Purpose: The heart is a highly aerobic organ consuming most of the oxygen the body in supporting heart function. Quantitative imaging of myocardial oxygen metabolism and perfusion is essential for studying cardiac physiopathology in vivo. Here, we report a new imaging method that can simultaneously assess myocardial oxygen metabolism and blood flow in the rat heart.
Methods: This novel method is based on the O-MRSI combined with brief inhalation of O-isotope labeled oxygen gas for quantitative imaging of myocardial metabolic rate of oxygen consumption (MVO ), myocardial blood flow (MBF), and oxygen extraction fraction (OEF). We demonstrate this imaging method under basal and high workload conditions in rat hearts at 9.4 T.
Results: We show that this O MRSI-based approach can directly measure and image MVO (1.35-4.06 μmol/g/min), MBF (0.49-1.38 mL/g/min), and OEF (0.33-0.44) in the heart of anesthetized rat under basal and high workload (21.6 × 10 -56.7 × 10 mmHg • bpm) conditions. Under high workload condition, MVO and MBF values in healthy rats approximately doubled, whereas OEF remained unchanged, indicating a strong coupling between myocardial oxygen metabolic demand and supply through blood perfusion.
Conclusion: The O-MRSI method has been used to simultaneously image the myocardial metabolic rate of oxygen consumption, blood flow, and oxygen extraction fraction in small animal hearts, which are sensitive to the physiological changes induced by high workload. This approach could provide comprehensive measures that are critical for studying myocardial function in normal and diseased states and has a potential for translation.
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http://dx.doi.org/10.1002/mrm.29908 | DOI Listing |
Cureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
View Article and Find Full Text PDFJDS Commun
January 2025
Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland P61 C996.
Standard operating procedures (SOPs) can improve farm work organization by ensuring processes are standardized among the different people completing the same task. In this study, we examined the use of SOPs on family-operated farms and determined the influence of the number of people working on a farm on SOP use. A survey of 315 Irish dairy farms was completed examining the human resource and workload management practices; this study used a subset of questions from that survey.
View Article and Find Full Text PDFBMC Nurs
January 2025
College of Medicine and Health Sciences, School of Nursing and Midwifery, University of Rwanda, Po. Box: 3286, Kigali, Rwanda.
Background: Pressure injuries are costly and can lead to mortality and psychosocial consequences if not managed effectively. Proper management of pressure injuries is crucial for quality nursing care. However, there is limited research on nurses' knowledge and practices in preventing and managing pressure injuries among critically ill patients in Rwanda.
View Article and Find Full Text PDFFam Med Community Health
January 2025
Institut du Savoir Montfort, Ottawa, Ontario, Canada
Objectives: Primary care attachment represents an inclusive, equitable and cost-effective way of enhancing health outcomes globally. However, the growing shortage of family physicians threatens to disrupt patient-provider relationships. Understanding the consequences of these disruptions is essential for guiding future research and policy.
View Article and Find Full Text PDFJ Strength Cond Res
February 2025
MilanLab Research Department, A.C. Milan S.p.A., Milan, Italy.
Riboli, A, Nardi, F, Osti, M, Cefis, M, Tesoro, G, and Mazzoni, S. Training load, official match locomotor demand, and their association in top-class soccer players during a full competitive season. J Strength Cond Res 39(2): 249-259, 2025-To examine training load and official match locomotor demands of top-class soccer players during a full competitive season and to evaluate their association.
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