Ultra-low field (ULF) MRI with a pulsed prepolarization is a promising method with potential for applications where conventional high-, mid-, and low-field medical MRI cannot be used due to cost, weight, or other restrictions. Previously, successful ULF demonstrations of anatomical imaging were made using liquid helium-cooled SQUIDs and conducted inside a magnetically shielded room. The Larmor frequency for these demonstrations was ∼3 kHz. In order to make ULF MRI more accessible, portable, and inexpensive, we have recently developed a non-cryogenic system. To eliminate the requirement for a magnetically shielded room and improve the detection sensitivity, we increased the frequency to 83.6 kHz. While the background noise at these frequencies is greatly reduced, this is still within the ULF regime and most of its advantages such as simplicity in magnetic field generation hardware, and less stringent requirements for uniform fields, remaining. In this paper we demonstrate use of this system to image a human hand with up to 1.5mm resolution. The signal-to-noise ratio was sufficient to reveal anatomical features within a scan time of less than 7 min. This prototype can be scaled up for constructing head and full body scanners, and work is in progress toward demonstration of head imaging.
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http://dx.doi.org/10.1016/j.jmr.2011.05.011 | DOI Listing |
Eur Arch Otorhinolaryngol
January 2025
Vrije Universiteit Brussel, Brussels Health Centre, Brussels, Belgium.
Purpose: Cochlear implants (CI) are the most successful bioprosthesis in medicine probably due to the tonotopic anatomy of the auditory pathway and of course the brain plasticity. Correct placement of the CI arrays, respecting the inner ear anatomy are therefore important. The ideal trajectory to insert a cochlear implant array is defined by an entrance through the round window membrane and continues as long as possible parallel to the basal turn of the cochlea.
View Article and Find Full Text PDFEndocrine
January 2025
Anatomic Pathology - Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
Purpose: Adrenal vascular tumors are mainly represented by adrenal cavernous hemangiomas (ACHs) and adrenal cystic lymphangiomas (ACLs). Their radiological features often overlap with malignant tumors, therefore ruling out malignancy becomes mandatory. We analyzed clinical, radiological, and histopathological data to identify specific characteristics of these tumors.
View Article and Find Full Text PDFEur Radiol
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Clinic of Radiology, Imaging Institute of Southern Switzerland (IIMSI), Ente Ospedaliero Cantonale (EOC), Via Tesserete 46, 6900, Lugano, Switzerland.
Lung cancer is the most common and deadly cancer worldwide. The 9th edition of the tumor node meta (TNM) classification system, effective from January 1, 2025, introduces significant updates. Notably, the N2 category is newly divided into N2a (single-station involvement) and N2b (multiple-station involvement), which reflects distinct prognostic implications.
View Article and Find Full Text PDFSci Data
January 2025
Universidad Nacional de Colombia, Bogotá, 1100111, Colombia.
Endoscopy is vital for detecting and diagnosing gastrointestinal diseases. Systematic examination protocols are key to enhancing detection, particularly for the early identification of premalignant conditions. Publicly available endoscopy image databases are crucial for machine learning research, yet challenges persist, particularly in identifying upper gastrointestinal anatomical landmarks to ensure effective and precise endoscopic procedures.
View Article and Find Full Text PDFNat Commun
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Digital Biomarkers for Oncology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Accurate melanoma diagnosis is crucial for patient outcomes and reliability of AI diagnostic tools. We assess interrater variability among eight expert pathologists reviewing histopathological images and clinical metadata of 792 melanoma-suspicious lesions prospectively collected at eight German hospitals. Moreover, we provide access to the largest panel-validated dataset featuring dermoscopic and histopathological images with metadata.
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