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.

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.

We evaluated a 16-channel loop + dipole (LD) transceiver antenna array with improved specific absorption rate (SAR) efficiency for 10.5 Tesla (T) human head imaging applications. Three different array designs with equal inner dimensions were considered: an 8-channel dipole antenna, an 8-channel loop, and a 16-channel LD antenna arrays. Signal-to-noise ratio (SNR) and B ₁ ⁺ efficiency (in units of μT per √W) were simulated and measured in 10.5 T magnetic resonance imaging (MRI) experiments. For the safety validation, 10 g SAR and SAR efficiency (defined as the B ₁ ⁺ over √ (peak 10 g SAR)) were calculated through simulation. Finally, high resolution porcine brain images were acquired with the 16-channel LD antenna array, including a fast turbo-spin echo (TSE) sequence incorporating B ₁ shimming techniques. Both the simulation and experiments demonstrated that the combined 16-channel LD antenna array showed similar B ₁ ⁺ efficiency compared to the 8-channel dipole antenna and the 8-channel loop arrays in a circular polarized (CP) mode. In a central 2 mm × 2 mm region of the phantom, however, the 16-channel LD antenna array showed an improvement in peak 10 g SAR of 27.5 % and 32.5 % over the 8-channel dipole antenna and the 8-channel loop arrays, respectively. We conclude that the proposed 16-channel head LD antenna array design is capable of achieving ~7% higher SAR efficiency at 10.5 T compared to either the 8-channel loop-only or the 8-channel dipole-only antenna arrays of the same dimensions.

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.

As of May 8, 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused 514 million confirmed coronavirus disease 2019 (COVID-19) cases and over 6 million COVID-19 confirmed deaths worldwide.^1,2 The efficacy of recently approved medical countermeasures for COVID-19 may be circumvented by emergent SARS-CoV-2 variants that are more transmissible and immune-evasive.³ Data from patients during the first few months of the COVID-19 pandemic (in early 2020) showed that chest CT is sensitive to the detection of the radiographic lung abnormalities associated with COVID-19.⁴ Independent of SARS-CoV-2 variants, pathogenesis is similar, and computed tomography (CT) continues to be an option for determining prognosis. However, the use of medical imaging as a means of evaluating medical countermeasure efficacy in randomized clinical trials is critically hindered by the lack of standardized quantitative image analysis methods and reliable animal models.⁵ In animal models of severe COVID-19, quantitative image analysis methods enable accurate, quantifiable, unbiased, and reproducible measurements of COVID-19 pulmonary disease from medical images.⁶ In particular, noninvasive quantitative imaging biomarkers that do not require serial euthanasia are essential to the characterization of disease severity, progression, and pathogenesis in animal models.^{7 – 12} Quantitation of COVID-19-like lung abnormalities using multimodality imaging biomarkers, including volumetric assessment of radiodensity (CT), has been described in crab-eating (cynomolgus) macaques (Macaca fascicularis) exposed to SARS-CoV-2.⁶

PurposeWe 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.ApproachSix 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.ResultsA 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.ConclusionsRepeatability 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.