Despite advancements in understanding macroscopic and functional brain changes in developing nonhuman primates, a comprehensive in vivo understanding of underlying quantitative microstructural and compositional tissue changes remains elusive. To address this knowledge gap, we applied a quantitative multimodal magnetic resonance imaging (MRI) approach, integrating T1 relaxation time, R2* relaxation rate, and voxel-based morphometry, alongside hematology and serum chemistry analyses, in 94 rhesus monkeys of varying ages (62 males, 32 females; mean age = 5.66±2.08 yr; age range = 1.96-10.3 yr). Our in vivo multimodal analyses revealed distinct age-dependent brain patterns: R2* sharply increased before the age of 5 in deep gray matter (globus pallidus, striatum, thalamus), indicating rapid early iron accumulation in the brain, and then plateaued, strongly supporting a 5-yr developmental age threshold. T1 increased with age in the brainstem and cerebellum, suggesting unique microstructural changes. Voxel-based morphometry revealed a significant volume increase in the deep gray matter, including the thalamus and striatum, and white matter. This study highlights advanced quantitative MRI as a precise, noninvasive developmental index for tracking age-dependent brain tissue properties and microstructural organization in rhesus monkeys during critical developmental ages. These findings provide a robust methodological framework for future research on nonhuman primates, advancing the understanding of neurodevelopment.

Evaluation of the intra-subject reproducibility of radiomic features is pivotal but challenging because it requires multiple replicate measurements, typically lacking in the clinical setting. Radiomics analysis based on computed tomography (CT) has been increasingly used to characterize liver malignancies and liver diffusive diseases. However, radiomic features are greatly affected by scanning parameters and reconstruction kernels, among other factors. In this study, we examined the effects of diets, reconstruction kernels, and liver-to-spleen normalization on the intra-subject reproducibility of radiomic features. The final goal of this work is to create a framework that may help identify reproducible radiomics features suitable for further diagnosis and grading of fatty liver disease in nonhuman primates using radiomics analysis. As a first step, the identification of reproducible features is essential. To accomplish this aim, we retrospectively analyzed serial CT images from two groups of crab-eating macaques, fed a normal or atherogenic diet. Serial CT examinations resulted in 45 high-resolution scans. From each scan, two CT images were reconstructed using a standard B kernel and a bone-enhanced D kernel, with and without normalization relative to the spleen. Radiomic features were extracted from six regions in the liver parenchyma. Intra-subject variability showed that many features are fully reproducible regardless of liver disease status whereas others are significantly different in a limited number of tests. Features significantly different between the normal and atherogenic diet groups were also investigated. Reproducible features were listed, with normalized images having more reproducible features.

Purpose:We describe a method to identify repeatable liver computed tomography (CT) radiomic features, suitable for detection of steatosis, in nonhuman primates. Criteria used for feature selection exclude nonrepeatable features and may be useful to improve the performance and robustness of radiomics-based predictive models. Approach:Six crab-eating macaques were equally assigned to two experimental groups, fed regular chow or an atherogenic diet. High-resolution CT images were acquired over several days for each macaque. First-order and second-order radiomic features were extracted from six regions in the liver parenchyma, either with or without liver-to-spleen intensity normalization from images reconstructed using either a standard (B-filter) or a bone-enhanced (D-filter) kernel. Intrasubject repeatability of each feature was assessed using a paired t-test for all scans and the minimum p-value was identified for each macaque. Repeatable features were defined as having a minimum p-value among all macaques above the significance level after Bonferroni's correction. Features showing a significant difference with respect to diet group were identified using a two-sample t-test. Results:A list of repeatable features was generated for each type of image. The largest number of repeatable features was achieved from spleen-normalized D-filtered images, which also produced the largest number of second-order radiomic features that were repeatable and different between diet groups. Conclusions:Repeatability depends on reconstruction kernel and normalization. Features were quantified and ranked based on their repeatability. Features to be excluded for more robust models were identified. Features that were repeatable but different between diet groups were also identified.

As of 14 December 2021, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), caused nearly 269 million confirmed cases and almost 5.3 million deaths worldwide. Chest computed tomography (CT) has high diagnostic sensitivity for the detection of pulmonary disease in COVID-19 patients. Toward timely and accurate clinical evaluation and prognostication, radiomic analyses of CT images have been explored to investigate the correlation of imaging and non-imaging clinical manifestations and outcomes. Delta (∆) radiomics optimally performed from pre-infection to the post-critical phase, requires baseline data typically not obtained in clinical settings; additionally, their robustness is affected by differences in acquisition protocols. In this work, we investigated the reliability, sensitivity, and stability of whole-lung radiomic features of CT images of nonhuman primates either mock-exposed or exposed to SARS-CoV-2 to study imaging biomarkers of SARS-CoV-2 infection. Images were acquired at a pre-exposure baseline and post-exposure days, and lung fields were segmented. The reliability of radiomic features was assessed, and the dynamic range of each feature was compared to the maximum normal intra-subject variation and ranked.

Purpose:We propose a method to identify sensitive and reliable whole-lung radiomic features from computed tomography (CT) images in a nonhuman primate model of coronavirus disease 2019 (COVID-19). Criteria used for feature selection in this method may improve the performance and robustness of predictive models.Approach:Fourteen crab-eating macaques were assigned to two experimental groups and exposed to either severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or a mock inoculum. High-resolution CT scans were acquired before exposure and on several post-exposure days. Lung volumes were segmented using a deep-learning methodology, and radiomic features were extracted from the original image. The reliability of each feature was assessed by the intraclass correlation coefficient (ICC) using the mock-exposed group data. The sensitivity of each feature was assessed using the virus-exposed group data by defining a factor R that estimates the excess of variation above the maximum normal variation computed in the mock-exposed group. R and ICC were used to rank features and identify non-sensitive and unstable features.Results:Out of 111 radiomic features, 43% had excellent reliability ( ICC > 0.90 ), and 55% had either good ( ICC > 0.75 ) or moderate ( ICC > 0.50 ) reliability. Nineteen features were not sensitive to the radiological manifestations of SARS-CoV-2 exposure. The sensitivity of features showed patterns that suggested a correlation with the radiological manifestations.Conclusions:Features were quantified and ranked based on their sensitivity and reliability. Features to be excluded to create more robust models were identified. Applicability to similar viral pneumonia studies is also possible.

Abnormal energy metabolism associated with mitochondrial dysfunction is thought to be a major contributor to the progression of neurodegenerative diseases such as Parkinson's disease (PD). Recent advancements in the field of magnetic resonance (MR) based metabolic imaging provide state-of-the-art technologies for non-invasively probing cerebral energy metabolism under various brain conditions. In this proof-of-principle clinical study, we employed quantitative 31P MR spectroscopy (MRS) imaging techniques to determine a constellation of metabolic and bioenergetic parameters, including cerebral adenosine triphosphate (ATP) and other phosphorous metabolite concentrations, intracellular pH and nicotinamide adenine dinucleotide (NAD) redox ratio, and ATP production rates in the occipital lobe of cognitive-normal PD patients, and then we compared them with age-sex matched healthy controls. Small but statistically significant differences in intracellular pH, NAD and ATP contents and ATPase enzyme activity between the two groups were detected, suggesting that subtle defects in energy metabolism and mitochondrial function are quantifiable before regional neurological deficits or pathogenesis begin to occur in these patients. Pilot data aiming to evaluate the bioenergetic effect of mitochondrial-protective bile acid, ursodeoxycholic acid (UDCA) were also obtained. These results collectively demonstrated that in vivo 31P MRS-based neuroimaging can non-invasively and quantitatively assess key metabolic-energetic metrics in the human brain. This provides an exciting opportunity to better understand neurodegenerative diseases, their progression and response to treatment.

With the advent of deep learning, convolutional neural networks (CNNs) have evolved as an effective method for the automated segmentation of different tissues in medical image analysis. In certain infectious diseases, the liver is one of the more highly affected organs, where an accurate liver segmentation method may play a significant role to improve the diagnosis, quantification, and follow-up. Although several segmentation algorithms have been proposed for liver or liver-tumor segmentation in computed tomography (CT) of human subjects, none of them have been investigated for nonhuman primates (NHPs), where the livers have a wide range in size and morphology. In addition, the unique characteristics of different infections or the heterogeneous immune responses of different NHPs to the infections appear with a diverse radiodensity distribution in the CT imaging. In this study, we investigated three state-of-the-art algorithms; VNet, UNet, and feature pyramid network (FPN) for automated liver segmentation in whole-body CT images of NHPs. The efficacy of the CNNs were evaluated on 82 scans of 37 animals, including pre and post-exposure to different viruses such as Ebola, Marburg, and Lassa. Using a 10-fold cross-validation, the best performance for the segmented liver was provided by the FPN; an average 94.77% Dice score, and 3.6% relative absolute volume difference. Our study demonstrated the efficacy of multiple CNNs, wherein the FPN outperforms VNet and UNet for liver segmentation in infectious disease imaging research.

Mitochondrial dysfunction is implicated in the pathogenesis of Parkinson's disease. Preliminary data have shown lower brain adenosine triphosphate (ATP) levels in Parkinson's disease versus age-matched healthy controls. Ursodeoxycholic acid (UDCA) may improve impaired mitochondrial function. Our objective was to evaluate UDCA tolerability, pharmacokinetics, and its effect on brain bioenergetics in individuals with Parkinson's disease. An open-label, prospective, multiple-ascending-dose study of oral UDCA in 5 individuals with Parkinson's disease was completed. A blood safety panel, plasma concentrations of UDCA and UDCA conjugates, and brain ATP levels were measured before and after therapy (week 1: 15 mg/kg/day; week 2: 30 mg/kg/day; and weeks 3-6: 50 mg/kg/day). UDCA and conjugates were measured using liquid chromatography-mass spectrometry. ATP levels and ATPase activity were measured using 7-Tesla P-31 magnetic resonance spectroscopy. Secondary measures included the Unified Parkinson's Disease Rating Scale and Montreal Cognitive Assessment. UDCA was generally well tolerated. The most frequent adverse event was gastrointestinal discomfort, rated by subjects as mild to moderate. Noncompartmental pharmacokinetic analysis resulted in (mean +/- standard deviation) a maximum concentration of 8749 +/- 2840 ng/mL and half-life of 2.1 +/- 0.71 hr. Magnetic resonance spectroscopy data were obtained in 3 individuals with Parkinson's disease and showed modest increases in ATP and decreases in ATPase activity. Changes in Unified Parkinson's Disease Rating Scale (parts I-IV) and Montreal Cognitive Assessment scores (mean +/- standard deviation) were -4.6 +/- 6.4 and 2 +/- 1.7, respectively. This is the first report of UDCA use in individuals with Parkinson's disease. Its pharmacokinetics are variable, and at high doses it appears reasonably well tolerated. Our findings warrant additional studies of its effect on brain bioenergetics.

Journal of Magnetic Resonance ImagingVolume 52, Issue 3 p. 764-765 Editorial Editorial for “Functional Alterations of White Matter in Chronic Never-Treated and Treated Schizophrenia Patients“ Byeong-Yeul Lee PhD, Corresponding Author byeongyeul.lee@nih.gov orcid.org/0000-0003-1928-0455 Integrated Research Facility, National Institute of Allergy and Infectious Diseases, National Institute of Health, Frederick, Maryland, 21702 USAAddress reprint requests to: B.-Y.L., Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institute of Health, 8200 Research Plaza, Frederick, MD 21702, USA. E-mail: byeongyeul.lee@nih.govSearch for more papers by this author Byeong-Yeul Lee PhD, Corresponding Author byeongyeul.lee@nih.gov orcid.org/0000-0003-1928-0455 Integrated Research Facility, National Institute of Allergy and Infectious Diseases, National Institute of Health, Frederick, Maryland, 21702 USAAddress reprint requests to: B.-Y.L., Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institute of Health, 8200 Research Plaza, Frederick, MD 21702, USA. E-mail: byeongyeul.lee@nih.govSearch for more papers by this author First published: 02 July 2020 https://doi.org/10.1002/jmri.27274Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume52, Issue3September 2020Pages 764-765 RelatedInformation

This work introduces an innovative magnetic resonance (MR) imaging technology that incorporates radiofrequency (RF) coil(s) with permittivity-tunable ultrahigh dielectric constant (tuHDC) ceramics to significantly improve RF coil transmission and reception efficiencies, MR imaging sensitivity and signal-to-noise ratio (SNR). The tuHDC ceramics made of composite barium strontium titanate (BST) compounds (Ba 0.6 Sr 0.4 TiO 3 ) have low dielectric loss and very high permittivity tunability from 2,000 to 15000 by varying the ceramic temperature between 0°C and 40°C to achieve an optimal permittivity for MR imaging application. We demonstrated for the first time the proof of concept using the BST-based tuHDC-RF-coil technology to improve MR spectroscopic imaging performance of 17 O nuclide at 10.5 Tesla (T) at a low ceramic temperature and 23 Na nuclide at 7T at room temperature. We discovered a large and spatially independent noise reduction under an optimal ceramic temperature, which synergistically resulted in an unprecedented SNR improvement. Large improvements were also demonstrated for 1 H MRI on a 1.5T clinical scanner using the same ceramics. The tuHDC-RF-coil technology is robust, flexible and cost-effective; it presents a technical breakthrough to significantly improve imaging sensitivity and resolution for broad MR imaging applications; which is critical for advancing biomedical and neuroscience research, and improving diagnostic imaging.

For ultra-high field and frequency (UHF) magnetic resonance imaging (MRI), the associated short wavelengths in biological tissues leads to penetration and homogeneity issues at 10.5 tesla (T) and require antenna transmit arrays for efficiently generated 447 MHz B1+ fields (defined as the transmit radiofrequency (RF) magnetic field generated by RF coils). Previously, we evaluated a 16-channel combined loop + dipole antenna (LD) 10.5 T head array. While the LD array configuration did not achieve the desired B1+ efficiency, it showed an improvement of the specific absorption rate (SAR) efficiency compared to the separate 8-channel loop and separate 8-channel dipole antenna arrays at 10.5 T. Here we compare a 16-channel dipole antenna array with a 16-channel LD array of the same dimensions to evaluate B1+ efficiency, 10 g SAR, and SAR efficiency. The 16-channel dipole antenna array achieved a 24% increase in B1+ efficiency in the electromagnetic simulation and MR experiment compared to the LD array, as measured in the central region of a phantom. Based on the simulation results with a human model, we estimate that a 16-channel dipole antenna array for human brain imaging can increase B1+ efficiency by 15% with similar SAR efficiency compared to a 16-channel LD head array.

Spatial averaging of multiple voxels from high-resolution chemical shift imaging (hrCSI) is a common strategy for in vivo metabolic studies to achieve a better signal-to-noise ratio (SNR) for a region-of-interest. However, the mechanism about how the spatial averaging approach influences the respective spectral signal and noise and its relevance to the k-space sampling schemes remains unclear. Using three-dimension 17O CSI technique with the weighted k-space sampling method of Fourier series window, we performed quantitative SNR comparisons between a single low-resolution CSI (lrCSI) voxel (being 27 times larger than the hrCSI voxel size) and the spatially averaged hrCSI voxels with matched sampling volume and location. We demonstrated that the averaged hrCSI voxel spectrum had a large SNR loss (> 4 times) compared to the lrCSI voxel, which was resulted from unmatched increases in signal (~1.9 fold) and noise (~9.3 fold). The signal increase was caused by the spatial overlapping between the adjacent hrCSI voxels. The substantial noise increase was mainly attributed to the strong noise coherence among hrCSI voxels acquired with the weighted k-space sampling. This study presents a quantitative relation between the k-space sampling schemes to an apparent SNR penalty of the spatial averaging approach. The information could be useful for designing CSI acquisition method and determination of optimal spatial resolution for in vivo metabolic imaging studies.

Objective To investigate morphologic changes in the somatosensory cortex and the thickness of the corpus callosum subdivisions that provide interhemispheric connections between the 2 somatosensory cortical areas. Methods Twenty-eight patients with severe restless legs syndrome (RLS) symptoms and 51 age-matched healthy controls were examined with high-resolution MRI at 3.0 tesla. The vertex-wise analysis in conjunction with a novel cortical surface classification method was performed to assess the cortical thickness across the whole-brain structures. In addition, the thickness of the midbody of the corpus callosum that links postcentral gyri in the 2 hemispheres was measured. Results We demonstrated that a morphologic change occurred in the brain somatosensory system in patients with RLS compared to controls. Patients with RLS exhibited a 7.5% decrease in average cortical thickness in the bilateral postcentral gyrus (p < 0.0001). Accordingly, there was a substantial decrease in the corpus callosum posterior midbody (p < 0.008) wherein the callosal fibers are connected to the postcentral gyrus, suggesting altered white matter properties in the somatosensory pathway. Conclusion Our results provide in vivo evidence of morphologic changes in the primary somatosensory system, which could be responsible for the sensory functional symptoms of RLS. These results provide a better understanding of the pathophysiology underlying the RLS sensory symptoms and could lead to a potential imaging marker for RLS.

Characterization of the microstructural properties and topography of the human corpus callosum (CC) is key to understanding interhemispheric neural communication and brain function. In this work, we tested the hypothesis that high-resolution T-1 relaxometry at high field has adequate sensitivity and specificity for characterizing microstructural properties of the human CC, and elucidating the structural connectivity of the callosal fibers to the cortices of origin. The high-resolution parametric T-1 images acquired from healthy subjects (N=16) at 7T clearly showed a consistent T-1 distribution among individuals with substantial variation along the human CC axis, which is highly similar to the spatial patterns of myelin density and myelinated axon size based on the histology study. Compared to the anterior part of the CC, the posterior midbody and splenium had significantly higher T-1 values. In conjunction with T-1-based classification method, the splenial T-1 values were decoded more reliably compared to a conventional partitioning method, showing a much higher T-1 value in the inferior splenium than in the middle/superior splenium. Moreover, the T-1 profile of the callosal subdivision represented the topology of the fiber connectivity to the projected cortical regions: the fibers in the posterior midbody and inferior splenium with a higher T-1 (inferring a larger axon size) were mainly connected to motor-sensory and visual cortical areas, respectively; in contrast, the fibers in the anterior/posterior CC with a lower T-1 (inferring a smaller axon size) were primarily connected to the frontal/parietal-temporal areas. These findings indicate that high-resolution T-1 relaxometry imaging could provide a complementary and robust neuroimaging tool, useful for exploring the complex tissue properties and topographic organization of the human corpus callosum.

The cover image, by is based on the Research Article Brain investigations of rodent disease models by chemical exchange saturation transfer at 21.1 T by Tangi Roussel et al., https://doi.org/10.1002/nbm.3995.

Cellular ATP energy metabolism and regulation are essential for brain function and health. Given the high ATP expenditure at resting-state, it is not yet clear how the human brain at working-state can effectively regulate ATP production to meet higher energy requirement. Through quantitative measurement of regional cerebral ATP production rates and associated neurophysiological parameters in human visual cortex at rest and during visual stimulation, we found significant stimulus-induced and highly correlated neuroenergetic changes, indicating distinctive and complementary roles of the ATP synthesis reactions in supporting evoked neuronal activity and maintaining ATP homeostasis. We also uncovered large individual variances in the neuroenergetic responses and significant reductions in intracellular [H+] and free [Mg2+] during the stimulation. These results provide new insights into the mechanism underlying the brain ATP energy regulation and present a sensitive and much-needed neuroimaging tool for quantitatively assessing neuroenergetic state in healthy and diseased human brain.

A loop+dipole transceiver antenna array was designed for 447 MHz/10.5 tesla human head imaging. This was achieved by a geometrically decoupled combination of a loop and a dipole antenna without inter-element decoupling circuitry. We made comparisons between an 8-channel loop only array, an 8-channel dipole only antenna array and a 16-channel loop+dipole combined antenna array through simulation using the finite difference time domain (FDTD) method and MR imaging experiments.

In vivo31P MRS provides a unique and important imaging tool for studying high-energy phosphate metabolism and bioenergetics noninvasively. However, compared to 1H MRS, 31P MRS with a relatively low gyromagnetic ratio (γ) has a lower and limited sensitivity even at ultrahigh field. The proof of concept has been recently demonstrated that the use of high dielectric constant (HDC) materials between RF coil and object sample could increase MRI signal and reduce required RF transmission power for reaching the same RF pulse flip angle in the region of interest. For low-γ MRS applications operated at relatively lower frequency, however, it demands the dielectric materials with a much higher permittivity for achieving optimal performance. We conducted a 31P MRS imaging study using ultra-HDC (uHDC; with a relative permittivity of ~1200) material blocks incorporated with an RF volume coil at ultrahigh field of 7.0T. The experimental results from phantom and human calf muscle demonstrate that the uHDC technique significantly enhanced RF magnetic transmit field (B1+) and reception field (B1-) and the gain could reach up to two folds in the tissue near the uHDC blocks. The overall results indicate that the incorporation of the uHDC materials having an appropriate permittivity value with a RF coil can significantly increase detection sensitivity and reduces RF transmission power for X-nuclei MRS applications at ultrahigh field. The uHDC technology could provide an efficient, cost-effective engineering solution for achieving high detection sensitivity and concurrently minimizing tissue heating concern for human MRS and MRI applications.

In vivo 31P magnetic resonance spectroscopy (MRS) provides a unique tool for the non‐invasive study of brain energy metabolism and mitochondrial function. The assessment of bioenergetic impairment in different brain regions is essential to understand the pathophysiology and progression of human brain diseases. This article presents a simple and effective approach which allows the interleaved measurement of 31P spectra and imaging from two distinct human brain regions of interest with dynamic B0 shimming capability. A transistor–transistor logic controller was employed to actively switch the single‐channel X‐nuclear radiofrequency (RF) transmitter–receiver between two 31P RF surface coils, enabling the interleaved acquisition of two 31P free induction decays (FIDs) from human occipital and frontal lobes within the same repetition time. Linear gradients were incorporated into the RF pulse sequence to perform the first‐order dynamic shimming to further improve spectral resolution. The overall results demonstrate that the approach provides a cost‐effective and time‐efficient solution for reliable 31P MRS measurement of cerebral phosphate metabolites and adenosine triphosphate (ATP) metabolic fluxes from two human brain regions with high detection sensitivity and spectral quality at 7 T. The same design concept can be extended to acquire multiple spectra from more than two brain regions or can be employed for other magnetic resonance applications beyond the 31P spin.

NAD is an essential metabolite that exists in NAD(+) or NADH form in all living cells. Despite its critical roles in regulating mitochondrial energy production through the NAD(+)/NADH redox state and modulating cellular signaling processes through the activity of the NAD(+)-dependent enzymes, the method for quantifying intracellular NAD contents and redox state is limited to a few in vitro or ex vivo assays, which are not suitable for studying a living brain or organ. Here, we present a magnetic resonance (MR) -based in vivo NAD assay that uses the high-field MR scanner and is capable of noninvasively assessing NAD(+) and NADH contents and the NAD(+)/NADH redox state in intact human brain. The results of this study provide the first insight, to our knowledge, into the cellular NAD concentrations and redox state in the brains of healthy volunteers. Furthermore, an age-dependent increase of intracellular NADH and age-dependent reductions in NAD(+), total NAD contents, and NAD(+)/NADH redox potential of the healthy human brain were revealed in this study. The overall findings not only provide direct evidence of declined mitochondrial functions and altered NAD homeostasis that accompany the normal aging process but also, elucidate the merits and potentials of this new NAD assay for noninvasively studying the intracellular NAD metabolism and redox state in normal and diseased human brain or other organs in situ.