Background: In high field MRI capable of multi-channel radio frequency (RF) transmission, B 1 shimming is a time-consuming job because conventional B 1 shimming techniques require B 1 mapping for each channel. After acquiring the complex-numbered B 1 field maps, the optimal amplitude and phase of the driving RF pulse are determined for each channel to maximize the B 1 field uniformity in conventional B 1 shimming. However, time-consuming B 1 shimming procedures at the pre-scan may not be tolerated in the clinical imaging in which patient throughput is one of the important factors.
Methods: To avoid the time-consuming B 1 mapping, the first spin echo and the stimulated echo were repeatedly acquired in the slice-selective stimulated echo sequence without imaging gradients. A cost function of the amplitudes and phases of the driving RF pulse for every channel was defined in a way that the ratio between the spin echo and stimulated echo amplitudes rapidly converged to √ 2. The amplitude and phase of the driving RF pulse were iteratively modified over the repeating RF pulse sequence so that the cost function was minimized.
Results: From the finite-difference-time-domain (FDTD) electromagnetic field simulations with a human body model placed in a birdcage coil operating at 3 T, it was observed that the RF pulse calibration with iterative cost function minimization can give improvement of B1 field uniformity as well as flip-angle calibration. The experiments at 3 T also showed improvement of RF field uniformity in the phantom imaging studies.
Conclusions: Since the proposed RF pulse calibration is not based on B 1 mapping, the RF pulse calibration time could be much shorter than the B 1-mapping based methods. The proposed method is expected to be a practical substitute for the B 1-mapping-based B 1 shimming methods when long pre-scan time is not tolerable.
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http://dx.doi.org/10.1186/s12938-015-0010-z | DOI Listing |
Front Med (Lausanne)
January 2025
Hepatobiliary Pancreatic Surgery Department, Huadu District People's Hospital of Guangzhou, Guangzhou, China.
Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population. This study compared the performance of traditional logistic regression and machine learning models in predicting adult sepsis mortality.
Objective: To develop an optimum model for predicting the mortality of adult sepsis patients based on comparing traditional logistic regression and machine learning methodology.
Heliyon
January 2025
Center for Global Health Research, Saveetha Medical College & Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, 602 105, Tamil Nadu, India.
AI-optimized electrochemical aptasensors are transforming diagnostic testing by offering high sensitivity, selectivity, and rapid response times. Leveraging data-driven AI techniques, these sensors provide a non-invasive, cost-effective alternative to traditional methods, with applications in detecting molecular biomarkers for neurodegenerative diseases, cancer, and coronavirus. The performance metrics outlined in the comparative table illustrate the significant advancements enabled by AI integration.
View Article and Find Full Text PDFMed Intensiva (Engl Ed)
January 2025
Intensive Care Unit, Hospital Universitario Doctor Peset, Av Gaspar Aguilar 90, 46017 Valencia, Spain.
Objective: We aimed to determine predictors of non-invasive ventilation (NIV) failure and validate a nomogram to identify patients at risk of NIV failure.
Design: Observational, analytical study of a retrospective cohort from a single center, compared with an external cohort (March 2020 to August 2021).
Setting: Two intensive care units (ICUs).
Cochrane Database Syst Rev
January 2025
School of Medical Sciences, Department of Metabolism and Systems Science, WHO Collaborating Centre for Global Women's Health Research, University of Birmingham, Birmingham, UK.
Background: Postpartum haemorrhage (PPH) is the leading cause of maternal mortality worldwide. Accurate diagnosis of PPH can prevent adverse outcomes by enabling early treatment.
Objectives: What is the accuracy of methods (index tests) for diagnosing primary PPH (blood loss ≥ 500 mL in the first 24 hours after birth) and severe primary PPH (blood loss ≥ 1000 mL in the first 24 hours after birth) (target conditions) in women giving birth vaginally (participants) compared to weighed blood loss measurement or other objective measurements of blood loss (reference standards)?
Search Methods: We searched CENTRAL, MEDLINE, Embase, Web of Science Core Collection, ClinicalTrials.
J Arrhythm
February 2025
Department of Cardiovascular Medicine, Faculty of Medical Sciences University of Fukui Fukui Japan.
Background: Accurate prediction for survival in individualized patients with cardiac resynchronization therapy with a defibrillator (CRT-D) is difficult.
Methods: We analyzed the New Japan cardiac device treatment registry (JCDTR) database to develop a survival prediction model for CRT-D recipients.
Results: Four hundred and eighty-two CRT-D recipients, at the implantation year 2018-2021, with a QRS width ≥120 ms and left ventricular ejection fraction (LVEF) ≤35% at baseline, were analyzed.
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