Special Issue "Diagnostic Imaging of Cardiovascular Disease in Small Animals"

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Veterinary Clinical Studies".

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Dr. Alessia Diana
E-Mail Website
Guest Editor
Alma Mater Studiorum- Università di Bologna, Bologna, Italy
Interests: small animals cardiovascular imaging; contrast enhanced ultrasonography; thoracic radiography; cardiovascular disease
Prof. Dr. Carlo Guglielmini
E-Mail Website
Guest Editor
Department of Animal Medicine, Production and Health, University of Padova, 35020 Padua, Italy
Interests: veterinary cardiology; cardiovascular imaging; echocardiography; cardiac arrhythmia

Special Issue Information

Dear Colleagues,

The theme of this Special Issue of Animals is Diagnostic Imaging of Cardiovascular Disease in Small Animals. Cardiovascular disease has always been an important field of application for diagnostic imaging in small animal practice. Thoracic radiography was the first technique employed and it still plays a fundamental role in the diagnosis of heart failure of both dogs and cats. Successively, the widespread use of diagnostic ultrasound and, successively, computed tomography (CT) and magnetic resonance imaging (MRI) has greatly enhanced our understanding of cardiac anatomy and function allowing an even greater ability to assess even subtle cardiac dysfunction. More recently, the application of deep learning artificial intelligence (AI) technique to thoracic radiographs seems to offer an important new perspective for the early recognition of cardiac enlargement also in small animals. All studies focused on the different diagnostic procedures (i.e., survey radiography, angiography, ultrasonography, contrast enhancement ultrasonography, echocardiography, CT, MRI and AI) applied to cardiovascular anatomy and diseases of small animals are welcome and will be carefully considered for publication. The purpose of this Special Issue is to collect a group of papers on the topic of Diagnostic Imaging of Cardiovascular Disease to emphasize both the usefulness of consolidated imaging techniques and future solutions due to technological advancement.

Prof. Alessia Diana
Prof. Carlo Guglielmini
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 papers will be 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. Animals 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 1800 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

  • angiography
  • artificial intelligence (AI)
  • cardiovascular disease
  • computed tomography (CT)
  • contrast enhancement ultrasonography (CEUS)
  • echocardiography
  • magnetic resonance imaging (MRI)
  • small animals
  • survey radiography

Published Papers (2 papers)

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Editorial

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Editorial
Diagnostic Imaging of Cardiovascular Disease in Small Animals
Animals 2020, 10(12), 2392; https://doi.org/10.3390/ani10122392 - 15 Dec 2020
Viewed by 552
Abstract
Cardiovascular disease (CVD) has always been an important field of application for diagnostic imaging in small animal practices and, vice-versa, diagnostic imaging has greatly expanded the diagnostic capabilities of veterinary clinicians dealing with CVD [...] Full article
(This article belongs to the Special Issue Diagnostic Imaging of Cardiovascular Disease in Small Animals)

Other

Jump to: Editorial

Case Report
Unusual Presentation of Aortic Valve Infective Endocarditis in a Dog: Aorto-Cavitary Fistula, Tricuspid Valve Endocarditis, and Third-Degree Atrioventricular Block
Animals 2021, 11(3), 690; https://doi.org/10.3390/ani11030690 - 04 Mar 2021
Viewed by 372
Abstract
A 2-year-old Boxer with a history of subaortic stenosis and immunosuppressant therapy developed aortic valve infective endocarditis. On echocardiographic examination with simultaneous electrocardiographic tracing, multiple uncommon periannular complications of the aortic valve endocarditis were found, including aorto-cavitary fistula with diastolic left-to-right shunt, tricuspid [...] Read more.
A 2-year-old Boxer with a history of subaortic stenosis and immunosuppressant therapy developed aortic valve infective endocarditis. On echocardiographic examination with simultaneous electrocardiographic tracing, multiple uncommon periannular complications of the aortic valve endocarditis were found, including aorto-cavitary fistula with diastolic left-to-right shunt, tricuspid valve endocarditis, and third-degree atrioventricular block. Necropsy confirmed the above echocardiographic findings. Although aortic valve endocarditis represents a well-known disease entity in dogs, the dynamic nature of this condition may allow development of complex and uncommon echocardiographic features. Full article
(This article belongs to the Special Issue Diagnostic Imaging of Cardiovascular Disease in Small Animals)
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