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Brain Sciences
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Frontiers in Diagnostic Neuroradiology
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Frontiers in Diagnostic Neuroradiology

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 5740

Special Issue Editor

Dr. Daniel Ginat

E-Mail Website
Guest Editor
Department of Radiology, The University of Chicago, Chicago, IL, USA
Interests: neuroradiology; quantitative imaging; artificial intelligence; radiomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neuroimaging has played an important in the characterization of a wide array of conditions, including tumors, inflammation, infection, demyelinating diseases, cerebrovascular diseases, and traumatic brain injury. We are in the midst of a paradigm shift in how neuroimaging is acquired, processed, and interpreted, with an increasing influence of novel techniques that are intended to derive the most useful information from imaging in an objective manner. The aim of this Special Issue is to showcase recent advances in neuroimaging, with an emphasis on CT and MRI. The Special Issue encompasses neuroimaging applications of relatively novel techniques, such as spectral energy CT, synthetic MRI, artificial intelligence, and radiomics and other quantitative imaging approaches. Original research articles and a limited number of review articles are sought.

Dr. Daniel Ginat
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. Brain Sciences is an international peer-reviewed open access monthly 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 2200 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

  • Neuroradiology
  • Quantitative imaging
  • Artificial intelligence
  • Brain
  • CT
  • MRI

Published Papers (2 papers)

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Research

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6 pages, 635 KiB  
Article
Implementation of Machine Learning Software on the Radiology Worklist Decreases Scan View Delay for the Detection of Intracranial Hemorrhage on CT
by Daniel Ginat
Brain Sci. 2021, 11(7), 832; https://doi.org/10.3390/brainsci11070832 - 23 Jun 2021
Cited by 18 | Viewed by 2532
Abstract
Background and Purpose: Prompt identification of acute intracranial hemorrhage on CT is important. The goal of this study was to assess the impact of artificial intelligence software for prioritizing positive cases. Materials and Methods: Cases analyzed by Aidoc (Tel Aviv, Israel) software for [...] Read more.
Background and Purpose: Prompt identification of acute intracranial hemorrhage on CT is important. The goal of this study was to assess the impact of artificial intelligence software for prioritizing positive cases. Materials and Methods: Cases analyzed by Aidoc (Tel Aviv, Israel) software for triaging acute intracranial hemorrhage cases on non-contrast head CT were retrospectively reviewed. The scan view delay time was calculated as the difference between the time the study was completed on PACS and the time the study was first opened by a radiologist. The scan view delay was stratified by scan location, including emergency, inpatient, and outpatient. The scan view delay times for cases flagged as positive by the software were compared to those that were not flagged. Results: A total of 8723 scans were assessed by the software, including 6894 cases that were not flagged and 1829 cases that were flagged as positive. Although there was no statistically significant difference in the scan view time for emergency cases, there was a significantly lower scan view time for positive outpatient and inpatient cases flagged by the software versus negative cases, with a reduction of 604 min on average, 90% in the scan view delay (p-value < 0.0001) for outpatients, and a reduction of 38 min on average, and 10% in the scan view delay (p-value <= 0.01) for inpatients. Conclusion: The use of artificial intelligence triage software for acute intracranial hemorrhage on head CT scans is associated with a significantly shorter scan view delay for cases flagged as positive than cases not flagged among outpatients and inpatients at an academic medical center. Full article
(This article belongs to the Special Issue Frontiers in Diagnostic Neuroradiology)
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Review

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33 pages, 4964 KiB  
Review
Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer’s Disease
by Anna Orzyłowska and Wendy Oakden
Brain Sci. 2022, 12(1), 53; https://doi.org/10.3390/brainsci12010053 - 30 Dec 2021
Cited by 4 | Viewed by 2421
Abstract
Alzheimer’s disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of [...] Read more.
Alzheimer’s disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease. Full article
(This article belongs to the Special Issue Frontiers in Diagnostic Neuroradiology)
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