Special Issue Information

Dear Colleagues,

As Editor-in-Chief of Tomography, I am pleased to announce a new Special Issue, entitled “Tomography in 2023”, which aims to comprise a collection of high-quality reviews and original papers from Editorial Board Members or outside leading authors, discussing new knowledge or new cutting-edge developments and the state-of-the-art in imaging science research. Artificial intelligence, patient and professional dose exposure, COVID-19 imaging research, and interventional radiology are welcome topics.

Prof. Dr. Emilio Quaia
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. Tomography 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

artificial intelligence
dose exposure
COVID-19
MR imaging
CT
interventional radiology

Published Papers (2 papers)

Download All Papers

Research

Jump to: Review

Open AccessFeature PaperArticle

Thin PDS Foils Represent an Equally Favorable Restorative Material for Orbital Floor Fractures Compared to Titanium Meshes

Natascha Platz Batista da Silva

and

Tomography 2023, 9(4), 1515-1525; https://doi.org/10.3390/tomography9040121 - 16 Aug 2023

Viewed by 518

Abstract

Orbital floor fractures (OFFs) are common injuries of the midface and may result in long-term complications. The aim of this study was to compare two restoration materials, PDS foils and titanium meshes, with regards to (1) clinical outcome and (2) reduction in orbital volume. The monocentric discovery cohort was analyzed retrospectively and included 476 patients with OFFs treated between 2010 and 2020. A subcohort of 104 patients (study cohort) with isolated OFFs and available high-resolution imaging material was used for volume measurements. Postoperative complications were not significantly different between patients treated with different restoration materials. Prevalence of revision surgery was significantly higher in patients treated with thick PDS foils (25 mm). OFFs treated with PDS foils and titanium meshes showed a significant reduction in orbital volume (p = 0.0422 and p = 0.0056, respectively), however, this volume decrease was significantly less pronounced in patients treated with PDS foils alone (p = 0.0134). Restoration using PDS foil in an isolated OFF reduces the orbital volume to a lesser extent than titanium mesh. Class III patients according to the classification of Jaquiéry with a missing bony ledge medial to the infraorbital fissure particularly benefit from restoration with PDS foils due to a lower reduction in the orbital volume. Regarding short- and long-term postoperative complications, a PDS foil thickness of 0.15 mm appears equivalent to titanium mesh in the treatment of OFFs. Full article

(This article belongs to the Special Issue Tomography in 2023)

► Show Figures

Figure 1

Review

Jump to: Research

Open AccessReview

Neuroimaging Scoring Tools to Differentiate Inflammatory Central Nervous System Small-Vessel Vasculitis: A Need for Artificial Intelligence/Machine Learning?—A Scoping Review

and

Tomography 2023, 9(5), 1811-1828; https://doi.org/10.3390/tomography9050144 - 02 Oct 2023

Viewed by 129

Abstract

Neuroimaging has a key role in identifying small-vessel vasculitis from common diseases it mimics, such as multiple sclerosis. Oftentimes, a multitude of these conditions present similarly, and thus diagnosis is difficult. To date, there is no standardized method to differentiate between these diseases. This review identifies and presents existing scoring tools that could serve as a starting point for integrating artificial intelligence/machine learning (AI/ML) into the clinical decision-making process for these rare diseases. A scoping literature review of EMBASE and MEDLINE included 114 articles to evaluate what criteria exist to diagnose small-vessel vasculitis and common mimics. This paper presents the existing criteria of small-vessel vasculitis conditions and mimics them to guide the future integration of AI/ML algorithms to aid in diagnosing these conditions, which present similarly and non-specifically. Full article

(This article belongs to the Special Issue Tomography in 2023)

Journal Menu

Journal Browser

Special Issue "Tomography in 2023"

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (2 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI