Objectives: This study compared risks associated with magnetic resonance imaging (MRI) in patients with non-MRI conditional and MRI conditional pacing and defibrillator systems with particular attention to clinically actionable outcomes.
Background: While recipients of new MRI conditional pacemaker and defibrillator systems may undergo MRI scanning with very low risk, safety and regulatory concerns persist regarding such scanning in recipients of non-MRI conditional systems.
Methods: Patients with any cardiac device who were referred for MRI were prospectively enrolled at a single center and underwent scanning at 1.5 Tesla. Pre- and postscan lead characteristic changes, system integrity, and symptoms were analyzed. A comparison was made between non-MRI conditional and MRI conditional devices.
Results: 105 patients were evaluated allowing for comparison of 97 scans with non-MRI conditional devices and 16 scans with MRI conditional devices. The cohort included those with pacemaker dependency, defibrillator, and cardiac resynchronization devices. Small, nonsignificant changes were observed in lead characteristics following scanning, and there was no significant difference when comparing non-MRI and MRI conditional devices. Lead parameter changes did not require lead revision or programming changes. No device reset, failures, or premature scan termination was observed.
Conclusions: 1.5 T MRI scanning in patients with MRI conditional and non-MRI conditional cardiac devices was performed with similar, low clinical risk.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/pace.13060 | DOI Listing |
Hum Brain Mapp
January 2025
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Adolescent-onset schizophrenia (AOS) is relatively rare, under-studied, and associated with more severe cognitive impairments and poorer outcomes than adult-onset schizophrenia. Neuroimaging has shown altered regional activations (first-order effects) and functional connectivity (second-order effects) in AOS compared to controls. The pairwise maximum entropy model (MEM) integrates first- and second-order factors into a single quantity called energy, which is inversely related to probability of occurrence of brain activity patterns.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Experimental Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Introduction: Lung cancer is the first cause of cancer death in the world, due to a delayed diagnosis and the absence of efficacy therapies. KRAS mutation occurs in 25% of all lung cancers and the concomitant mutations in LKB1 determine aggressive subtypes of these tumors. The improvement of therapeutical options for KRASG12C mutations has increased the possibility of treating these tumors, but resistance to these therapies has emerged.
View Article and Find Full Text PDFNature
January 2025
Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
Glioblastoma is an incurable brain malignancy. By the time of clinical diagnosis, these tumours exhibit a degree of genetic and cellular heterogeneity that provides few clues to the mechanisms that initiate and drive gliomagenesis. Here, to explore the early steps in gliomagenesis, we utilized conditional gene deletion and lineage tracing in tumour mouse models, coupled with serial magnetic resonance imaging, to initiate and then closely track tumour formation.
View Article and Find Full Text PDFAnn Med
December 2025
Department of Radiology, Pinghu Hospital of Traditional Chinese Medicine, Pinghu, China.
Objectives: Develop risk-adapted conditional biopsy pathways utilizing MRI in combination with prostate-specific antigen (PSA) density (PSAD) and the ratio of free to total PSA (f/tPSA), respectively, to enhance the detection of clinically significant prostate cancer (csPCa) while minimizing 'negative' biopsies in low-risk patients.
Methods: The Prostate Imaging Reporting and Data System (PI-RADS) category, PSAD, f/tPSA and biopsy-pathology of 1018 patients were collected retrospectively. Subsequently, PSAD and f/tPSA were divided into four intervals, which were then combined with the MRI findings to construct two risk stratification matrix tables.
Magn Reson Imaging
December 2024
Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721, United States of America; Department of Biomedical Engineering, University of Arizona, Tucson, AZ 85724, United States of America; Department of Medical Imaging, University of Arizona, Tucson, AZ 85724, United States of America; Program in Applied Mathematics, University of Arizona, Tucson, AZ 85724, United States of America. Electronic address:
Purpose: The purpose of this study was to develop DiffDL, a generative diffusion probabilistic model designed to produce high-quality diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics from a reduced set of diffusion-weighted images (DWIs). This model addresses the challenge of prolonged data acquisition times in diffusion MRI while preserving metric accuracy.
Methods: DiffDL was trained using data from the Human Connectome Project, including 300 training/validation subjects and 50 testing subjects.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!