Applied Sciences

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Special Issue Information

Dear Colleagues,

Magnetic resonance imaging (MRI) is an important method to examine the human brain for research and clinical purposes. This Special Issue invites various studies on anatomy, physiology, and clinical applications regarding the MRI of the human brain. For example, virtual surgery on deep brain stimulation, automated segmentation technique, or 3D modeling will be interesting topics. New perspectives on MRI will be incredibly beneficial to researchers in the field and to patients.

Dr. Beom Sun Chung
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

anatomy
brain
deep brain stimulation
magnetic resonance imaging

Published Papers (2 papers)

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Research

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14 pages, 2351 KiB

Open AccessArticle

Assessment of Bone Mineral Density from Lumbosacral MRI: A Retrospective Study with Texture Analysis Radiomics

by Giulio Vara, Paolo Spinnato, Giancarlo Facchini, Marco Miceli, Francesco Ursini, Luca Spinardi, Gianfranco Vornetti and Stefano Ratti

Appl. Sci. 2023, 13(10), 6305; https://doi.org/10.3390/app13106305 - 22 May 2023

Cited by 2 | Viewed by 1358

Abstract

Osteoporosis is a common condition characterized by low bone mineral density (BMD) and deterioration of bone microarchitecture, leading to increased risk of fractures. Early diagnosis and treatment of osteoporosis are critical for preventing fractures and their associated morbidity and mortality. Currently, dual-energy X-ray absorptiometry (DXA) is the gold standard for assessing BMD; however, it has limitations such as radiation exposure, cost, and limited availability in certain regions. Magnetic resonance imaging (MRI) of the lumbar spine is routinely performed for various indications, and it provides high-resolution images of the bone and tissue without ionizing radiation. Recently, texture analysis (TA) of MRI images has shown promise in assessing BMD by quantifying the spatial distribution and heterogeneity of bone marrow fat and trabecular bone. In this article, we present our experience with the opportunistic use of lumbar spine MRI for BMD assessment using TA, and we compare the results with DXA measurements. We also discuss the potential clinical implications of this approach, including its use in patients who cannot undergo DXA or in whom BMD assessment is not routinely performed. MRI should provide information in a single examination in regard to degenerative disk pathology and arthritis, with the addition of BMD prediction. Full article

(This article belongs to the Special Issue Medical Magnetic Resonance Imaging (MRI) Techniques and Applications)

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Other

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14 pages, 19506 KiB

Open AccessSystematic Review

A Systematic Review and Meta-Analysis of the Grey Matter Volumetric Changes in Mild Traumatic Brain Injuries

by Ioannis Mavroudis, Symela Chatzikonstantinou, Alin Ciobica, Ioana-Miruna Balmus, Alin Iordache, Dimitrios Kazis, Rumana Chowdhury and Alina-Costina Luca

Appl. Sci. 2022, 12(19), 9954; https://doi.org/10.3390/app12199954 - 3 Oct 2022

Cited by 4 | Viewed by 1824

Abstract

Traumatic brain injury (TBI) is currently a problematic issue of public health due to its frequency, and many of the mild cases often remain undiagnosed despite the possible predisposition to prolonged or persistent post-concussive symptomatology. It was shown here that the severity and persistence of grey matter (GM) changes following TBI could predict disease outcomes. Our aim was to conduct a voxel-wise meta-analysis to detect significant GM changes following mild TBI (mTBI) and to investigate whether these changes are associated with the duration and severity of post-concussion syndrome (PCS). A voxel-wise meta-analysis was conducted regarding the GM and white matter (WM) changes in mTBI adult patients versus healthy controls, and Seed-based d Mapping was used to correlate the data. Standard meta-analysis statistical processing was used to assess heterogeneity and publication bias. Our analysis showed significant GM volume increases in the left medial cingulate/paracingulate gyri, the middle frontal gyrus, and the right caudate nucleus of the mTBI patients and significant volume loss in the thalamus, the frontal lobe, and the temporal lobe. These changes could potentially be associated with PCS that some mTBI later patients develop as a result to the injury or other compensatory changes. Additional studies considering long-term GM changes in mTBI patients and their potential relationship to PCS could provide further insight into the pathophysiological similarities and correlations between mTBI and PCS. Full article

(This article belongs to the Special Issue Medical Magnetic Resonance Imaging (MRI) Techniques and Applications)

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