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DICOM is an industry-standard for medical imaging data targeted at interoperability across systems. This enables transfer, storage and processing of imaging data regardless of the manufacturer. Pragmatically, manufacturers often store detailed acquisition parameters in private rather than public DICOM tags. In parallel, the DICOM standard itself has gradually evolved by introducing new public tags and properties to better capture emerging imaging technologies. Accurately extracting these details is essential for reproducible neuroimaging research. To address this need, we created a series of DICOM datasets illustrating how various manufacturers encode acquisition details that are critical for modern processing and analysis. These minimal test cases, covering CT and MR modalities, highlight manufacturer-specific conventions, including the use of public tags, private tags, and proprietary data structures. For each DICOM dataset, we provide corresponding NIfTI-formatted images with metadata JSON files following the BIDS standard, using consistent terminology to mitigate variations in how manufacturers encode acquisition details. Our repository provides validation datasets for any tool that is intended to extract acquisition details from medical imaging data.
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http://dx.doi.org/10.1038/s41597-025-05503-w | DOI Listing |
JAMA Psychiatry
September 2025
School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia.
Importance: Cannabis is the most commonly used illicit drug, with 10% to 30% of regular users developing cannabis use disorder (CUD), a condition linked to altered hippocampal integrity. Evidence suggests high-intensity interval training (HIIT) enhances hippocampal structure and function, with this form of physical exercise potentially mitigating CUD-related cognitive and mental health impairments.
Objective: To determine the impact of a 12-week HIIT intervention on hippocampal integrity (ie, structure, connectivity, biochemistry) compared with 12 weeks of strength and resistance (SR) training in CUD.
JAMA Dermatol
September 2025
Department of Dermatology, University of Washington, Seattle.
Importance: Merkel cell carcinoma (MCC) is typically caused by the Merkel cell polyomavirus (MCPyV) and recurs in 40% of patients. Half of patients with MCC produce antibodies to MCPyV oncoproteins, the titers of which rise with disease recurrence and fall after successful treatment.
Objective: To assess the utility of MCPyV oncoprotein antibodies for early detection of first recurrence of MCC in a real-world clinical setting.
JAMA Cardiol
September 2025
Seymour, Paul and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, New York.
Importance: Transthyretin cardiac amyloidosis (ATTR-CA) is an underdiagnosed but treatable cause of heart failure (HF) in older individuals that occurs in the context of normal wild-type (ATTRwt-CA) or an abnormal inherited (ATTRv-CA) TTR gene variant. While the most common inherited TTR variant, V142I, occurs in 3% to 4% of self-identified Black Americans and is associated with excess morbidity and mortality, the prevalence of ATTR-CA in this at-risk population is unknown.
Objective: To define the prevalence of ATTR-CA and proportions attributable to ATTRwt-CA or ATTRv-CA among older Black and Caribbean Hispanic individuals with HF.
Cereb Cortex
August 2025
Section of Brain Function Information, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan.
This study aimed to identify brain activity modulations associated with different types of visual tracking using advanced functional magnetic resonance imaging techniques developed by the Human Connectome Project (HCP) consortium. Magnetic resonance imaging data were collected from 27 healthy volunteers using a 3-T scanner. During a single run, participants either fixated on a stationary visual target (fixation block) or tracked a smoothly moving or jumping target (smooth or saccadic tracking blocks), alternating across blocks.
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August 2025
Aix-Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106, Marseille 13005, France.
Over three decades, statistical parametric mapping has transformed neuroimaging from descriptive mapping to causal inference, placing generative models at the core of causal explanations for brain function. It inspired to a large degree The Virtual Brain, which builds subject-specific digital twins from multimodal data, enabling brain simulations and exploration. Both frameworks converge at parameter estimation, where model and data meet, providing the mathematical manifestation of cause-effect in pathophysiology.
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