM time courses. The results suggest that the spectral patterns are non-stationary but could be categorized into five modes that recurred over time. These modes showed distinct spatial distributions of their occurrences and durations, and the distributions were highly consistent across individuals. In addition, one of the modes exhibited a strong coupling of its occurrence between GM and WM across individuals, and two communities of WM voxels were identified according to the hierarchical structures of transitions among modes. Moreover, these modes are coupled to the shape of instantaneous HRFs. Our findings extend previous studies and reveal the non-stationary nature of spectral patterns of BOLD signals over time, providing a spatial-temporal-frequency characterization of resting-state signals in WM.

Focal lesions may affect functional connectivity (FC) of the ventral and dorsal networks in the cervical spinal cord of people with relapsing-remitting multiple sclerosis (RRMS). Resting-state FC can be measured using functional MRI (fMRI) at 3T. This study sought to determine whether alterations in FC may be related to the degree of damage in the normal-appearing tissue. Tissue integrity and FC in the cervical spinal cord were assessed with diffusion tensor imaging (DTI) and resting-state fMRI, respectively, in a group of 26 RRMS participants with high cervical lesion load, low disability, and minimally impaired sensorimotor function, and healthy controls. Lower fractional anisotropy (FA) and higher radial diffusivity (RD) were observed in the normal-appearing white matter in the RRMS group relative to controls. Average FC in ventral and dorsal networks was similar between groups. Significant associations were found between higher FC in the dorsal sensory network and several DTI markers of pathology in the normal-appearing tissue. In the normal-appearing grey matter, dorsal FC was positively correlated with axial diffusivity (AD) (r = 0.46, p = 0.020) and mean diffusivity (MD) (r = 0.43, p = 0.032). In the normal-appearing white matter, dorsal FC was negatively correlated with FA (r = −0.43, p = 0.028) and positively correlated with RD (r = 0.49, p = 0.012), AD (r = 0.42, p = 0.037) and MD (r = 0.53, p = 0.006). These results suggest that increased connectivity, while remaining within the normal range, may represent a compensatory mechanism in response to structural damage in support of preserved sensory function in RRMS.

Summary: Evidence for prefrontal cortical (PFC) GABAergic dysfunction is one of the most consistent findings in schizophrenia and may contribute to cognitive deficits. Recent studies suggest that the mGlu1 subtype of metabotropic glutamate receptor regulates cortical inhibition; however, understanding the mechanisms through which mGlu1 positive allosteric modulators (PAMs) regulate PFC microcircuit function and cognition is essential for advancing these potential therapeutics toward the clinic. We report a series of electrophysiology, optogenetic, pharmacological magnetic resonance imaging, and animal behavior studies demonstrating that activation of mGlu1 receptors increases inhibitory transmission in the prelimbic PFC by selective excitation of somatostatin-expressing interneurons (SST-INs). An mGlu1 PAM reverses cortical hyperactivity and concomitant cognitive deficits induced by N-methyl-d-aspartate (NMDA) receptor antagonists. Using in vivo optogenetics, we show that prelimbic SST-INs are necessary for mGlu1 PAM efficacy. Collectively, these findings suggest that mGlu1 PAMs could reverse cortical GABAergic deficits and exhibit efficacy in treating cognitive dysfunction in schizophrenia.

Spontaneous fluctuations of Blood Oxygenation-Level Dependent (BOLD) MRI signal in a resting state have previously been detected and analyzed to describe intrinsic functional networks in the spinal cord of rodents, non-human primates and human subjects. In this study we combined high resolution imaging at high field with data-driven Independent Component Analysis (ICA) to i) delineate fine-scale functional networks within and between segments of the cervical spinal cord of monkeys, and also to ii) characterize the longitudinal effects of a unilateral dorsal column injury on these networks. Seven distinct functional hubs were revealed within each spinal segment, with new hubs detected at bilateral intermediate and gray commissure regions in addition to the bilateral dorsal and ventral horns previously reported. Pair-wise correlations revealed significantly stronger connections between hubs on the dominant hand side. Unilateral dorsal-column injuries disrupted predominantly inter-segmental rather than intra-segmental functional connectivities as revealed by correlation strengths and graph-theory based community structures. The effects of injury on inter-segmental connectivity were evident along the length of the cord both below and above the lesion region. Connectivity strengths recovered over time and there was revival of inter-segmental communities as animals recovered function. BOLD signals of frequency 0.01–0.033 Hz were found to be most affected by injury. The results in this study provide new insights into the intrinsic functional architecture of spinal cord and underscore the potential of functional connectivity measures to characterize changes in networks after an injury and during recovery.

Purpose: This study aims to test the ability of quantitative temporal diffusion spectroscopy (qTDS) to assess cellular changes associated with radiation-induced cell death in a rat glioma model. Methods and Materials: Tumor response to a single fraction of 20 Gy of x-ray radiation was investigated in a rat glioma (9L) model. Tumor response was monitored longitudinally at postinoculation days 21, 23, and 25, using a specific implementation of qTDS with acronym IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion), as well as conventional diffusion and high-resolution anatomic imaging. IMPULSED method combines diffusion-weighted signals acquired over a range of diffusion times that are then analyzed and interpreted using a theoretical model of water diffusion in tissues, which generates parametric maps depicting cellular and subcellular structural information on a voxel-wise basis. Results from different metrics were compared statistically. Results: A single dose of 20 Gy x-ray radiation significantly prolonged survival of 9L-bearing rats. The mean cell sizes of irradiated tumors decreased (P

The hemodynamic response function (HRF) describes how changes in brain activity manifest as a transient signal (BOLD) that is detected by fMRI imaging. Here, the authors show that the HRF in white matter shows reduced magnitudes, delayed onsets, and prolonged initial dips compared to the grey matter HRF.

Resting-state fMRI shows networks of correlated activity in the spinal cord, similar to those in the brain, but whether fMRI is a valid measure of functional connectivity in spinal cord is unclear. Here, the authors show that fMRI corresponds well to electrophysiological measures of spinal cord activity.

Purpose: The sensitivity and accuracy of chemical exchange saturation transfer (CEST) and nuclear Overhauser enhancement (NOE) effects for assessing injury-associated changes in cervical spinal cords were evaluated in squirrel monkeys. Multiple interacting pools of protons, including one identified by an NOE at −1.6 ppm relative to water (NOE(-1.6)), were derived and quantified from fitting proton Z-spectra. The effects of down-sampled data acquisitions and corrections for non-specific factors including T1, semi-solid magnetization transfer, and direct saturation of free water (DS), were investigated. The overall goal is to develop a protocol for rapid data acquisition for assessing the molecular signatures of the injured spinal cord and its surrounding regions. Methods: MRI scans were recorded of anesthetized squirrel monkeys at 9.4 T, before and after a unilateral dorsal column sectioning of the cervical spinal cord. Z-spectral images at 51 different RF offsets were acquired. The amplitudes of CEST and NOE effects from multiple proton pools were quantified using a six-pool Lorenzian fitting of each Z-spectrum (MTRmfit). In addition, down-sampled data using reduced selections of RF offsets were analyzed and compared. An apparent exchange-dependent relaxation (AREXmfit) method was also used to correct for non-specific factors in quantifying regional spectra around lesion sites. Results: The parametric maps from multi-pool fitting using the complete sampling data (P51e) detected unilateral changes at and around the injury. The maps derived from selected twofold down-sampled data with appropriate interpolation (P26sI51) revealed quite similar spatial distributions of different pools as those obtained using P51e at each resonance shift. Across 10 subjects, both data acquisition schemes detected significant decreases in NOE(-3.5) and NOE(-1.6) and increases in DS(0.0) and CEST(3.5) at the lesion site relative to measures of the normal tissues before injury. AREXmfit of cysts and other abnormal tissues at and around the lesion site also exhibited significant changes, especially at 3.5, −1.6 and −3.5 ppm RF offsets. Conclusion: These results confirm that a reduced set of RF offsets and down sampling are adequate for CEST imaging of injured spinal cord and allow shorter imaging times and/or permit additional signal averaging. AREXmfit correction improved the accuracy of CEST and NOE measures. The results provide a rapid (~13 mins), sensitive, and accurate protocol for deriving multiple NOE and CEST effects simultaneously in spinal cord imaging at high field.

Spontaneous fluctuations in MRI signals from gray matter (GM) in the brain are interpreted as originating from variations in neural activity, and their inter-regional correlations may be analyzed to reveal functional connectivity. However, most studies of intrinsic neuronal activity have ignored the spontaneous fluctuations that also arise in white matter (WM). In this work, we explore spontaneous fluctuations in resting state MRI signals in WM based on spatial independent component analyses (ICA), a data-driven approach that separates signals into independent sources without making specific modeling assumptions. ICA has become widely accepted as a valuable approach for identifying functional connectivity within cortex but has been rarely applied to derive equivalent structures within WM. Here, BOLD signal changes in WM of a group of subjects performing motor tasks were first detected using ICA, and a spatial component whose time course was consistent with the task was found, demonstrating the analysis is sensitive to evoked BOLD signals in WM. Secondly, multiple spatial components were derived by applying ICA to identify those voxels in WM whose MRI signals showed similar temporal behaviors in a resting state. These functionally-related structures are grossly symmetric and coincide with corresponding tracts identified from diffusion MRI. Finally, functional connectivity was quantified by calculating correlations between pairs of structures to explore the synchronicity of resting state BOLD signals across WM regions, and the experimental results revealed that there exist two distinct groupings of functional correlations in WM tracts at rest. Our study provides further insights into the nature of activation patterns, functional responses and connectivity in WM, and support previous suggestions that BOLD signals in WM show similarities with cortical activations and are characterized by distinct underlying structures in tasks and at rest.

The topological characteristics of functional networks, derived from measurements of resting-state connectivity in gray matter (GM), are associated with individual cognitive abilities or specific dysfunctions. However, blood oxygen level-dependent (BOLD) signals in white matter (WM) are usually ignored or even regressed out as nuisance factors in the data analyses that underlie network models. Recent studies have demonstrated reliable detection of WM BOLD signals and imply these reflect associated neural activities. Here we evaluate quantitatively the contributions of individual WM voxels to the identification of functional networks, which we term their engagement (or conceptually, their importance). We quantify the engagement by measuring the reductions of connectivity, produced by ignoring the signal fluctuations within each WM voxel, with respect to both the entire network (global) or a single GM node (local). We observed highly reproducible spatial distributions of global engagement maps, as well as a trend toward increased relevance of deep WM voxels at delayed times. Local engagement maps exhibit homogeneous spatial distributions with respect to internal nodes that constitute a well-recognized sub-functional network, but inhomogeneous distributions with respect to other nodes. WM voxels show distinct distributions of engagement depending on their anatomical locations. These findings demonstrate the important role of WM in network modeling, thus supporting the need for changes of conventional views that WM signal variations represent only physiological noise.

In response to a flickering visual stimulus, the BOLD response in primary visual cortex varies with the flickering frequency and is maximal when it is close to 8Hz. In previous studies we demonstrated that BOLD signals in specific white matter (WM) pathways covary with the alternations between stimulus conditions in a block design in similar manner to gray matter (GM) regions. Here we investigated whether WM tracts show varying responses to changes in flicker frequency and are modulated in the same manner as cortical areas. We used a Fourier analysis of BOLD signals to measure the signal amplitude and phase at the fundamental frequency of a block-design task in which flickering visual stimuli alternated with blank presentations, avoiding the assumption of any specific hemodynamic response function. The BOLD responses in WM pathways and the primary visual cortex were evaluated for flicker frequencies varying between 2 and 14Hz. The variations with frequency of BOLD signals in specific WM tracts followed closely those in primary visual cortex, suggesting that variations in cortical activation are directly coupled to corresponding BOLD signals in connected WM tracts. Statistically significant differences in the timings of BOLD responses were also measured between visual cortex and specific WM bundles. These results confirm that when cortical BOLD responses are modulated by selecting different task parameters, relevant WM tracts exhibit corresponding BOLD signals that are also affected.

Conventional coil arrays require complex decoupling technologies to reduce electromagnetic coupling between coil elements. Here, the authors report a self-decoupled RF coil design that achieves high inter-coil isolation between adjacent and non-adjacent elements and mixed arrays of loops and dipoles

Purpose: This study aims to systematically evaluate the accuracy and precision of pool size ratio (PSR) measurements from quantitative magnetization transfer (qMT) acquisitions using simplified models in the context of assessing injury-associated spatiotemporal changes in spinal cords of non-human primates. This study also aims to characterize changes in the spinal tissue pathology in individual subjects, both regionally and longitudinally, in order to demonstrate the relationship between regional tissue compositional changes and sensorimotor behavioral recovery after cervical spinal cord injury (SCI). Methods: MRI scans were recorded on anesthetized monkeys at 9.4 T, before and serially after a unilateral section of the dorsal column tract. Images were acquired following saturating RF pulses at different offset frequencies. Models incorporating two pools of protons but with differing numbers of variable parameters were used to fit the data to derive qMT parameters. The results using different amounts of measured data and assuming different numbers of variable model parameters were compared. Behavioral impairments and recovery were assessed by a food grasping-retrieving task. Histological sections were obtained post mortem for validation of the injury. Results: QMT fitting provided maps of pool size ratio (PSR), the relative amounts of immobilized protons exchanging magnetization compared to the “free” water. All the selected modeling approaches detected a lesion/cyst at the site of injury as significant reductions in PSR values. The regional contrasts in the PSR maps obtained using the different fittings varied, but the 2-parameter fitting results showed strong positive correlations with results from 5-parameter modeling. 2-parameter fitting results with modest (>3) RF offsets showed comparable sensitivity for detecting demyelination in white matter and loss of macromolecules in gray matter around lesion sites compared to 5-parameter fitting with fully-sampled data acquisitions. Histology confirmed that decreases of PSR corresponded to regional demyelination around lesion sites, especially when demyelination occurred along the dorsal column on the injury side. Longitudinally, PSR values of injured dorsal column tract and gray matter horns exhibited remarkable recovery that associated with behavioral improvement. Conclusion: Simplified qMT modeling approaches provide efficient and sensitive means to detect and characterize injury-associated demyelination in white matter tracts and loss of macromolecules in gray matter and to monitor its recovery over time. Keywords: MRI, Quantitative magnetization transfer (qMT), Pool size ratio (PSR), Spinal cord injury, Demyelination, Recovery

PURPOSE: A novel quantitative magnetic resonance imaging (MRI) method, namely, temporal diffusion spectroscopy (TDS), was used to detect the response of tumor cells (notably, mitotic arrest) to a specific antimitotic treatment (Nab-paclitaxel) in culture and human ovarian xenografts and evaluated as an early imaging biomarker of tumor responsiveness. METHODS: TDS measures a series of apparent diffusion coefficients (ADCs) of tissue water over a range of effective diffusion times, which may correspond to diffusion distances ranging from subcellular to cellular levels (~3-20 μm). By fitting the measured ADC data to a tissue model, parameters reflecting structural properties such as restriction size in solid tumors can be extracted. Two types of human ovarian cell lines (OVCAR-8 as a responder to Nab-paclitaxel and NCI/ADR-RES as a resistant type) were treated with either vehicle (PBS) or Nab-paclitaxel, and treatment responses of both in vitro and in vivo cases were investigated using TDS. RESULTS: Acute cell size increases induced by Nab-paclitaxel in responding tumors were confirmed by flow cytometry and light microscopy in cell culture. Nab-paclitaxel–induced mitotic arrest in treated tumors/cells was quantified histologically by measuring the mitotic index in vivo using a mitosis-specific marker (anti-phosphohistone H3). Changes in the fitted restriction size, one of the parameters obtained from TDS, were able to detect and quantify increases in tumor cell sizes. All the MR results had a high degree of consistency with other flow, microscopy, and histological data. Moreover, with an appropriate analysis, the Nab-paclitaxel–responsive tumors in vivo could be easily distinguished from all the other vehicle-treated and Nab-paclitaxel–resistant tumors. CONCLUSION: TDS detects increases in cell sizes associated with antimitotic-therapy–induced mitotic arrest in solid tumors in vivo which occur before changes in tissue cellularity or conventional diffusion MRI metrics. By quantifying changes in cell size, TDS has the potential to improve the specificity of MRI methods in the evaluation of therapeutic response and enable a mechanistic understanding of therapy-induced changes in tumors.

Introduction: Glycogen is the primary intracellular storage form of carbohydrates. In contrast to most tissues where stored glycogen can only supply the local tissue with energy, hepatic glycogen is mobilized and released into the blood to maintain appropriate circulating glucose levels, and is delivered to other tissues as glucose in response to energetic demands. Insulin and glucagon, two current targets of high interest in the pharmaceutical industry, are well-known glucose-regulating hormones whose primary effect in liver is to modulate glycogen synthesis and breakdown. The purpose of these studies was to develop methods to measure glycogen metabolism in real time non-invasively both in isolated mouse livers, and in non-human primates (NHPs) using 13C MRS.Methods: Livers were harvested from C57/Bl6 mice and perfused with [1-13C] Glucose. To demonstrate the ability to measure acute changes in glycogen metabolism ex-vivo, fructose, glucagon, and insulin were administered to the liver ex-vivo. The C1 resonance of glycogen was measured in real time with 13C MRS using an 11.7T (500 MHz) NMR spectrometer. To demonstrate the translatability of this approach, NHPs (male rhesus monkeys) were studied in a 7 T Philips MRI using a partial volume 1H/13C imaging coil. NPHs were subjected to a variable IV infusion of [1-13C] glucose (to maintain blood glucose at 3-4x basal), along with a constant 1 mg/kg/min infusion of fructose. The C1 resonance of glycogen was again measured in real time with 13C MRS. To demonstrate the ability to measure changes in glycogen metabolism in vivo, animals received a glucagon infusion (1 μg/kg bolus followed by 40 ng/kg/min constant infusion) half way through the study on the second study session.Results: In both perfused mouse livers and in NHPs, hepatic 13C-glycogen synthesis (i.e., monotonic increases in the 13C-glycogen NMR signal) was readily detected. In both paradigms, addition of glucagon resulted in cessation of glycogen synthesis and induction of glycogen breakdown. In the perfused liver, inclusion of insulin was able to dose-dependently block the effect of glucagon.Conclusion: Hepatic glycogen synthesis, as well as acute hormonally-induced changes thereof, can be measured using 13C MRS at high magnetic fields both ex-vivo and in vivo. Measurements of this process represent novel, translatable biomarkers of glucagon action, and additionally may be useful for pharmacological targets which modulate glycogen metabolism.

Jak1/2 inhibition suppresses STAT3 phosphorylation that is characteristic of many cancers. Activated STAT3 promotes the transcription of factors that enhance tumor growth, survival, and angiogenesis. AZD1480 is a novel small molecule inhibitor of Jak1/2, which is a key mediator of STAT3 activation. This study examined the use of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) biomarkers in assessing early tumor response to AZD1480. Cediranib (AZD2171), a vascular endothelial growth factor signaling inhibitor, was used as a comparator. Thirty mice were injected with Calu-6 lung cancer cells and randomized into the three treatment groups: AZD1480, cediranib, and sham. DW-MRI and DCE-MRI protocols were performed at baseline and at days 3 and 5 after treatment. The percent change from baseline measurements for Ktrans, ADC, and ve were calculated and compared with hematoxylin and eosin (H&E), CD31, cParp, and Ki-67 histology data. Decreases in Ktrans of 29% (P < .05) and 53% (P < .05) were observed at days 3 and 5, respectively, for the cediranib group. No significant changes in Ktrans occurred for the AZD1480 group, but a significant increase in ADC was demonstrated at days 3 (63%, P < .05) and 5 (49%, P < .05). CD31 staining indicated diminished vasculature in the cediranib group, whereas significantly increased cParp staining for apoptotic activity and extracellular space by image analysis of H&E were present in the AZD1480 group. These imaging biomarker changes, and corresponding histopathology, support the use of ADC, but not Ktrans, as a pharmacodynamic biomarker of response to AZD1480 at these time points.

We report herein a method to track the migration of dendritic cells (DCs) using optical imaging. With the assistance of the delivery module, fluorescein isothiocyanate (FITC) could internalize inside DCs within 15 minutes of incubation. The fluorescent signal was mostly cytoplasmic and could be detected using in vivo imaging. Furthermore, we observed that the probe did not interfere with the DCs maturation as we assessed the expression of several surface markers. The labeled DCs secreted interleukin-12 (IL-12) and tumor necrosis factor-alpha (TNF-α) and stimulated the proliferation of CD4+ T lymphocytes responding to lipopolysaccharide (LIPS) stimulation. We have systematically compared the probe uptake between mature and immature DCs. The study showed that the latter phagocytosed the probe slightly better than the former. Intravital imaging of treated mice showed the migration of DCs to lymph nodes (LNs), which is confirmed by immunohistochemistry. Taken together, we demonstrated the potential use of optical imaging for tracking the migration of DCs and homing in vivo. The delivery molecules could also be used on other imaging modalities or for delivery of antigens.

We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS). Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.

The overall objectives of this research are to (i) develop azulene-based PET probes and (ii) image COX2 as a potential biomarker of breast cancer. Several lines of research have demonstrated that COX2 is overexpressed in breast cancer and that its presence correlates with poor prognoses. While other studies have reported that COX2 inhibition can be modulated and used beneficially as a chemopreventive strategy in cancer, no viable mechanism for achieving that approach has yet been developed. This shortfall could be circumvented through in vivo imaging of COX2 activity, particularly using sensitive imaging techniques such as PET. Toward that goal, our laboratory focuses on the development of novel 18F-labled COX2 probes. We began the synthesis of the probes by transforming tropolone into a lactone, which was subjected to an [8+2] cycloaddition reaction to yield 2-methylazulene as the core ring of the probe. After exploring numerous synthetic routes, the final target molecule and precursor PET compounds were prepared successfully using convergent synthesis. Conventional 18F labeling methods caused precursor decomposition, which prompted us to hypothesize that the acidic protons of the methylene moiety between the azulene and thiazole rings were readily abstracted by a strong base such as potassium carbonate. Ultimately, this caused the precursors to disintegrate. This observation was supported after successfully using an 18F labeling strategy that employed a much milder phosphate buffer. The 18F-labeled COX2 probe was tested in a breast cancer xenograft mouse model. The data obtained via successive whole-body PET/CT scans indicated probe accumulation and retention in the tumor. Overall, the probe was stable in vivo and no defluorination was observed. A biodistribution study and Western blot analysis corroborate with the imaging data. In conclusion, this novel COX2 PET probe was shown to be a promising agent for cancer imaging and deserves further investigation.

Compressive sensing (CS) has been shown to enable dramatic acceleration of MRI acquisition in some applications. Being an iterative reconstruction technique, CS MRI reconstructions can be more time-consuming than traditional inverse Fourier reconstruction. We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. We demonstrate that the combination of the rapid convergence of the split Bregman algorithm and the massively parallel strategy of GPU computing can enable real-time CS reconstruction of even acquisition data matrices of dimension 40962 or more, depending on available GPU VRAM. Reconstruction of two-dimensional data matrices of dimension 10242 and smaller took ~0.3 s or less, showing that this platform also provides very fast iterative reconstruction for small-to-moderate size images.

We present an ultrasonography (US)-magnetic resonance imaging (MRI) coregistration technique and examine its application in a preliminary multimodal, multiparametric study in a preclinical model of breast cancer. Nine mice were injected with 67NR breast cancer cells and imaged 6 and 9 days later with 4.7 T MRI and high-frequency US. Tumor volumes from each data set were segmented independently by two investigators and coregistered using an iterative closest point algorithm. In addition to anatomic images, vascular endothelial growth factor receptor 2 (VEGFR2) distribution images from the central tumor slice using VEGFR2-targeted ultrasound contrast agent (UCA) and measurements of perfusion and extravascular-extracellular volume fraction using dynamic contrast-enhanced MRI were acquired from five mice for multiparametric coregistration. Parametric maps from each modality were coregistered and examined for spatial correlation. Average registration root mean square (RMS) error was 0.36 ± 0.11 mm, less than approximately two voxels. Segmented volumes were compared between investigators to minimize interobserver variability; the average RMS error was 0.23 ± 0.09 mm. In the preliminary study, VEGFR2-targeted UCA data did not demonstrate direct spatial correlation with magnetic resonance measures of vascular properties. In summary, a method for accurately coregistering small animal US and MRI has been presented that allows for comparison of quantitative metrics provided by the two modalities.

We have developed novel proteinase-modulated contrast agents (PCAs) to detect the activity of proteinases in vivo using magnetic resonance imaging. The PCAs are based on the concept of a solubility switch, from hydrophilic to hydrophobic, that significantly modifies the pharmacokinetic properties of the agent as revealed by the slow efflux kinetics from the activity site. Our compound PCA7-switch detects the activity of the secreted matrix-degrading proteinase matrix-metalloproteinase 7 (MMP-7) in living, tumor-bearing mice. Control experiments were performed using an agent that was not cleaved by MMP-7 (PCA7-scrambled), an agent that could be cleaved by MMP-7 but lacked the solubility switch (PCA7-B), and a standard contrast agent (gadolinium–diethylenetriaminepentaacetic acid). PCA7-switch detected a reduction in MMP-7 activity in tumor-bearing mice treated with a synthetic MMP inhibitor, demonstrating its effectiveness in noninvasive functional imaging of proteolytic activity in vivo.

Background and Significance: Achievable signal to noise ratios (SNR) in magnetic resonance microscopy images are limited by acquisition times and the decreasing number of spins in smaller voxels. A common method of enhancing SNR is to cool the RF receiver coil. Significant SNR gains are realized only when the Johnson noise generated within the RF hardware is large compared to the electromagnetic noise produced by the sample. Cryogenic cooling of imaging probes is in common use in high field systems, but it is difficult to insulate a sample from the extreme temperatures involved and in practice imaging cryoprobes have been limited to surface or partial volume designs only. In order to use a solenoid in which the windings were not directly cooled and in close proximity to the sample, we designed a chamber to cool only the tune and match circuitry and show experimentally it is possible to achieve much of the theoretically available SNR gain. Methods: A microcoil circuit consisting of two tuning capacitors, one fixed capacitor, and SMB coaxial cable was designed to resonate at 650 MHz for imaging on a Bruker 15.2 T scanner. Sample noise increases with the sample diameter, so surface loops and solenoids of varying diameters were tested on the bench to determine the largest diameter coil that demonstrated significant SNR gains from cooling. A liquid N2 cryochamber was designed to cool the tune and match circuit, coaxial cable, and connectors, while leaving the RF coil in ambient air. As the cryochamber was filled with liquid N2, quality factors were measured on the bench while monitoring the coil's surface temperature. Improvements of SNR on images of ionic solutions were demonstrated via cooling the tune and match circuit in the magnet bore. Results: At 650 MHz, loops and solenoids < 3 mm in diameter showed significant improvements in quality factor on the bench. The resistance of the variable capacitors and the coaxial cable were measured to be 45% and 32% of room temperature values near the Larmor frequency. Images obtained with a 2 turn, 3 mm diameter loop with the matching circuit at room temperature and then cooled with liquid nitrogen demonstrated SNR improvements of a factor of 2. Conclusions: By cooling the tune and match circuit and leaving the surface loop in ambient air, SNR was improved by a factor of 2. The results are significant because it allows for more space to insulate the sample from the extreme temperatures used in imaging cryoprobes.

Pain perception involves multiple brain regions and networks. Understanding how these brain networks work together is fundamental for appreciating network-wise changes reported in patients with chronic pain disorders. Parcellating pain related networks and understanding their causal relationships is the first step to understand how painful information is processed, integrated, and modulated, and it requires direct manipulation of specific brain regions. Nonhuman primates (NHP) offer an ideal model system to achieve these goals because cortical and subcortical regions in the NHP brain are established based on a variety of different types of data collected in a way that is not feasible or, at least, extremely difficult in humans (i.e., histology data, tract-tracing, intracerebral recordings). In addition, different methodological techniques can also help characterize and further understand these brain cortical and subcortical regions over the course of development. Here we used a heat nociceptive stimulation that is proven to elicit activity of nociceptive neurons in the cortex to refine and parcellate the whole brain nociceptive functional networks, to identify key network hubs, and to characterize network-wise temporal dynamic signatures using high-resolution fMRI. We first functionally localized 24 cortical and subcortical regions that responded to heat nociceptive stimuli (somatosensory area 1/2, area 3a/3b, S2, posterior insula (pIns), anterior insula, area 7b, posterior parietal cortex, anterior cingulate cortex (ACC), prefrontal cortex, caudate, and mediodorsal (MD) and ventral posterior lateral (VPL) thalamic nuclei) and used them as seeds in resting state fMRI (rsfMRI) data analysis. We applied both hierarchical clustering and graph-theory analyses of the pairwise rsfMRI correlation metrics and identified five cortical and one subcortical sub-networks: strong resting state functional connectivity (rsFC) between ACC and prefrontal regions, parietal cortex and area 7b, S2 and posterior insula, areas 3a/3b and 1/2 within the S1 cortex, and thalamic MD and caudate nuclei. The rsFC strengths between cortical areas within each subnetwork were significantly stronger than those between subcortical regions. Regions within each sub-network also exhibited highly correlated temporal dynamics at rest, but the overall dynamic patterns varied drastically across sub-networks. Graph-theory analysis identified the MD nucleus as a hub that connects subcortical and cortical nociceptive sub-networks. The S2-pIns connection joins the sensory and affective/cognitive sub-networks.

Noninvasive estimation of mean axon diameter presents a new opportunity to explore white matter plasticity, development, and pathology. Several diffusion-weighted MRI (DW-MRI) methods have been proposed to measure the average axon diameter in white matter, but they typically require many diffusion encoding measurements and complicated mathematical models to fit the signal to multiple tissue compartments, including intra- and extra-axonal spaces. Here, Monte Carlo simulations uncovered a straightforward DW-MRI metric of axon diameter: the change in radial apparent diffusion coefficient estimated at different effective diffusion times, ΔD⊥. Simulations indicated that this metric increases monotonically within a relevant range of effective mean axon diameter while being insensitive to changes in extra-axonal volume fraction, axon diameter distribution, g-ratio, and influence of myelin water. Also, a monotonic relationship was found to exist for signals coming from both intra- and extra-axonal compartments. The slope in ΔD⊥ with effective axon diameter increased with the difference in diffusion time of both oscillating and pulsed gradient diffusion sequences.

Background Immune checkpoint inhibitors, the most widespread class of immunotherapies, have demonstrated unique response patterns that are not always adequately captured by traditional response criteria such as the Response Evaluation Criteria in Solid Tumors or even immune-specific response criteria. These response metrics rely on monitoring tumor growth, but an increase in tumor size and/or appearance after starting immunotherapy does not always represent tumor progression, but also can be a result of T cell infiltration and thus positive treatment response. Therefore, non-invasive and longitudinal monitoring of T cell infiltration are needed to assess the effects of immunotherapies such as checkpoint inhibitors. Here, we proposed an innovative concept that a sufficiently large influx of tumor infiltrating T cells, which have a smaller diameter than cancer cells, will change the diameter distribution and decrease the average size of cells within a volume to a degree that can be quantified by non-invasive MRI.Methods We validated our hypothesis by studying tumor response to combination immune-checkpoint blockade (ICB) of anti-PD-1 and anti-CTLA4 in a mouse model of colon adenocarcinoma (MC38). The response was monitored longitudinally using Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED), a diffusion MRI-based method which has been previously shown to non-invasively map changes in intracellular structure and cell sizes with the spatial resolution of MRI, in cell cultures and in animal models. Tumors were collected for immunohistochemical and flow cytometry analyzes immediately after the last imaging session.Results Immunohistochemical analysis revealed that increased T cell infiltration of the tumors results in a decrease in mean cell size (eg, a 10% increase of CD3+ T cell fraction results a ~1 µm decrease in the mean cell size). IMPULSED showed that the ICB responders, mice with tumor volumes were less than 250 mm3 or had tumors with stable or decreased volumes, had significantly smaller mean cell sizes than both Control IgG-treated tumors and ICB non-responder tumors.Conclusions IMPULSED-derived cell size could potentially serve as an imaging marker for differentiating responsive and non-responsive tumors after checkpoint inhibitor therapies, a current clinical challenge that is not solved by simply monitoring tumor growth.

ObjectiveIn vivo functional changes in white matter during the progression of Alzheimer's disease (AD) have not been previously reported. Our objectives are to measure changes in white matter functional connectivity (FC) in an elderly population undergoing cognitive decline as AD develops, to establish their relationship to neuropsychological scores of cognitive abilities, and to assess the performance in prediction of AD using white matter FC measures as features.MethodsAnalyses were conducted using resting state functional MRI and neuropsychological data from 383 ADNI participants, including 136 cognitive normal (CN) controls, 46 with significant memory concern, 83 with early mild cognitive impairment (MCI), 37 with MCI, 46 with late MCI, and 35 with AD dementia. FC metrics between segregated white matter tracts and discrete gray matter volumes or between white matter tracts were quantitatively analyzed and characterized, along with their relationships to 6 cognitive measures. Finally, supervised machine learning was implemented on white matter FCs to classify the participants and performance of the classification was evaluated.ResultsSignificant decreases in FC measures were found in white matter with prominent, specific, regional deficits appearing in late MCI and AD dementia patients from CN. These changes significantly correlated with neuropsychological measurements of impairments in cognition and memory. The sensitivity and specificity of distinguishing AD dementia and CN using white matter FCs were 0.83 and 0.81 respectively.Conclusions and relevanceThe white matter FC decreased in late MCI and AD dementia patients compared to CN participants, and this decrease was correlated with cognitive measures. White matter FC is valuable in the prediction of AD. All these findings suggest that white matter FC may be a promising avenue for understanding functional impairments in white matter tracts during AD progression.

Functional magnetic resonance imaging using blood oxygenation level dependent (BOLD) contrast is well established as one of the most powerful methods for mapping human brain function. Numerous studies have measured how low-frequency BOLD signal fluctuations from the brain are correlated between voxels in a resting state, and have exploited these signals to infer functional connectivity within specific neural circuits. However, to date there have been no previous substantiated reports of resting state correlations in the spinal cord. In a cohort of healthy volunteers, we observed robust functional connectivity between left and right ventral (motor) horns, and between left and right dorsal (sensory) horns. Our results demonstrate that low-frequency BOLD fluctuations are inherent in the spinal cord as well as the brain, and by analogy to cortical circuits, we hypothesize that these correlations may offer insight into the execution and maintenance of sensory and motor functions both locally and within the cerebrum.

The systematic investigation of susceptibility-induced contrast in MRI is important to better interpret the influence of microvascular and microcellular morphology on DSC-MRI derived perfusion data. Recently, a novel computational approach called the Finite Perturber Method (FPM), which enables the study of susceptibility-induced contrast in MRI arising from arbitrary microvascular morphologies in 3D has been developed. However, the FPM has lower efficiency in simulating water diffusion especially for complex tissues. In this work, an improved computational approach that combines the FPM with a matrix-based finite difference method (FDM), which we call the Finite Perturber the Finite Difference Method (FPFDM), has been developed in order to efficiently investigate the influence of vascular and extravascular morphological features on susceptibility-induced transverse relaxation. The current work provides a framework for better interpreting how DSC-MRI data depend on various phenomena, including contrast agent leakage in cancerous tissues and water diffusion rates. In addition, we illustrate using simulated and micro-CT extracted tissue structures the improved FPFDM along with its potential applications and limitations.

A novel form of acoustic modulation of light from an incoherent source has been detected in water as well as in turbid media. We demonstrate that patterns of modulated light intensity appear to propagate as the optical shadow of the density variations caused by ultrasound within an illuminated ultrasonic focal zone. This pattern differs from previous reports of acousto-optical interactions that produce diffraction effects that rely on phase shifts and changes in light directions caused by the acoustic modulation. Moreover, previous studies of acousto-optic interactions have mainly reported the effects of sound on coherent light sources via photon tagging, and/or the production of diffraction phenomena from phase effects that give rise to discrete sidebands. We aimed to assess whether the effects of ultrasound modulation of the intensity of light from an incoherent light source could be detected directly, and how the acoustically modulated (AOM) light signal depended on experimental parameters. Our observations suggest that ultrasound at moderate intensities can induce sufficiently large density variations within a uniform medium to cause measurable modulation of the intensity of an incoherent light source by absorption. Light passing through a region of high intensity ultrasound then produces a pattern that is the projection of the density variations within the region of their interaction. The patterns exhibit distinct maxima and minima that are observed at locations much different from those predicted by Raman-Nath, Bragg, or other diffraction theory. The observed patterns scaled appropriately with the geometrical magnification and sound wavelength. We conclude that these observed patterns are simple projections of the ultrasound induced density changes which cause spatial and temporal variations of the optical absorption within the illuminated sound field. These effects potentially provide a novel method for visualizing sound fields and may assist the interpretation of other hybrid imaging methods.

Functional Magnetic Resonance Imaging (fMRI) in the midbrain at 7 Tesla suffers from unexpectedly low temporal signal to noise ratio (TSNR) compared to other brain regions. Various methodologies were used in this study to quantitatively identify causes of the noise and signal differences in midbrain fMRI data. The influence of physiological noise sources was examined using RETROICOR, phase regression analysis, and power spectral analyses of contributions in the respiratory and cardiac frequency ranges. The impact of between-shot phase shifts in 3-D multi-shot sequences was tested using a one-dimensional (1-D) phase navigator approach. Additionally, the effects of shared noise influences between regions that were temporally, but not functionally, correlated with the midbrain (adjacent white matter and anterior cerebellum) were investigated via analyses with regressors of 'no interest'. These attempts to reduce noise did not improve the overall TSNR in the midbrain. In addition, the steady state signal and noise were measured in the midbrain and the visual cortex for resting state data. We observed comparable steady state signals from both the midbrain and the cortex. However, the noise was 2-3 times higher in the midbrain relative to the cortex, confirming that the low TSNR in the midbrain was not due to low signal but rather a result of large signal variance. These temporal variations did not behave as known physiological or other noise sources, and were not mitigated by conventional strategies. Upon further investigation, resting state functional connectivity analysis in the midbrain showed strong intrinsic fluctuations between homologous midbrain regions. These data suggest that the low TSNR in the midbrain may originate from larger signal fluctuations arising from functional connectivity compared to cortex, rather than simply reflecting physiological noise.

Resting state functional magnetic resonance imaging (fMRI) has been commonly used to measure functional connectivity between cortical regions, while diffusion tensor imaging (DTI) can be used to characterize structural connectivity of white matter tracts. In principle combining resting state fMRI and DTI data could allow characterization of structure-function relations of distributed neural networks. However, due to differences in the biophysical origins of their signals and in the tissues to which they apply, there has been no direct integration of these techniques to date. We demonstrate that MRI signal variations and power spectra in a resting state are largely comparable between gray matter and white matter, that there are temporal correlations of fMRI signals that persist over long distances within distinct white matter structures, and that neighboring intervoxel correlations of low frequency resting state signals showed distinct anisotropy in many regions. These observations suggest that MRI signal variations from within white matter in a resting state may convey similar information as their corresponding fluctuations of MRI signals in gray matter. We thus derive a local spatio-temporal correlation tensor which captures directional variations of resting-state correlations and which reveals distinct structures in both white and gray matter. This novel concept is illustrated with in vivo experiments in a resting state, which demonstrate the potential of the technique for mapping the functional structure of neural networks and for direct integration of structure-function relations in the human brain.

Measurements of apparent diffusion coefficient (ADC) using magnetic resonance imaging (MRI) have been suggested as potential imaging biomarkers for monitoring tumor response to treatment. However, conventional pulsed-gradient spin echo (PGSE) methods incorporate relatively long diffusion times, and are usually sensitive to changes in cell density and necrosis. Diffusion temporal spectroscopy using the oscillating gradient spin echo (OGSE) sequence is capable of probing short length scales, and may detect significant intracellular microstructural changes independent of gross cell density changes following anti-cancer treatment. To test this hypothesis, SW620 xenografts were treated by barasertib (AZD1152), a selective inhibitor of Aurora B kinase which causes SW620 cancer cells to develop polyploidy and increase in size following treatment, ultimately leading to cell death through apoptosis. Following treatment, the ADC values obtained by both the PGSE and low frequency OGSE methods increased. However, the ADC values at high gradient frequency (i.e. short diffusion times) were significantly lower in treated tumors, consistent with increased intracellular restrictions/hindrances. This suggests that ADC values at long diffusion times are dominated by tumor microstructure at long length scales, and may not convey unambiguous information of subcellular space. While the diffusion temporal spectroscopy provides more comprehensive means to probe tumor microstructure at various length scales. This work is the first study to probe intracellular microstructural variations due to polyploidy following treatment using diffusion MRI in vivo. It is also the first observation of post-treatment ADC changes occurring in opposite directions at short and long diffusion times. The current study suggests that temporal diffusion spectroscopy potentially provides pharmacodynamic biomarkers of tumor early response which distinguish microstructural variations following treatment at both the subcellular and supracellular length scales.

High-resolution functional MRI is a leading application for very high field (7 Tesla) human MR imaging. Though higher field strengths promise improvements in signal-to-noise ratios (SNR) and BOLD contrast relative to fMRI at 3 Tesla, these benefits may be partially offset by accompanying increases in geometric distortion and other off-resonance effects. Such effects may be especially pronounced with the single-shot EPI pulse sequences typically used for fMRI at standard field strengths. As an alternative, one might consider multishot pulse sequences, which may lead to somewhat lower temporal SNR than standard EPI, but which are also often substantially less susceptible to off-resonance effects. Here we consider retinotopic mapping of human visual cortex as a practical test case by which to compare examples of these sequence types for high-resolution fMRI at 7 Tesla. We performed polar angle retinotopic mapping at each of 3 isotropic resolutions (2.0, 1.7, and 1.1 mm) using both accelerated single-shot 2D EPI and accelerated multishot 3D gradient-echo pulse sequences. We found that single-shot EPI indeed led to greater temporal SNR and contrast-to-noise ratios (CNR) than the multishot sequences. However, additional distortion correction in postprocessing was required in order to fully realize these advantages, particularly at higher resolutions. The retinotopic maps produced by both sequence types were qualitatively comparable, and showed equivalent test/retest reliability. Thus, when surface-based analyses are planned, or in other circumstances where geometric distortion is of particular concern, multishot pulse sequences could provide a viable alternative to single-shot EPI.

The vertebrobasilar system (VBS) is unique in human anatomy in that two arteries merge into a single vessel, and it is especially important because it supplies the posterior circulation of the brain. Atherosclerosis develops in this region, and atherosclerotic plaques in the vertebrobasilar confluence can progress with catastrophic consequences, including artery occlusion. Quantitative assessments of the flow characteristics in the VBS could elucidate the factors that influence flow patterns in this confluence, and deviations from normal patterns might then be used to predict locations to monitor for potential pathological changes, to detect early signs of disease, and to evaluate treatment options and efficacy. In this study, high-field MRI was used in conjunction with computational fluid dynamics (CFD) modeling to investigate the hemodynamics of subject-specific confluence models (n = 5) and to identify different geometrical classes of vertebrobasilar systems (n = 12) of healthy adult subjects. The curvature of the vessels and their mutual orientation significantly affected flow parameters in the VBS. The basilar artery geometry strongly influenced both skewing of the velocity profiles and the wall shear stress distributions in the VBS. All five subjects modeled possessed varying degrees of vertebral asymmetry, and helical flow was observed in four cases, suggesting that factors other than vertebral asymmetry influence mixing of the vertebral artery flow contributions. These preliminary studies verify that quantitative, MR imaging techniques in conjunction with subject-specific CFD models of healthy adult subjects may be used to characterize VBS hemodynamics and to predict flow features that have been related to the initiation and development of atherosclerosis in large arteries. This work represents an important first step towards applying this approach to study disease initiation and progression in the VBS.

As the education field moves toward using responsiveness to intervention (RTI) to identify students with disabilities, an important question is the degree to which this classification can be connected to a student’s neurobiological characteristics. A few functional neuroimaging studies have reported a relationship between activation and response to instruction; however, whether a similar correlation exists with white matter (WM) is not clear. To investigate this issue, we acquired high angular resolution diffusion images from a group of first grade children who differed in their levels of responsiveness to a year-long reading intervention. Using probabilistic tractography, we calculated the strength of WM connections among nine cortical regions of interest and correlated these estimates with participants’ scores on four standardized reading measures. We found eight significant correlations, four of which were connections between the insular cortex and angular gyrus. In each of the correlations, a relationship with children’s response to intervention was evident.

BACKGROUND:Experience can alter how objects are represented in the visual cortex. But experience can take different forms. It is unknown whether the kind of visual experience systematically alters the nature of visual cortical object representations. METHODOLOGY/PRINCIPAL FINDINGS:We take advantage of different training regimens found to produce qualitatively different types of perceptual expertise behaviorally in order to contrast the neural changes that follow different kinds of visual experience with the same objects. Two groups of participants went through training regimens that required either subordinate-level individuation or basic-level categorization of a set of novel, artificial objects, called "Ziggerins". fMRI activity of a region in the right fusiform gyrus increased after individuation training and was correlated with the magnitude of configural processing of the Ziggerins observed behaviorally. In contrast, categorization training caused distributed changes, with increased activity in the medial portion of the ventral occipito-temporal cortex relative to more lateral areas. CONCLUSIONS/SIGNIFICANCE:Our results demonstrate that the kind of experience with a category of objects can systematically influence how those objects are represented in visual cortex. The demands of prior learning experience therefore appear to be one factor determining the organization of activity patterns in visual cortex.

BACKGROUND:The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted an integration of structural and functional analyses of the human language circuits, including Wernicke's (WA), Broca's (BA) and supplementary motor area (SMA), using a combination of blood oxygen level dependent (BOLD) and diffusion tensor MRI. METHODOLOGY/PRINCIPAL FINDINGS:Functional connectivity was measured by low frequency inter-regional correlations of BOLD MRI signals acquired in a resting steady-state, and structural connectivity was measured by using adaptive fiber tracking with diffusion tensor MRI data. The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions. Along the path between BA and SMA, the fibers tracked generally formed a single bundle and the mean radius of the bundle was positively correlated with functional connectivity. However, fractional anisotropy was found not to be correlated with functional connectivity along paths connecting either BA and SMA or BA and WA. CONCLUSIONS/SIGNIFICANCE:These findings suggest that structure-function relations in the human language circuits may involve a number of confounding factors that need to be addressed. Nevertheless, the insights gained from this work offers a useful guidance for continued studies that may provide a non-invasive means to evaluate brain network integrity in vivo for use in diagnosing and determining disease progression and recovery.

BackgroundPrior studies have independently reported associations between major depressive disorder (MDD), elevated cortisol concentrations, early adverse events and region-specific decreases in grey matter volume, but the relationships among these variables are unclear. In the present study, we sought to evaluate the relationships between grey matter volume, early adverse events and cortisol levels in MDD.Methods/resultsGrey matter volume was compared between 19 controls and 19 individuals with MDD using voxel-based morphometry. A history of early adverse events was assessed using the Childhood Trauma Questionnaire. Subjects also provided salivary cortisol samples. Depressed patients showed decreased grey matter volume in the rostral ACC as compared to controls. Rostral ACC volume was inversely correlated with both cortisol and early adverse events.ConclusionsThese findings suggest a key relationship between ACC morphology, a history of early adverse events and circulating cortisol in the pathophysiology of MDD.