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A detailed spatiotemporal atlas of the white matter tracts for the fetal brain.
Proc Natl Acad Sci U S A
January 2025
Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA 02115.
This study presents the construction of a comprehensive spatiotemporal atlas of white matter tracts in the fetal brain for every gestational week between 23 and 36 wk using diffusion MRI (dMRI). Our research leverages data collected from fetal MRI scans, capturing the dynamic changes in the brain's architecture and microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers.
View Article and Find Full Text PDFGOLD grade-specific characterization of COPD in the COSYCONET multi-center trial: comparison of semiquantitative MRI and quantitative CT.
Eur Radiol
January 2025
Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany.
Objectives: We hypothesized that semiquantitative visual scoring of lung MRI is suitable for GOLD-grade specific characterization of parenchymal and airway disease in COPD and that MRI scores correlate with quantitative CT (QCT) and pulmonary function test (PFT) parameters.
Methods: Five hundred ninety-eight subjects from the COSYCONET study (median age = 67 (60-72)) at risk for COPD or with GOLD1-4 underwent PFT, same-day paired inspiratory/expiratory CT, and structural and contrast-enhanced MRI. QCT assessed total lung volume (TLV), emphysema, and air trapping by parametric response mapping (PRM, PRM) and airway disease by wall percentage (WP).
Noninvasive Assessment of Liver Fibrosis in Patients With Iron Overload.
Ultrasound Med Biol
December 2024
Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
Objective: We assessed the diagnostic performance of ultrasound two-dimensional shear wave elastography (US 2D-SWE) to predict clinically significant fibrosis (CSF) in patients with serologic iron overload (SIO) and the subgroup with histologic liver iron overload (LIO).
Methods: A single-center retrospective cross-sectional study of adults with SIO (serum ferritin ≥ 200 ng/mL in females and ≥ 300 ng/mL in males) and suspected chronic liver disease with nonfocal liver biopsy results and US 2D-SWE exams within 1 year was performed. Histopathological fibrosis stage ≥2 and liver iron ≥2+ was considered CSF and LIO, respectively.
Role of radiation emergency medicine: historical view-a perspective on the past, present, and future.
J Radiat Res
December 2024
Faculty and Postgraduate School of Nursing, Tokyo Healthcare University, 2-5-1 Higashigaoka, Meguro-ku, Tokyo 152-8558, Japan.
The more science progresses, the more life and society change. Medicine also changes with the times and the culture. This is also true for radiation emergency medicine, which includes dose-assessment leading to diagnosis, treatment, medical follow-up and prognosis of persons who have developed acute injury or illness due to radioactive contamination or radiation exposure.
View Article and Find Full Text PDFDeep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population.
EBioMedicine
December 2024
Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. Electronic address:
Article Synopsis
- This study explores the use of advanced deep learning methods to automatically measure body composition from whole-body MRI scans, aiming to assess their ability to predict mortality in the general population.
- The investigation was based on data from two large Western European cohort studies, focusing on key body composition metrics such as subcutaneous and visceral adipose tissue, skeletal muscle, and intramuscular fat.
- Results indicate significant associations between several volumetric body composition measures and mortality risk, highlighting the potential of automated techniques to improve clinical outcomes related to cardiometabolic diseases and cancer.
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