Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla.

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

A 128-channel receive array for cortical brain imaging at 7 T.

PURPOSE: A 128-channel receive-only array for brain imaging at 7 T was simulated, designed, constructed, and tested within a high-performance head gradient designed for high-resolution functional imaging. METHODS: The coil used a tight-fitting helmet geometry populated with 128 loop elements and preamplifiers to fit into a 39 cm diameter space inside a built-in gradient. The signal-to-noise ratio (SNR) and parallel imaging performance (1/g) were measured in vivo and simulated using electromagnetic modeling. The histogram of 1/g factors was analyzed to assess the range of performance. The array's performance was compared to the industry-standard 32-channel receive array and a 64-channel research array. RESULTS: It was possible to construct the 128-channel array with body noise-dominated loops producing an average noise correlation of 5.4%. Measurements showed increased sensitivity compared with the 32-channel and 64-channel array through a combination of higher intrinsic SNR and g-factor improvements. For unaccelerated imaging, the 128-channel array showed SNR gains of 17.6% and 9.3% compared to the 32-channel and 64-channel array, respectively, at the center of the brain and 42% and 18% higher SNR in the peripheral brain regions including the cortex. For R = 5 accelerated imaging, these gains were 44.2% and 24.3% at the brain center and 86.7% and 48.7% in the cortex. The 1/g-factor histograms show both an improved mean and a tighter distribution by increasing the channel count, with both effects becoming more pronounced at higher accelerations. CONCLUSION: The experimental results confirm that increasing the channel count to 128 channels is beneficial for 7T brain imaging, both for increasing SNR in peripheral brain regions and for accelerated imaging.

Variation of Benzo[a]pyrene, NNN, and NNK Levels in 16 Commercial Smokeless Tobacco Products.

This study examined the variation of benzo[a]pyrene (B[a]P), N'-nitrosonornicotine (NNN), and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) levels in 16 smokeless tobacco products from several different product subcategories obtained at two different locations and at two different procurement times. B[a]P quantities range from 0.6 to 160 ng/g on a wet-weight basis, whereas NNN and NNK quantities range from 276 to 10473 ng/g and 79 to 28882 ng/g, respectively. The B[a]P, NNN, and NNK quantities vary widely among various smokeless tobacco product categories and among various brands within each product subcategory. Dry snuff products contain the highest B[a]P, NNN, and NNK quantities, whereas loose and portioned snus products contain the lowest B[a]P, NNN, and NNK levels. In general, variation of B[a]P, NNN, and NNK levels across four sets of each product brand purchased six months apart and at two different locations show statistically significant differences (p < 0.05), although with a much narrower product set-to-set variability.

Magnetic Resonance Imaging of the Lumbar Spine: Recommendations for Acquisition and Image Evaluation from the BACPAC Spine Imaging Working Group.

Management of patients suffering from low back pain (LBP) is challenging and requires development of diagnostic techniques to identify specific patient subgroups and phenotypes in order to customize treatment and predict clinical outcome. The Back Pain Consortium (BACPAC) Research Program Spine Imaging Working Group has developed standard operating procedures (SOPs) for spinal imaging protocols to be used in all BACPAC studies. These SOPs include procedures to conduct spinal imaging assessments with guidelines for standardizing the collection, reading/grading (using structured reporting with semi-quantitative evaluation using ordinal rating scales), and storage of images. This article presents the approach to image acquisition and evaluation recommended by the BACPAC Spine Imaging Working Group. While the approach is specific to BACPAC studies, it is general enough to be applied at other centers performing magnetic resonance imaging (MRI) acquisitions in patients with LBP. The herein presented SOPs are meant to improve understanding of pain mechanisms and facilitate patient phenotyping by codifying MRI-based methods that provide standardized, non-invasive assessments of spinal pathologies. Finally, these recommended procedures may facilitate the integration of better harmonized MRI data of the lumbar spine across studies and sites within and outside of BACPAC studies.

Quantitative measurement of harmful and potentially harmful constituents, pH, and moisture content in 16 commercial smokeless tobacco products.

Smokeless tobacco products expose adult and youth tobacco users to various addictive and carcinogenic constituents that can cause long-term nicotine dependence and oral cancers. In this study, nicotine, benzo[a]pyrene (B[a]P), N'-nitrosonornicotine (NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), acetaldehyde, crotonaldehyde, formaldehyde, moisture, and pH levels in 16 smokeless tobacco products were measured on a wet-weight basis (wwb). In addition, change in analytical variability with increasing replicate measurements was assessed. Total nicotine in the products varied from 6.2 to 35.5 mg/g. The percentage of total nicotine in the unprotonated form ranged from 0.1 to 62%; whereas, product moisture varied from 7.4 to 57%. The quantities of harmful and potentially harmful constituents (HPHCs) range from 0.46 to 179.9 ng/g for B [a]P, 270-12206 and 81-20716 ng/g for NNN and NNK, respectively, and 0.33-6.85 and 0.13-5.67 µg/g for acetaldehyde and formaldehyde, respectively. This study shows wide variation in smokeless tobacco product HPHC quantities. The results also show that analytical variability stabilizes after seven replicate measurements.

Volatile Organic Compounds in Mainstream Smoke of Sixty Domestic Little Cigar Products.

The mainstream smoke yields of five volatile organic compounds (VOCs) were determined from 60 commercial U.S. little cigar products under ISO 3308 and Canadian Intense (CI) smoking regimens on linear smoking machines using a gas sampling bag collection. The five VOCs, 1,3-butadiene, acrylonitrile, benzene, isoprene, and toluene were analyzed using an automated GC/MS analytical method validated for measuring various VOCs in mainstream smoke. The VOCs range in amounts from micrograms to milligrams per little cigar. VOC deliveries vary considerably among the little cigar products under the ISO smoking regimen primarily due to varying filter ventilation. Under the CI smoking regimen where filter ventilation is blocked, the delivery range narrows, although individual and total VOC yields are approximately 2 fold higher than those under the ISO smoking regimen. Correlation analysis reveals strong associations between acrylonitrile and 1,3-butadiene or toluene under the ISO smoking regimen. Compared to cigarettes, little cigars delivered substantially higher VOC mainstream smoke yields under both ISO and CI smoking regimens. Moreover, little cigar smoke also contains higher VOCs than cigarette smoke when adjusted for mass of tobacco.

The predominance of seafood allergy in Vietnamese adults: Results from the first population-based questionnaire survey.

BACKGROUND: Food allergy (FA) is a serious, costly and growing health problem worldwide. FA occurs in both children and adults; however, there is a paucity of information on FA prevalence and its clinical features in the adult population, especially in Asia. We sought to assess the prevalence of FAs in Vietnamese adults and the distribution of offending food items among different regions throughout Vietnam. METHODS: A nationwide, cross-sectional, population-based survey was conducted among University students aged 16-50 years. We used a structured, anonymous questionnaire, which was modified from recently published FA epidemiologic studies and based on European Academy of Allergy and Clinical Immunology (EAACI) guidelines, to collect data on FA prevalence, clinical presentations, and implicated food groups. Statistical analysis was performed to generate the prevalence of self-reported and doctor-diagnosed FA and to examine the association of key environmental factors and FA incidence in this population. RESULTS: Of the 14,500 surveys distributed, a total of 9,039 responses were returned, resulting in a response rate of 62.4%. Among participants who reported food-induced adverse reactions, 48.0% have repeated reactions. 18.0% of the participants perceived FA symptoms, but less than half of them sought medical services for confirmation (37.9%). Stratifying for true FA symptoms, the prevalence of self-reported FA was 11.8% and of doctor-diagnosed FA, 4.6%. The most common doctor-diagnosed FA was to crustacean (3.0%; 95% CI, 2.6-3.3), followed by fish (1.6%; 95% CI, 1.3-1.8), mollusk (1.3%; 95% CI, 1.0-1.5) and beef (1.0%; 95% CI, 0.8-1.2). The prevalence of doctor-diagnosed FA differed among participants living in urban (6.5%) and rural regions (4.9%) (P < 0.001). Atopic family history was the strongest predictor for FA (odds ratio 8.0; 95% CI, 6.2-10.4). CONCLUSIONS: Seafood allergy among adults is predominant in Vietnam, followed by beef, milk, and egg, while peanut, soy, and tree nut allergy are much less common. Populations in rural regions have considerably less FA; however, the protective environmental factors have yet to be identified.

A cross-sectional, population-based study on the prevalence of food allergies among children in two different socio-economic regions of Vietnam.

BACKGROUND: There is a paucity of data on the prevalence of food allergy (FA) in Vietnam. A cross-sectional, population-based study was conducted to evaluate the current prevalence of FA among 2- to 6-year-old children in two different regions in Vietnam. METHOD: A structured, anonymous questionnaire, modified from published FA epidemiologic studies and based on EAACI guidelines, was distributed to parents/guardians of participating children in Hue City (urban area) and Tien Giang Province (rural area). Data collected from the survey were statistically analyzed to generate the prevalence of self-reported and doctor-diagnosed FA and overarching pattern of food allergens. RESULTS: A total of 8620 responses were collected (response rate 81.5%). Children in Tien Giang reported more than twice the food-induced adverse reactions seen in children in Hue (47.8% vs. 20.5%). In contrast, children in Hue showed higher self-reported FA (9.8%) and doctor-diagnosed FA rates (8.4%) than children in Tien Giang (7.9% and 5.0%, respectively). Crustacean was the predominant allergy-inducing food in both areas (330 of 580 cases, 56.9%), followed by fish, mollusk, beef, milk, and egg. However, substantial variations of FA patterns were seen between the study sites. Geographic location and co-morbidities of other allergic diseases were key risk factors for FA (P < 0.001). CONCLUSIONS: The prevalence of FA in Vietnamese children seems to be higher than previously reported from other Asian countries. Crustacean is the predominant allergy-inducing food among participating preschool children in Vietnam. The variation of reported food allergen sources across different socio-economic locations could imply different eating habits or the participation of indoor and outdoor allergen exposure.

Human Connectome Project-style resting-state functional MRI at 7 Tesla using radiofrequency parallel transmission.

We investigate the utility of radiofrequency (RF) parallel transmission (pTx) for whole-brain resting-state functional MRI (rfMRI) acquisition at 7 Tesla (7T). To this end, Human Connectome Project (HCP)-style data acquisitions were chosen as a showcase example. Five healthy subjects were scanned in pTx and single-channel transmit (1Tx) modes. The pTx data were acquired using a prototype 16-channel transmit system and a commercially available Nova 8-channel transmit 32-channel receive RF head coil. Additionally, pTx single-spoke multiband (MB) pulses were designed to image sagittal slices. HCP-style 7T rfMRI data (1.6-mm isotropic resolution, 5-fold slice and 2-fold in-plane acceleration, 3600 image volumes and ∼ 1-h scan) were acquired with pTx and the results were compared to those acquired with the original 7T HCP rfMRI protocol. The use of pTx significantly improved flip-angle uniformity across the brain, with coefficient of variation (i.e., std/mean) of whole-brain flip-angle distribution reduced on average by ∼39%. This in turn yielded ∼17% increase in group temporal SNR (tSNR) as averaged across the entire brain and ∼10% increase in group functional contrast-to-noise ratio (fCNR) as averaged across the grayordinate space (including cortical surfaces and subcortical voxels). Furthermore, when placing a seed in either the posterior parietal lobe or putamen to estimate seed-based dense connectome, the increase in fCNR was observed to translate into stronger correlation of the seed with the rest of the grayordinate space. We have demonstrated the utility of pTx for slice-accelerated high-resolution whole-brain rfMRI at 7T; as compared to current state-of-the-art, the use of pTx improves flip-angle uniformity, increases tSNR, enhances fCNR and strengthens functional connectivity estimation.

The Human Connectome Project 7 Tesla retinotopy dataset: Description and population receptive field analysis.

About a quarter of human cerebral cortex is dedicated mainly to visual processing. The large-scale spatial organization of visual cortex can be measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated visual stimuli, also known as "retinotopic mapping." One of the datasets collected by the Human Connectome Project involved ultrahigh-field (7 Tesla) fMRI retinotopic mapping in 181 healthy young adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we describe the experimental paradigm and the results of model-based analysis of the fMRI data. These results provide estimates of population receptive field position and size. Our analyses include both results from individual subjects as well as results obtained by averaging fMRI time series across subjects at each cortical and subcortical location and then fitting models. Both the group-average and individual-subject results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal cortex as well as subcortical areas. The group-average results agree well with previously published parcellations of visual areas. In addition, split-half analyses show strong within-subject reliability, further demonstrating the high quality of the data. We make publicly available the analysis results for individual subjects and the group average, as well as associated stimuli and analysis code. These resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical organization and the properties of high-resolution fMRI. In addition, they provide a set of observations that can be compared with other Human Connectome Project measures acquired in these same participants.

Prevalence of food allergy in Vietnam: comparison of web-based with traditional paper-based survey.

BACKGROUND: Web-based surveys (WBS) are increasingly applied in epidemiological studies as an appealing alternative to traditional survey methods. Rapid data collection, reduced expenditure and ease of access to large populations are some of the clear advantages of online surveys. However, WBS are still subject to limitations in terms of sample size, response rate and other additional biases compared to traditional survey methods. In the present study, we seek to validate data on food allergy (FA) in two independent sample populations collected from a WBS, and compare it to a paper-based survey (PBS). METHODS: Data collected from two survey modes were compared by hypothesis testing for independent sample population. The WBS included 1185 respondents, while the PBS included 9039 respondents. RESULTS: Overall, the data from the WBS were comparable to the PBS conducted over the same period of time in Vietnamese adults. There were no effects of different survey modes on the lifetime prevalence of doctor-diagnosed FA (5.7%; P = 0.7795, ß = 0.05) and IgE-mediated FA (5.8%; P = 0.9590, ß = 0.05). Both surveys showed the dominance of seafood allergy in this population (up to 2.6%), followed by beef allergy. Close correlation was seen in the patterns of FAs and different clinical symptoms. The contribution of family history of allergic diseases and place of residence to FA were confirmed in both surveys. CONCLUSIONS: The consistency of the WBS results with the PBS indicates a promising application of online surveys as an economic and validated model for future epidemiological studies, specifically in developing countries.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI.

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.

High-resolution whole-brain diffusion MRI at 7T using radiofrequency parallel transmission.

PURPOSE: Investigating the utility of RF parallel transmission (pTx) for Human Connectome Project (HCP)-style whole-brain diffusion MRI (dMRI) data at 7 Tesla (7T). METHODS: Healthy subjects were scanned in pTx and single-transmit (1Tx) modes. Multiband (MB), single-spoke pTx pulses were designed to image sagittal slices. HCP-style dMRI data (i.e., 1.05-mm resolutions, MB2, b-values = 1000/2000 s/mm2 , 286 images and 40-min scan) and data with higher accelerations (MB3 and MB4) were acquired with pTx. RESULTS: pTx significantly improved flip-angle detected signal uniformity across the brain, yielding ∼19% increase in temporal SNR (tSNR) averaged over the brain relative to 1Tx. This allowed significantly enhanced estimation of multiple fiber orientations (with ∼21% decrease in dispersion) in HCP-style 7T dMRI datasets. Additionally, pTx pulses achieved substantially lower power deposition, permitting higher accelerations, enabling collection of the same data in 2/3 and 1/2 the scan time or of more data in the same scan time. CONCLUSION: pTx provides a solution to two major limitations for slice-accelerated high-resolution whole-brain dMRI at 7T; it improves flip-angle uniformity, and enables higher slice acceleration relative to current state-of-the-art. As such, pTx provides significant advantages for rapid acquisition of high-quality, high-resolution truly whole-brain dMRI data.

Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field.

Following rapid technological advances, ultra-high field functional MRI (fMRI) enables exploring correlates of neuronal population activity at an increasing spatial resolution. However, as the fMRI blood-oxygenation-level-dependent (BOLD) contrast is a vascular signal, the spatial specificity of fMRI data is ultimately determined by the characteristics of the underlying vasculature. At 7T, fMRI measurement parameters determine the relative contribution of the macro- and microvasculature to the acquired signal. Here we investigate how these parameters affect relevant high-end fMRI analyses such as encoding, decoding, and submillimeter mapping of voxel preferences in the human auditory cortex. Specifically, we compare a T2* weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T2 weighted dataset obtained with 3D GRASE. We first investigated the decoding accuracy based on two encoding models that represented different hypotheses about auditory cortical processing. This encoding/decoding analysis profited from the large spatial coverage and sensitivity of the T2* weighted acquisitions, as evidenced by a significantly higher prediction accuracy in the GE-EPI dataset compared to the 3D GRASE dataset for both encoding models. The main disadvantage of the T2* weighted GE-EPI dataset for encoding/decoding analyses was that the prediction accuracy exhibited cortical depth dependent vascular biases. However, we propose that the comparison of prediction accuracy across the different encoding models may be used as a post processing technique to salvage the spatial interpretability of the GE-EPI cortical depth-dependent prediction accuracy. Second, we explored the mapping of voxel preferences. Large-scale maps of frequency preference (i.e., tonotopy) were similar across datasets, yet the GE-EPI dataset was preferable due to its larger spatial coverage and sensitivity. However, submillimeter tonotopy maps revealed biases in assigned frequency preference and selectivity for the GE-EPI dataset, but not for the 3D GRASE dataset. Thus, a T2 weighted acquisition is recommended if high specificity in tonotopic maps is required. In conclusion, different fMRI acquisitions were better suited for different analyses. It is therefore critical that any sequence parameter optimization considers the eventual intended fMRI analyses and the nature of the neuroscience questions being asked.

Pushing the limits of ultra-high resolution human brain imaging with SMS-EPI demonstrated for columnar level fMRI.

Encoding higher spatial resolution in simultaneous multi-slice (SMS) EPI is highly dependent on gradient performance, high density receiver coil arrays and pulse sequence optimization. We simulate gradient amplitude and slew rate determination of EPI imaging performance in terms of minimum TE, echo spacing (ES) and spatial resolution. We discuss the effects of image zooming in pulse sequences that have been used for sub-millimeter resolutions and the trade-offs in using partial Fourier and parallel imaging to reduce TE, PSF and ES. Using optimizations for SMS EPI pulse sequences with available gradient and receiver hardware, experimental results in ultra-high resolution (UHR) (0.45-0.5mm isotropic) SMS-EPI fMRI and mapping ocular dominance columns (ODC) in human brain at 0.5 mm isotropic resolution are demonstrated. We discuss promising future directions of UHR fMRI.

Evaluation of SLIce Dithered Enhanced Resolution Simultaneous MultiSlice (SLIDER-SMS) for human fMRI.

High isotropic resolution fMRI is challenging primarily due to long repetition times (TR) and insufficient SNR, especially at lower field strengths. Recently, Simultaneous Multi-Slice (SMS) imaging with blipped-CAIPI has substantially reduced scan time and improved SNR efficiency of fMRI. Similarly, super-resolution techniques utilizing sub- voxel spatial shifts in the slice direction have increased both resolution and SNR efficiency. Here we demonstrate the synergistic combination of SLIce Dithered Enhanced Resolution (SLIDER) and SMS for high-resolution, high-SNR whole brain fMRI in comparison to standard resolution fMRI data as well as high-resolution data. With SLIDER-SMS, high spatial frequency information is recovered (unaliased) even in absence of super-resolution deblurring algorithms. Additionally we find that BOLD CNR (as measured by t-value in a visual checkerboard paradigm) is improved by as much as 100% relative to traditionally acquired high- resolution data. Using this gain in CNR, we are able to obtain unprecedented nominally isotropic resolutions at 3T (0.66 mm) and 7T (0.45 mm).

Decoding the Semantic Content of Natural Movies from Human Brain Activity.

One crucial test for any quantitative model of the brain is to show that the model can be used to accurately decode information from evoked brain activity. Several recent neuroimaging studies have decoded the structure or semantic content of static visual images from human brain activity. Here we present a decoding algorithm that makes it possible to decode detailed information about the object and action categories present in natural movies from human brain activity signals measured by functional MRI. Decoding is accomplished using a hierarchical logistic regression (HLR) model that is based on labels that were manually assigned from the WordNet semantic taxonomy. This model makes it possible to simultaneously decode information about both specific and general categories, while respecting the relationships between them. Our results show that we can decode the presence of many object and action categories from averaged blood-oxygen level-dependent (BOLD) responses with a high degree of accuracy (area under the ROC curve > 0.9). Furthermore, we used this framework to test whether semantic relationships defined in the WordNet taxonomy are represented the same way in the human brain. This analysis showed that hierarchical relationships between general categories and atypical examples, such as organism and plant, did not seem to be reflected in representations measured by BOLD fMRI.

Using precise word timing information improves decoding accuracy in a multiband-accelerated multimodal reading experiment.

The blood-oxygen-level-dependent (BOLD) signal measured in functional magnetic resonance imaging (fMRI) experiments is generally regarded as sluggish and poorly suited for probing neural function at the rapid timescales involved in sentence comprehension. However, recent studies have shown the value of acquiring data with very short repetition times (TRs), not merely in terms of improvements in contrast to noise ratio (CNR) through averaging, but also in terms of additional fine-grained temporal information. Using multiband-accelerated fMRI, we achieved whole-brain scans at 3-mm resolution with a TR of just 500 ms at both 3T and 7T field strengths. By taking advantage of word timing information, we found that word decoding accuracy across two separate sets of scan sessions improved significantly, with better overall performance at 7T than at 3T. The effect of TR was also investigated; we found that substantial word timing information can be extracted using fast TRs, with diminishing benefits beyond TRs of 1000 ms.