A recently introduced quantitative susceptibility mapping (QSM) technique, χ-separation, offers the capability to separate paramagnetic (χ) and diamagnetic (χ) susceptibility distribution within the brain. In-vivo high-resolution mapping of iron and myelin distribution, estimated by χ-separation, could provide a deeper understanding of brain substructures, assisting the investigation of their functions and alterations. This can be achieved using 7T MRI, which benefits from a high signal-to-noise ratio and susceptibility effects. However, applying χ-separation at 7T presents difficulties due to the requirement of an R map, coupled with issues such as high specific absorption rate (SAR), large B transmit field inhomogeneities, and prolonged scan time. To address these challenges, we developed a novel deep neural network, R2PRIMEnet, designed to convert a 7T R* map into a 3T R' map. Building on this development, we present a new pipeline for χ-separation at 7T, enabling us to generate high-resolution χ-separation maps from multi-echo gradient-echo data. The proposed method is compared with alternative pipelines, such as an end-to-end network and linearly-scaled R', and is validated against χ-separation maps at 3T, demonstrating its accuracy. The 7T χ-separation maps generated by the proposed method exhibit similar contrasts to those from 3T, while 7T high-resolution maps offer enhanced clarity and detail. Quantitative analysis confirms that the proposed method surpasses the alternative pipelines. The proposed method results well delineate the detailed brain structures associated with iron and myelin. This new pipeline holds promise for analyzing iron and myelin concentration changes in various neurodegenerative diseases through precise structural examination.
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http://dx.doi.org/10.1016/j.neuroimage.2025.121060 | DOI Listing |
BMC Pharmacol Toxicol
January 2025
Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, 201399, China.
Purpose: This study aims to assess the risks associated with drug-induced macular edema and to examine the epidemiological characteristics of this condition.
Methods: This study analyzed data from the U.S.
Cancer Imaging
January 2025
Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China.
Background: Previous studies utilizing dual-energy CT (DECT) for evaluating treatment efficacy in nasopharyngeal cancinoma (NPC) are limited. This study aimed to investigate whether the parameters from DECT can predict the response to induction chemotherapy in NPC patients in two centers.
Methods: This two-center retrospective study included patients diagnosed with NPC who underwent contrast-enhanced DECT between March 2019 and November 2023.
BMC Nurs
January 2025
China Rehabilitation Research Center, No.18 Jiaomen North Road, Fengtai District, Beijing, China.
Background: Nursing prescribing rights have been proposed in many countries, with physicians' attitudes playing an important role. This study aimed to investigate the attitudes of physicians toward nurse prescribing rights.
Methods: A cross-sectional study of 112 Chinese physicians was conducted from January to March 2024.
BMC Public Health
January 2025
Centre for Prevention, Lifestyle and Health, National Institute for Public Health and The Environment, Bilthoven, The Netherlands.
Background: A new paradigm of hybrid working exists, with most office workers sharing their work between the office and home office environment. Working from home increases time spent or prolonged sitting, which is associated with an increased risk of chronic disease. Interventions to reduce sitting time, specifically designed for both the office and home-office environments, are required to address this growing public health issue.
View Article and Find Full Text PDFBMC Med Ethics
January 2025
Unité de Neurophysiologie du Stress, Institut de Recherche Biomédicale Des Armées, Brétigny Sur Orge Cedex, 91223, France.
Background: A variety of cognitive biases are known to compromise ethical deliberation and decision-making processes. However, little is known about their role in clinical ethics supports (CES).
Methods: We searched five electronic databases (Pubmed, PsychINFO, the Web of Science, CINAHL, and Medline) to identify articles describing cognitive bias in the context of committees that deliberate on ethical issues concerning patients, at all levels of care.
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