The Mind of a Mouse.

Large scientific projects in genomics and astronomy are influential not because they answer any single question but because they enable investigation of continuously arising new questions from the same data-rich sources. Advances in automated mapping of the brain's synaptic connections (connectomics) suggest that the complicated circuits underlying brain function are ripe for analysis. We discuss benefits of mapping a mouse brain at the level of synapses.

Impact of repeated blast exposure on active-duty United States Special Operations Forces.

United States (US) Special Operations Forces (SOF) are frequently exposed to explosive blasts in training and combat, but the effects of repeated blast exposure (RBE) on SOF brain health are incompletely understood. Furthermore, there is no diagnostic test to detect brain injury from RBE. As a result, SOF personnel may experience cognitive, physical, and psychological symptoms for which the cause is never identified, and they may return to training or combat during a period of brain vulnerability. In 30 active-duty US SOF, we assessed the relationship between cumulative blast exposure and cognitive performance, psychological health, physical symptoms, blood proteomics, and neuroimaging measures (Connectome structural and diffusion MRI, 7 Tesla functional MRI, [11C]PBR28 translocator protein [TSPO] positron emission tomography [PET]-MRI, and [18F]MK6240 tau PET-MRI), adjusting for age, combat exposure, and blunt head trauma. Higher blast exposure was associated with increased cortical thickness in the left rostral anterior cingulate cortex (rACC), a finding that remained significant after multiple comparison correction. In uncorrected analyses, higher blast exposure was associated with worse health-related quality of life, decreased functional connectivity in the executive control network, decreased TSPO signal in the right rACC, and increased cortical thickness in the right rACC, right insula, and right medial orbitofrontal cortex-nodes of the executive control, salience, and default mode networks. These observations suggest that the rACC may be susceptible to blast overpressure and that a multimodal, network-based diagnostic approach has the potential to detect brain injury associated with RBE in active-duty SOF.

Stroke-Related Visceral Alterations: A Voxel-Based Neuroanatomic Localization Study.

OBJECTIVE: Functional and morphologic changes in extracranial organs can occur after acute brain injury. The neuroanatomic correlates of such changes are not fully known. Herein, we tested the hypothesis that brain infarcts are associated with cardiac and systemic abnormalities (CSAs) in a regionally specific manner. METHODS: We generated voxelwise p value maps of brain infarcts for poststroke plasma cardiac troponin T (cTnT) elevation, QTc prolongation, in-hospital infection, and acute stress hyperglycemia (ASH) in 1,208 acute ischemic stroke patients prospectively recruited into the Heart-Brain Interactions Study. We examined the relationship between infarct location and CSAs using a permutation-based approach and identified clusters of contiguous voxels associated with p < 0.05. RESULTS: cTnT elevation not attributable to a known cardiac reason was detected in 5.5%, QTc prolongation in the absence of a known provoker in 21.2%, ASH in 33.9%, and poststroke infection in 13.6%. We identified significant, spatially segregated voxel clusters for each CSA. The clusters for troponin elevation and QTc prolongation mapped to the right hemisphere. There were 3 clusters for ASH, the largest of which was in the left hemisphere. We found 2 clusters for poststroke infection, one associated with pneumonia in the left and one with urinary tract infection in the right hemisphere. The relationship between infarct location and CSAs persisted after adjusting for infarct volume. INTERPRETATION: Our results show that there are discrete regions of brain infarcts associated with CSAs. This information could be used to bootstrap toward new markers for better differentiation between neurogenic and non-neurogenic mechanisms of poststroke CSAs. ANN NEUROL 2023;94:1155-1163.

Neuroimmune activation and increased brain aging in chronic pain patients after the COVID-19 pandemic onset.

The COVID-19 pandemic has exerted a global impact on both physical and mental health, and clinical populations have been disproportionally affected. To date, however, the mechanisms underlying the deleterious effects of the pandemic on pre-existing clinical conditions remain unclear. Here we investigated whether the onset of the pandemic was associated with an increase in brain/blood levels of inflammatory markers and MRI-estimated brain age in patients with chronic low back pain (cLBP), irrespective of their infection history. A retrospective cohort study was conducted on 56 adult participants with cLBP (28 'Pre-Pandemic', 28 'Pandemic') using integrated Positron Emission Tomography/ Magnetic Resonance Imaging (PET/MRI) and the radioligand [11C]PBR28, which binds to the neuroinflammatory marker 18 kDa Translocator Protein (TSPO). Image data were collected between November 2017 and January 2020 ('Pre-Pandemic' cLBP) or between August 2020 and May 2022 ('Pandemic' cLBP). Compared to the Pre-Pandemic group, the Pandemic patients demonstrated widespread and statistically significant elevations in brain TSPO levels (P =.05, cluster corrected). PET signal elevations in the Pandemic group were also observed when 1) excluding 3 Pandemic subjects with a known history of COVID infection, or 2) using secondary outcome measures (volume of distribution -VT- and VT ratio - DVR) in a smaller subset of participants. Pandemic subjects also exhibited elevated serum levels of inflammatory markers (IL-16; P <.05) and estimated BA (P <.0001), which were positively correlated with [11C]PBR28 SUVR (r's ≥ 0.35; P's < 0.05). The pain interference scores, which were elevated in the Pandemic group (P <.05), were negatively correlated with [11C]PBR28 SUVR in the amygdala (r = -0.46; P<.05). This work suggests that the pandemic outbreak may have been accompanied by neuroinflammation and increased brain age in cLBP patients, as measured by multimodal imaging and serum testing. This study underscores the broad impact of the pandemic on human health, which extends beyond the morbidity solely mediated by the virus itself.

Image reconstruction by domain-transform manifold learning.

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) Versus the Standard of Care Imaging in the Diagnosis of Peritoneal Carcinomatosis.

OBJECTIVE: To compare positron emission tomography (PET)/magnetic resonance imaging (MRI) to the standard of care imaging (SCI) for the diagnosis of peritoneal carcinomatosis (PC) in primary abdominopelvic malignancies. SUMMARY BACKGROUND DATA: Identifying PC impacts prognosis and management of multiple cancer types. METHODS: Adult subjects were prospectively and consecutively enrolled from April 2019 to January 2021. Inclusion criteria were: 1) acquisition of whole-body contrast-enhanced (CE) 18F-fluorodeoxyglucose PET/MRI, 2) pathologically confirmed primary abdominopelvic malignancies. Exclusion criteria were: 1) greater than 4 weeks interval between SCI and PET/MRI, 2) unavailable follow-up. SCI consisted of whole-body CE PET/computed tomography (CT) with diagnostic quality CT, and/or CE-CT of the abdomen and pelvis, and/or CE-MRI of the abdomen±pelvis. If available, pathology or surgical findings served as the reference standard, otherwise, imaging followup was used. When SCI and PET/MRI results disagreed, medical records were checked for management changes. Follow-up data were collected until August 2021. RESULTS: One hundred sixty-four subjects were included, 85 (52%) were female, and the median age was 60 years (interquartile range 50-69). At a subject level, PET/MRI had higher sensitivity (0.97, 95% CI 0.86-1.00) than SCI (0.54, 95% CI 0.37-0.71), P < 0.001, without a difference in specificity, of 0.95 (95% CI 0.90-0.98) for PET/MRI and 0.98 (95% CI 0.93-1.00) for SCI, P » 0.250. PET/MRI and SCI results disagreed in 19 cases. In 5/19 (26%) of the discordant cases, PET/MRI findings consistent with PC missed on SCI led to management changes. CONCLUSION: PET/MRI improves detection of PC compared with SCI which frequently changes management.

Linear multi-scale modeling of diffusion MRI data: A framework for characterization of oriented structures across length scales.

Diffusion-weighted magnetic resonance imaging (DW-MRI) has evolved to provide increasingly sophisticated investigations of the human brain's structural connectome in vivo. Restriction spectrum imaging (RSI) is a method that reconstructs the orientation distribution of diffusion within tissues over a range of length scales. In its original formulation, RSI represented the signal as consisting of a spectrum of Gaussian diffusion response functions. Recent technological advances have enabled the use of ultra-high b-values on human MRI scanners, providing higher sensitivity to intracellular water diffusion in the living human brain. To capture the complex diffusion time dependence of the signal within restricted water compartments, we expand upon the RSI approach to represent restricted water compartments with non-Gaussian response functions, in an extended analysis framework called linear multi-scale modeling (LMM). The LMM approach is designed to resolve length scale and orientation-specific information with greater specificity to tissue microstructure in the restricted and hindered compartments, while retaining the advantages of the RSI approach in its implementation as a linear inverse problem. Using multi-shell, multi-diffusion time DW-MRI data acquired with a state-of-the-art 3 T MRI scanner equipped with 300 mT/m gradients, we demonstrate the ability of the LMM approach to distinguish different anatomical structures in the human brain and the potential to advance mapping of the human connectome through joint estimation of the fiber orientation distributions and compartment size characteristics.

Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact.

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.

Disruption of Brainstem Structural Connectivity in REM Sleep Behavior Disorder Using 7 Tesla Magnetic Resonance Imaging.

BACKGROUND: Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is one of the earliest manifestations of α synucleinopathies. Brainstem pathophysiology underlying REM sleep behavior disorder has been described in animal models, yet it is understudied in living humans because of the lack of an in vivo brainstem nuclei atlas and to the limited magnetic resonance imaging (MRI) sensitivity. OBJECTIVE: To investigate brainstem structural connectivity changes in iRBD patients by using an in vivo probabilistic brainstem nuclei atlas and 7 Tesla MRI. METHODS: Structural connectivity of 12 iRBD patients and 12 controls was evaluated by probabilistic tractography. Two-sided Wilcoxon rank-sum test was used to compare the structural connectivity indices across groups. RESULTS: In iRBD, we found impaired (Z = 2.6, P < 0.01) structural connectivity in 14 brainstem nuclei, including the connectivity between REM-on (eg, subcoeruleus [SubC]) and REM sleep muscle atonia (eg, medullary reticular formation) areas. CONCLUSIONS: The brainstem nuclei diagram of impaired connectivity in human iRBD expands animal models and is a promising tool to study and possibly assess prodromal synucleinopathy stages. © 2021 International Parkinson and Movement Disorder Society.

The pandemic brain: Neuroinflammation in non-infected individuals during the COVID-19 pandemic.

While COVID-19 research has seen an explosion in the literature, the impact of pandemic-related societal and lifestyle disruptions on brain health among the uninfected remains underexplored. However, a global increase in the prevalence of fatigue, brain fog, depression and other "sickness behavior"-like symptoms implicates a possible dysregulation in neuroimmune mechanisms even among those never infected by the virus. We compared fifty-seven 'Pre-Pandemic' and fifteen 'Pandemic' datasets from individuals originally enrolled as control subjects for various completed, or ongoing, research studies available in our records, with a confirmed negative test for SARS-CoV-2 antibodies. We used a combination of multimodal molecular brain imaging (simultaneous positron emission tomography / magnetic resonance spectroscopy), behavioral measurements, imaging transcriptomics and serum testing to uncover links between pandemic-related stressors and neuroinflammation. Healthy individuals examined after the enforcement of 2020 lockdown/stay-at-home measures demonstrated elevated brain levels of two independent neuroinflammatory markers (the 18 kDa translocator protein, TSPO, and myoinositol) compared to pre-lockdown subjects. The serum levels of two inflammatory markers (interleukin-16 and monocyte chemoattractant protein-1) were also elevated, although these effects did not reach statistical significance after correcting for multiple comparisons. Subjects endorsing higher symptom burden showed higher TSPO signal in the hippocampus (mood alteration, mental fatigue), intraparietal sulcus and precuneus (physical fatigue), compared to those reporting little/no symptoms. Post-lockdown TSPO signal changes were spatially aligned with the constitutive expression of several genes involved in immune/neuroimmune functions. This work implicates neuroimmune activation as a possible mechanism underlying the non-virally-mediated symptoms experienced by many during the COVID-19 pandemic. Future studies will be needed to corroborate and further interpret these preliminary findings.

Feasibility of simultaneous high-resolution anatomical and quantitative magnetic resonance imaging of sciatic nerves in patients with Charcot-Marie-Tooth type 1A (CMT1A) at 7T.

INTRODUCTION/AIMS: Magnetic resonance imaging (MRI) of peripheral nerves can provide image-based anatomical information and quantitative measurement. The aim of this pilot study was to investigate the feasibility of high-resolution anatomical and quantitative MRI assessment of sciatic nerve fascicles in patients with Charcot-Marie-Tooth (CMT) 1A using 7T field strength. METHODS: Six patients with CMT1A underwent imaging on a high-gradient 7T MRI scanner using a 28-channel knee coil. Two high-resolution axial images were simultaneously acquired using a quantitative double-echo in steady-state (DESS) sequence. By comparing the two DESS echoes, T2 and apparent diffusion coefficient (ADC) maps were calculated. The cross-sectional areas and mean T2 and ADC were measured in individual fascicles of the tibial and fibular (peroneal) portions of the sciatic nerve at its bifurcation and 10 mm distally. Disease severity was measured using Charcot-Marie-Tooth Examination Score (CMTES) version 2 and compared to imaging findings. RESULTS: We demonstrated the feasibility of 7T MRI of the proximal sciatic nerve in patients with CMT1A. Using the higher field, it was possible to measure individual bundles in the tibial and fibular divisions of the sciatic nerve. There was no apparent correlation between diffusion measures and disease severity in this small cohort. DISCUSSION: This pilot study indicated that high-resolution MRI that allows for combined anatomical and quantitative imaging in one scan is feasible at 7T field strengths and can be used to investigate the microstructure of individual nerve fascicles.

Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics.

Recent studies have demonstrated that fast fMRI can track neural activity well above the temporal limit predicted by the canonical hemodynamic response model. While these findings are promising, the biophysical mechanisms underlying these fast fMRI phenomena remain underexplored. In this study, we discuss two aspects of the hemodynamic response, complementary to several existing hypotheses, that can accommodate faster fMRI dynamics beyond those predicted by the canonical model. First, we demonstrate, using both visual and somatosensory paradigms, that the timing and shape of hemodynamic response functions (HRFs) vary across graded levels of stimulus intensity-with lower-intensity stimulation eliciting faster and narrower HRFs. Second, we show that as the spatial resolution of fMRI increases, voxel-wise HRFs begin to deviate from the canonical model, with a considerable portion of voxels exhibiting faster temporal dynamics than predicted by the canonical HRF. Collectively, both stimulus/task intensity and image resolution can affect the sensitivity of fMRI to fast brain activity, which may partly explain recent observations of fast fMRI signals. It is further noteworthy that, while the present investigations focus on fast neural responses, our findings suggest that a revised hemodynamic model may benefit the many fMRI studies using paradigms with wide ranges of contrast levels (e.g., resting or naturalistic conditions) or with modern, high-resolution MR acquisitions.

History of conditioned reward association disrupts inhibitory control: an examination of neural correlates.

The neural processes that support inhibitory control in the face of stimuli with a history of reward association are not yet well understood. Yet, the ability to flexibly adapt behavior to changing reward-contingency contexts is important for daily functioning and warrants further investigation. This study aimed to characterize neural and behavioral impacts of stimuli with a history of conditioned reward association on motor inhibitory control in healthy young adults by investigating group-level effects as well as individual variation in the ability to inhibit responses to stimuli with a reward history. Participants (N = 41) first completed a reward conditioning phase, during which responses to rewarded stimuli were associated with money and responses to unrewarded stimuli were not. Rewarded and unrewarded stimuli from training were carried forward as No-Go targets in a subsequent go/no-go task to test the effect of reward history on inhibitory control. Participants underwent functional brain imaging during the go/no-go portion of the task. On average, a history of reward conditioning disrupted inhibitory control. Compared to inhibition of responses to stimuli with no reward history, trials that required inhibition of responses to previously rewarded stimuli were associated with greater activity in frontal and striatal regions, including the inferior frontal gyrus, insula, striatum, and thalamus. Activity in the insula and thalamus during false alarms and in the ventromedial prefrontal cortex during correctly withheld trials predicted behavioral performance on the task. Overall, these results suggest that reward history serves to disrupt inhibitory control and provide evidence for diverging roles of the insula and ventromedial prefrontal cortex while inhibiting responses to stimuli with a reward history.

Rapid computation of TMS-induced E-fields using a dipole-based magnetic stimulation profile approach.

BACKGROUND: TMS neuronavigation with on-line display of the induced electric field (E-field) has the potential to improve quantitative targeting and dosing of stimulation, but present commercially available solutions are limited by simplified approximations. OBJECTIVE: Developing a near real-time method for accurate approximation of TMS induced E-fields with subject-specific high-resolution surface-based head models that can be utilized for TMS navigation. METHODS: Magnetic dipoles are placed on a closed surface enclosing an MRI-based head model of the subject to define a set of basis functions for the incident and total E-fields that define the subject's Magnetic Stimulation Profile (MSP). The near real-time speed is achieved by recognizing that the total E-field of the coil only depends on the incident E-field and the conductivity boundary geometry. The total E-field for any coil position can be obtained by matching the incident field of the stationary dipole basis set with the incident E-field of the moving coil and applying the same basis coefficients to the total E-field basis functions. RESULTS: Comparison of the MSP-based approximation with an established TMS solver shows great agreement in the E-field amplitude (relative maximum error around 5%) and the spatial distribution patterns (correlation >98%). Computation of the E-field took ~100 ms on a cortical surface mesh with 120k facets. CONCLUSION: The numerical accuracy and speed of the MSP approximation method make it well suited for a wide range of computational tasks including interactive planning, targeting, dosing, and visualization of the intracranial E-fields for near real-time guidance of coil positioning.

Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome.

The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.

Intact Brain Network Function in an Unresponsive Patient with COVID-19.

Many patients with severe coronavirus disease 2019 (COVID-19) remain unresponsive after surviving critical illness. Although several structural brain abnormalities have been described, their impact on brain function and implications for prognosis are unknown. Functional neuroimaging, which has prognostic significance, has yet to be explored in this population. Here we describe a patient with severe COVID-19 who, despite prolonged unresponsiveness and structural brain abnormalities, demonstrated intact functional network connectivity, and weeks later recovered the ability to follow commands. When prognosticating for survivors of severe COVID-19, clinicians should consider that brain networks may remain functionally intact despite structural injury and prolonged unresponsiveness. ANN NEUROL 2020;88:851-854.

PET/MRI assessment of lung nodules in primary abdominal malignancies: sensitivity and outcome analysis.

PURPOSE: To evaluate PET/MR lung nodule detection compared to PET/CT or CT, to determine growth of nodules missed by PET/MR, and to investigate the impact of missed nodules on clinical management in primary abdominal malignancies. METHODS: This retrospective IRB-approved study included [18F]-FDG PET/MR in 126 patients. All had standard of care chest imaging (SCI) with diagnostic chest CT or PET/CT within 6 weeks of PET/MR that served as standard of reference. Two radiologists assessed lung nodules (size, location, consistency, position, and [18F]-FDG avidity) on SCI and PET/MR. A side-by-side analysis of nodules on SCI and PET/MR was performed. The nodules missed on PET/MR were assessed on follow-up SCI to ascertain their growth (≥ 2 mm); their impact on management was also investigated. RESULTS: A total of 505 nodules (mean 4 mm, range 1-23 mm) were detected by SCI in 89/126 patients (66M:60F, mean age 60 years). PET/MR detected 61 nodules for a sensitivity of 28.1% for patient and 12.1% for nodule, with higher sensitivity for > 7 mm nodules (< 30% and > 70% respectively, p < 0.05). 75/337 (22.3%) of the nodules missed on PET/MR (follow-up mean 736 days) demonstrated growth. In patients positive for nodules at SCI and negative at PET/MR, missed nodules did not influence patients' management. CONCLUSIONS: Sensitivity of lung nodule detection on PET/MR is affected by nodule size and is lower than SCI. 22.3% of missed nodules increased on follow-up likely representing metastases. Although this did not impact clinical management in study group with primary abdominal malignancy, largely composed of extra-thoracic advanced stage cancers, with possible different implications in patients without extra-thoracic spread.

Resting-state "physiological networks".

Slow changes in systemic brain physiology can elicit large fluctuations in fMRI time series, which manifest as structured spatial patterns of temporal correlations between distant brain regions. Here, we investigated whether such "physiological networks"-sets of segregated brain regions that exhibit similar responses following slow changes in systemic physiology-resemble patterns associated with large-scale networks typically attributed to remotely synchronized neuronal activity. By analyzing a large group of subjects from the 3T Human Connectome Project (HCP) database, we demonstrate brain-wide and noticeably heterogenous dynamics tightly coupled to either respiratory variation or heart rate changes. We show, using synthesized data generated from physiological recordings across subjects, that these physiologically-coupled fluctuations alone can produce networks that strongly resemble previously reported resting-state networks, suggesting that, in some cases, the "physiological networks" seem to mimic the neuronal networks. Further, we show that such physiologically-relevant connectivity estimates appear to dominate the overall connectivity observations in multiple HCP subjects, and that this apparent "physiological connectivity" cannot be removed by the use of a single nuisance regressor for the entire brain (such as global signal regression) due to the clear regional heterogeneity of the physiologically-coupled responses. Our results challenge previous notions that physiological confounds are either localized to large veins or globally coherent across the cortex, therefore emphasizing the necessity to consider potential physiological contributions in fMRI-based functional connectivity studies. The rich spatiotemporal patterns carried by such "physiological" dynamics also suggest great potential for clinical biomarkers that are complementary to large-scale neuronal networks.

Axon diameter index estimation independent of fiber orientation distribution using high-gradient diffusion MRI.

Axon diameter mapping using high-gradient diffusion MRI has generated great interest as a noninvasive tool for studying trends in axonal size in the human brain. One of the main barriers to mapping axon diameter across the whole brain is accounting for complex white matter fiber configurations (e.g., crossings and fanning), which are prevalent throughout the brain. Here, we present a framework for generalizing axon diameter index estimation to the whole brain independent of the underlying fiber orientation distribution using the spherical mean technique (SMT). This approach is shown to significantly benefit from the use of real-valued diffusion data with Gaussian noise, which reduces the systematic bias in the estimated parameters resulting from the elevation of the noise floor when using magnitude data with Rician noise. We demonstrate the feasibility of obtaining whole-brain orientationally invariant estimates of axon diameter index and relative volume fractions in six healthy human volunteers using real-valued diffusion data acquired on a dedicated high-gradient 3-Tesla human MRI scanner with 300 mT/m maximum gradient strength. The trends in axon diameter index are consistent with known variations in axon diameter from histology and demonstrate the potential of this generalized framework for revealing coherent patterns in axonal structure throughout the living human brain. The use of real-valued diffusion data provides a viable solution for eliminating the Rician noise floor and should be considered for all spherical mean approaches to microstructural parameter estimation.

Reduced tactile acuity in chronic low back pain is linked with structural neuroplasticity in primary somatosensory cortex and is modulated by acupuncture therapy.

Prior studies have shown that patients suffering from chronic Low Back Pain (cLBP) have impaired somatosensory processing including reduced tactile acuity, i.e. reduced ability to resolve fine spatial details with the perception of touch. The central mechanism(s) underlying reduced tactile acuity are unknown but may include changes in specific brain circuitries (e.g. neuroplasticity in the primary somatosensory cortex, S1). Furthermore, little is known about the linkage between changes in tactile acuity and the amelioration of cLBP by somatically-directed therapeutic interventions, such as acupuncture. In this longitudinal neuroimaging study, we evaluated healthy control adults (HC, N â€‹= â€‹50) and a large sample of cLBP patients (N â€‹= â€‹102) with structural brain imaging (T1-weighted MRI for Voxel-Based Morphometry, VBM; Diffusion Tensor Imaging, DTI) and tactile acuity testing using two-point discrimination threshold (2PDT) over the lower back (site of pain) and finger (control) locations. Patients were evaluated at baseline and following a 4-week course of acupuncture, with patients randomized to either verum acupuncture, two different forms of sham acupuncture (designed with or without somatosensory afference), or no-intervention usual care control. At baseline, cLBP patients demonstrated reduced acuity (greater 2PDT, P â€‹= â€‹0.01) over the low back, but not finger (P â€‹= â€‹0.29) locations compared to HC, suggesting that chronic pain affects tactile acuity specifically at body regions encoding the experience of clinical pain. At baseline, Gray Matter Volume (GMV) was elevated and Fractional Anisotropy (FA) was reduced, respectively, in the S1-back region of cLBP patients compared to controls (P â€‹< â€‹0.05). GMV in cLBP correlated with greater 2PDT-back scores (ρ â€‹= â€‹0.27, P â€‹= â€‹0.02). Following verum acupuncture, tactile acuity over the back was improved (reduced 2PDT) and greater improvements were associated with reduced S1-back GMV (ρ â€‹= â€‹0.52, P â€‹= â€‹0.03) and increased S1-back adjacent white matter FA (ρ â€‹= â€‹-0.56, P â€‹= â€‹0.01). These associations were not seen for non-verum control interventions. Thus, S1 neuroplasticity in cLBP is linked with deficits in tactile acuity and, following acupuncture therapy, may represent early mechanistic changes in somatosensory processing that track with improved tactile acuity.