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Novel Technologies in Radiology: Diagnosis, Prediction and Treatment

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 1000

Special Issue Editors


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Guest Editor
Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
Interests: Monte Carlo simulation; DNA damage; PET

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Guest Editor
Department of Radiation Oncology, Washington University at St Louis, 4511 Forest Park Avenue, St. Louis, MO 63108, USA
Interests: low-dimensional semiconductor; heterostructures; MR imaging reconstruction; ultra-low-field MRI system

Special Issue Information

Dear Colleagues,

With its roots traced back to the discovery of X-rays in 1895, radiology has undergone profound advancements, evolving into a cornerstone of modern medicine. Yet, it is still an active field. On the one side, emerging technologies such as artificial intelligence (AI) have provided insights to improve the quality of diagnosis and prediction by radiology. On the other side, the emphasis on precision therapy and personalized medicine brings challenges to radiology, prompting the field to innovate and develop new protocols or technologies. We therefore set up this Special Issue, which aims to collect cutting-edge advancements in technology and protocol design that may significantly enhance our diagnostic and predictive capabilities and eventually benefit the clinic to facilitate researchers.

We are pleased to invite researchers from various fields within this journal’s scope to contribute to this Special Issue or invite relevant experts and colleagues to do so. Both original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Novel design of devices, algorithms, and protocols.
  • Radiology and AI.
  • Radiology and personalized medicine.
  • Interventional radiology.
  • Molecular imaging.
  • Radiology and predictive medicine.

We look forward to receiving your contributions.

Dr. Youfang Lai
Dr. Yuting Peng
Guest Editors

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

  • deep learning
  • imaging guidance
  • PET
  • molecular imaging
  • imaging-based biomarkers

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Published Papers (1 paper)

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Research

13 pages, 1130 KiB  
Article
Radiological Reporting Systems in Multiple Sclerosis
by Alessandra Scaravilli, Mario Tranfa, Giuseppe Pontillo, Antonio Carotenuto, Caterina Lapucci, Riccardo Nistri, Elisabetta Signoriello, Marcello Moccia, Carla Tortorella, Ruggero Capra, Giacomo Lus, Matilde Inglese, Claudio Gasperini, Roberta Lanzillo, Carlo Pozzilli, Vincenzo Brescia Morra, Arturo Brunetti, Maria Petracca and Sirio Cocozza
Appl. Sci. 2024, 14(13), 5626; https://doi.org/10.3390/app14135626 - 27 Jun 2024
Cited by 1 | Viewed by 713
Abstract
(1) Background: Although MRI is a well-established tool in Multiple Sclerosis (MS) diagnosis and management, neuroradiological reports often lack standardization and/or quantitative information, with possible consequences in clinical care. The aim of this study was to evaluate the impact of information provided by [...] Read more.
(1) Background: Although MRI is a well-established tool in Multiple Sclerosis (MS) diagnosis and management, neuroradiological reports often lack standardization and/or quantitative information, with possible consequences in clinical care. The aim of this study was to evaluate the impact of information provided by neuroradiological reports and different reporting systems on the clinical management of MS patients. (2) Methods: An online questionnaire was proposed to neurologists working in Italian tertiary care level MS centers. Questions assessed the impact of different MRI-derived biomarkers on clinical choices, the preferred way of receiving radiological information, and the neurologists’ opinions about different reporting systems and the use of automated software in clinical practice. (3) Results: The online survey was completed by 62 neurologists. New/enlarging (100%) lesions, the global T2w/FLAIR lesion load (96.8%), and contrast-enhancing (95.2%) lesions were considered the most important biomarkers for therapeutic decision, while new/enlarging lesions (98.4%), global T2w/FLAIR lesion load (96.8%), and cerebral atrophy (90.3%) were relevant to prognostic evaluations. Almost all participants (98.4%) considered software for medical imaging quantification helpful in clinical management, mostly in relation to prognostic evaluations. (4) Conclusions: These data highlight the impact of providing accurate and reliable data in neuroradiological reports. The use of software for medical imaging quantification in MS can be helpful to standardize radiological reports and to provide useful clinical information to neurologists. Full article
(This article belongs to the Special Issue Novel Technologies in Radiology: Diagnosis, Prediction and Treatment)
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