Purpose: A fast T mapping method of the whole pancreas remains a challenge, due to the complex anatomy of the organ. In addition, a technique for pancreas water T mapping is needed, since the T is biased in the presence of fat. The purpose of this work is to accelerate the acquisition of water selective T (wT) mapping for the whole pancreas at 3 T.
Methods: The proposed method combines a continuous inversion-recovery Look-Locker acquisition with a single-shot gradient echo spiral readout, water-fat separation and dictionary matching for wT mapping of the whole pancreas at 3 T. The bias of T in the presence of fat was evaluated in a phantom by comparing the modified Look-Locker inversion-recovery (MOLLI) and the proposed method to MRS measurements. The present method was validated in 11 volunteers by evaluating its pancreas coverage and repeatability and by comparing it to MOLLI. Four pancreatitis patients were evaluated using the proposed method and clinical scans.
Results: The phantom wT results are in better agreement to MRS ( than MOLLI ( . The volunteer wT results demonstrate the whole pancreas coverage capability for different fat fractions, good repeatability ( and lower T values than MOLLI ( . The wT maps in patients captured diverse pancreatitis regions with higher values than in the volunteers , thus showing their potential clinical feasibility.
Conclusion: The present work proposes a wT mapping methodology of the whole pancreas at 3 T, where 24 slices ( ) were acquired in three short breath-holds of 12 s each.
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http://dx.doi.org/10.1007/s10334-025-01224-8 | DOI Listing |
JMIR Med Educ
March 2025
Division of Pulmonary, Critical Care, & Sleep Medicine, Department of Medicine, NYU Grossman School of Medicine, 550 First Avenue, 15th Floor, Medical ICU, New York, NY, 10016, United States, 1 2122635800.
Background: Although technology is rapidly advancing in immersive virtual reality (VR) simulation, there is a paucity of literature to guide its implementation into health professions education, and there are no described best practices for the development of this evolving technology.
Objective: We conducted a qualitative study using semistructured interviews with early adopters of immersive VR simulation technology to investigate use and motivations behind using this technology in educational practice, and to identify the educational needs that this technology can address.
Methods: We conducted 16 interviews with VR early adopters.
Inorg Chem
March 2025
College of Energy Storage Technology, Shandong University of Science and Technology, Qingdao 266590, China.
Cesium-lead halide perovskite nanomaterials have been considered new-generation emitters that can meet the requirements of high photoluminescence efficiency and the high color standard of Rec. 2020. However, their practical application is currently hindered by the challenge of achieving better stability and growth in green solvents.
View Article and Find Full Text PDFNano Lett
March 2025
College of Physics, Weihai Innovation Research Institute, College of Materials Science and Engineering, Qingdao University, Qingdao 266071, China.
Ferromagnetic metals, distinguished by high Curie temperatures and magnetization, are crucial in voltage-controlled magnetism for potential room-temperature applications in low-power multifunctional devices. Despite numerous attempts based on various mechanisms, achieving ideal magnetic modulation in metals remains challenging. This work proposes a new mechanism to control bulk metal magnetism by modulating valence electron filling in spin-polarized bands, leveraging the Slater-Pauling rule in alloys.
View Article and Find Full Text PDFBioinformatics
March 2025
Department of Statistics, Hunan University, Changsha, 410000, China.
Motivation: Inferring gene networks provides insights into biological pathways and functional relationships among genes. When gene expression samples exhibit heterogeneity, they may originate from unknown subtypes, prompting the utilization of mixture Gaussian graphical model for simultaneous subclassification and gene network inference. However, this method overlooks the heterogeneity of network relationships across subtypes and does not sufficiently emphasize shared relationships.
View Article and Find Full Text PDFElife
March 2025
Machine Learning Core, National Institute of Mental Health, Bethesda, United States.
Fiber photometry has become a popular technique to measure neural activity in vivo, but common analysis strategies can reduce the detection of effects because they condense signals into summary measures, and discard trial-level information by averaging . We propose a novel photometry statistical framework based on functional linear mixed modeling, which enables hypothesis testing of variable effects at , and uses trial-level signals without averaging. This makes it possible to compare the timing and magnitude of signals across conditions while accounting for between-animal differences.
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