Advanced H-1 Lung Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is one of the widely used medical imaging modality, since it can provide both structural and functional assessment in a single imaging session. However, two major challenges should be considered by using MRI for lung imaging. The first challenge is the intrinsic low SNR of H-1 lung MRI due to the low proton density as well as the fast decay of the lung parenchyma signal. And the second challenge is subject motion. To achieve high resolution structural image, MRI requires a long scan time, usually a few minutes or even longer, which make MRI sensitive to subject motion. To address the first challenge, ultra-short echo time (UTE) MRI sequence is used to capture the lung parenchyma signal before decay. As for subject motion, two major strategies are widely used. One strategy is fast breath-holding scan, the subjects are asked to hold their breaths for a short duration, and the fast 3D MR sequence would be used to acquire data within that duration. This dissertation proposes a new acquisition scheme based on the standard UTE sequence, which largely increases the encoding efficiency and improves the breath-holding scan images. The other is free breathing scan with motion correction. The subjects are allowed to breathe during the MR acquisition. After the acquisition, the motion corrupted data would go through the motion correction step to reconstruct the motion free images. In this dissertation, two novel motion corrected reconstruction strategies are proposed to incorporate the motion modeling and compensation into the reconstruction to get high SNR motion corrected 3D and 4D images. When translating the developed techniques to the clinical studies, specifically for pediatric and neonatal studies, more practical problems need to be considered, such as smaller but finer anatomy to image, the different respiratory patterns of the young subjects etc. This dissertation proposes a 5-minute free breathing UTE MRI strategy to achieve a 3D high resolution motion free lung image for pediatric and neonatal studies

Automated MRI Field of View Prescription from Region of Interest Prediction by Intra-stack Attention Neural Network

Manual prescription of the field of view (FOV) by MRI technologists is variable and prolongs the scanning process. Often, the FOV is too large or crops critical anatomy. We propose a deep-learning framework, trained by radiologists' supervision, for automating FOV prescription. An intra-stack shared feature extraction network and an attention network are used to process a stack of 2D image inputs to generate output scalars defining the location of a rectangular region of interest (ROI). The attention mechanism is used to make the model focus on the small number of informative slices in a stack. Then the smallest FOV that makes the neural network predicted ROI free of aliasing is calculated by an algebraic operation derived from MR sampling theory. We retrospectively collected 595 cases between February 2018 and February 2022. The framework's performance is examined quantitatively with intersection over union (IoU) and pixel error on position, and qualitatively with a reader study. We use the t-test for comparing quantitative results from all models and a radiologist. The proposed model achieves an average IoU of 0.867 and average ROI position error of 9.06 out of 512 pixels on 80 test cases, significantly better (P<0.05) than two baseline models and not significantly different from a radiologist (P>0.12). Finally, the FOV given by the proposed framework achieves an acceptance rate of 92% from an experienced radiologist

The phytochemicals and health benefits of Cyclocarya paliurus (Batalin) Iljinskaja

Cyclocarya paliurus (C. paliurus), a nutritional and nutraceutical resource for human and animal diets, has been constantly explored. The available biological components of C. paliurus were triterpenoids, polysaccharides, and flavonoids. Recent studies in phytochemical-phytochemistry; pharmacological-pharmacology has shown that C. paliurus performed medicinal value, such as antihypertensive, antioxidant, anticancer, antimicrobial, anti-inflammatory and immunological activities. Furthermore, C. paliurus and its extracts added to drinks would help to prevent and mitigate chronic diseases. This review provides an overview of the nutritional composition and functional applications of C. paliurus, summarizing the research progress on the extraction methods, structural characteristics, and biological activities. Therefore, it may be a promising candidate for developing functional ingredients in traditional Chinese medicine. However, a more profound understanding of its active compounds and active mechanisms through which they perform biological activities is required. As a result, the plant needs further investigation in vitro and in vivo

H2S gas sensing performance and mechanisms using CuO-Al2O3 composite films based on both surface acoustic wave and chemiresistor techniques

Surface acoustic wave and chemiresistor based gas sensors integrated with a sensing layer of sol-gel CuO-Al2O3 composite film were fabricated and their performance and mechanisms for H2S sensing were characterized and compared. In the composite film, CuO nanoparticles provide active sites for adsorption and reaction of H2S molecules while Al2O3 nanoparticles help to form a uniform and mesoporous film structure, both of which enhance the sensitivity of the sensors by providing numerous active CuO surfaces. Through the comparative studies, the SAW based H2S sensor operated at room temperature showed a lower detection limit, higher sensitivity, better linearity and good selectivity to H2S gas with its concentration ranging from 5 ppb to 100 ppm, compared with those of the chemiresistor sensor, which are mainly attributed to the effective mass sensing properties of the SAW sensor, because a minor change in the mass of the film caused by adsorbed H2S molecules would lead to a significant and monotonous change of the resonant frequency of the SAW devices

Advanced H-1 Lung Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is one of the widely used medical imaging modality, since it can provide both structural and functional assessment in a single imaging session. However, two major challenges should be considered by using MRI for lung imaging. The first challenge is the intrinsic low SNR of H-1 lung MRI due to the low proton density as well as the fast decay of the lung parenchyma signal. And the second challenge is subject motion. To achieve high resolution structural image, MRI requires a long scan time, usually a few minutes or even longer, which make MRI sensitive to subject motion. To address the first challenge, ultra-short echo time (UTE) MRI sequence is used to capture the lung parenchyma signal before decay. As for subject motion, two major strategies are widely used. One strategy is fast breath-holding scan, the subjects are asked to hold their breaths for a short duration, and the fast 3D MR sequence would be used to acquire data within that duration. This dissertation proposes a new acquisition scheme based on the standard UTE sequence, which largely increases the encoding efficiency and improves the breath-holding scan images. The other is free breathing scan with motion correction. The subjects are allowed to breathe during the MR acquisition. After the acquisition, the motion corrupted data would go through the motion correction step to reconstruct the motion free images. In this dissertation, two novel motion corrected reconstruction strategies are proposed to incorporate the motion modeling and compensation into the reconstruction to get high SNR motion corrected 3D and 4D images. When translating the developed techniques to the clinical studies, specifically for pediatric and neonatal studies, more practical problems need to be considered, such as smaller but finer anatomy to image, the different respiratory patterns of the young subjects etc. This dissertation proposes a 5-minute free breathing UTE MRI strategy to achieve a 3D high resolution motion free lung image for pediatric and neonatal studies

Optimizing trajectory ordering for fast radial ultra-short TE (UTE) acquisitions

PurposeAdditional spoiler gradients are required in 3D UTE sequences with random view ordering to suppress magnetization refocusing. By leveraging the encoding gradient induced spoiling effect, the spoiler gradients could potentially be reduced or removed to shorten the TR and increase encoding efficiency. An analysis framework is built that models the gradient spoiling effects and a new ordering scheme is proposed for fast 3D UTE acquisition.Theory and methodsUTE signal evolution and spatial encoding gradient induced spoiling effect are derived from the Bloch equations. And the concept is validated in 2D radial UTE simulation. Then an optimized ordering scheme, named reordered 2D golden angle (r2DGA) scheme, for 3D UTE acquisition is proposed. The r2DGA scheme is compared to the sequential and 3D golden angle schemes in both phantom and volunteer studies.ResultsThe proposed r2DGA ordering scheme was applied to two applications, single breath-holding and free breathing 3D lung MRI. With r2DGA ordering scheme, breath-holding lung MRI scan increased 60% scan efficiency by removing the spoiler gradients and the free breathing scan reduced 20% scan time compared to the 3D golden angle scheme by reducing the spoiler gradients.ConclusionsThe proposed r2DGA ordering scheme UTE acquisition reduces the need of spoiler gradients and increases the encoding efficiency, and shows improvements in both breath-holding and free breathing lung MRI applications