Advancements in Medical Imaging Technology

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1324

Special Issue Editor


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Guest Editor
School of Engineering, Santa Clara University, Santa Clara, CA 95053, USA
Interests: biosignal processing; bioimaging; AI-assisted disease classification; laryngeal dynamics and physiology; biomedical visualization; brain-computer Interface
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Special Issue Information

Dear Colleagues,

The Special Issue provides a platform for researchers to present their latest breakthroughs and discoveries in diagnostic medical imaging. Ongoing progress in hardware innovation and image reconstruction techniques, alongside post-processing methods integrating computer-aided diagnosis and cutting-edge deep learning technologies, offer significant potential to transform various aspects of healthcare. These advancements hold promise in improving disease prognosis, refining diagnostic accuracy and enabling personalized treatment strategies, ultimately revolutionizing patient care.

This issue will comprehensively cover a diverse array of topics related to diagnostic imaging modalities, encompassing CT, high-field and low-field MRI, ultrasonography and other imaging techniques commonly employed in disease diagnosis and prognosis. We encourage contributions from a wide spectrum of professionals, including engineers, medical practitioners and interdisciplinary teams possessing combined expertise in medicine and biomedical engineering. By fostering collaborations and knowledge exchange, our ultimate goal is to advance the field of medical imaging, driving innovation and improving patient outcomes on a global scale.

Prof. Dr. Yuling Yan
Guest Editor

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Keywords

  • diagnostic imaging
  • image reconstruction and analysis
  • computer-aided diagnosis
  • deep learning

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Published Papers (1 paper)

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11 pages, 2682 KiB  
Article
Visualization of Cerebrospinal Fluid Outflow and Egress along the Nerve Roots of the Lumbar Spine
by Diana Vucevic, Vadim Malis, Won C. Bae, Hideki Ota, Koichi Oshio, Marin A. McDonald and Mitsue Miyazaki
Bioengineering 2024, 11(7), 708; https://doi.org/10.3390/bioengineering11070708 - 12 Jul 2024
Viewed by 1008
Abstract
Intrinsic cerebrospinal fluid (CSF) dynamics in the brain have been extensively studied, particularly the egress sites of tagged intrinsic CSF in the meninges. Although spinal CSF recirculates within the central nervous system (CNS), we hypothesized that CSF outflows from the lumbar spinal canal. [...] Read more.
Intrinsic cerebrospinal fluid (CSF) dynamics in the brain have been extensively studied, particularly the egress sites of tagged intrinsic CSF in the meninges. Although spinal CSF recirculates within the central nervous system (CNS), we hypothesized that CSF outflows from the lumbar spinal canal. We aimed to visualize and semi-quantify the outflow using non-contrast MRI techniques. We utilized a 3 Tesla clinical MRI with a 16-channel spine coil, employing time–spatial labeling inversion (Time-SLIP) with tag-on and tag-off acquisitions, T2-weighted coronal 2D fluid-attenuated inversion recovery (FLAIR) and T2-weighted coronal 3D centric ky-kz single-shot FSE (cSSFSE). Images were acquired using time–spatial labeling inversion pulse (Time-SLIP) with tag-on and tag-off acquisitions with varying TI periods. Ten healthy volunteers with no known spinal diseases participated. Variations in tagged CSF outflow were observed across different thoracolumbar nerve root segments in all participants. We quantified CSF outflow at all lumbar levels and the psoas region. There was no significant difference among the ROIs for signal intensity. The tagged CSF outflow from the spinal canal is small but demonstrates egress to surrounding tissues. This finding may pave the way for exploring intrathecal drug delivery, understanding of CSF-related pathologies and its potential as a biomarker for peripheral neuropathy and radiculopathy. Full article
(This article belongs to the Special Issue Advancements in Medical Imaging Technology)
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