Imaging Techniques and Radiation Therapy in Veterinary Medicine

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

Deadline for manuscript submissions: 31 October 2024 | Viewed by 999

Special Issue Editors


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Guest Editor
Department of Veterinary Medicine, University of Teramo, Località Piano D’ Accio, 64100 Teramo, Italy
Interests: diagnostic imaging; radiology; ultrasound; CT; MRI; PET; radiation therapy
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Guest Editor
Department of Veterinary Medicine, University of Teramo, Località Piano D’ Accio, 64100 Teramo, Italy
Interests: ultrasound; magnetic resonance imaging; radiology; computed tomography

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Guest Editor
IVC Evidensia Small Animal Clinic Hofheim, 65719 Hofheim am Taunus, Germany
Interests: radiation therapy; photodynamic therapy

Special Issue Information

Dear Colleagues,

We are glad to present you this new Animals Special Issue on Imaging Techniques and Radiation Therapy in Veterinary Medicine.

Imaging techniques play a fundamental role in daily practice to achieve a final diagnosis in companion animals and proper treatment plans.

All the available imaging techniques provide specific information, and it is important to choose the proper technique to confirm or exclude the suspected diagnosis.

This Special Issue of Animals aims to collect new advances in Veterinary Imaging Techniques and Radiation Therapy, facilitating a deeper understanding of specific imaging techniques and more effective treatments for companion animals.

Prof. Dr. Massimo Vignoli
Dr. Francesca Del Signore
Dr. Julia Buchholz
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. Animals 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

  • imaging
  • companion animals
  • radiology
  • ultrasound
  • computer tomography
  • magnetic resonance
  • oncology
  • radiation therapy

Published Papers (1 paper)

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Research

11 pages, 2321 KiB  
Article
A New Method to Detect Buffalo Mastitis Using Udder Ultrasonography Based on Deep Learning Network
by Xinxin Zhang, Yuan Li, Yiping Zhang, Zhiqiu Yao, Wenna Zou, Pei Nie and Liguo Yang
Animals 2024, 14(5), 707; https://doi.org/10.3390/ani14050707 - 23 Feb 2024
Viewed by 691
Abstract
Mastitis is one of the most predominant diseases with a negative impact on ranch products worldwide. It reduces milk production, damages milk quality, increases treatment costs, and even leads to the premature elimination of animals. In addition, failure to take effective measures in [...] Read more.
Mastitis is one of the most predominant diseases with a negative impact on ranch products worldwide. It reduces milk production, damages milk quality, increases treatment costs, and even leads to the premature elimination of animals. In addition, failure to take effective measures in time will lead to widespread disease. The key to reducing the losses caused by mastitis lies in the early detection of the disease. The application of deep learning with powerful feature extraction capability in the medical field is receiving increasing attention. The main purpose of this study was to establish a deep learning network for buffalo quarter-level mastitis detection based on 3054 ultrasound images of udders from 271 buffaloes. Two data sets were generated with thresholds of somatic cell count (SCC) set as 2 × 105 cells/mL and 4 × 105 cells/mL, respectively. The udders with SCCs less than the threshold value were defined as healthy udders, and otherwise as mastitis-stricken udders. A total of 3054 udder ultrasound images were randomly divided into a training set (70%), a validation set (15%), and a test set (15%). We used the EfficientNet_b3 model with powerful learning capabilities in combination with the convolutional block attention module (CBAM) to train the mastitis detection model. To solve the problem of sample category imbalance, the PolyLoss module was used as the loss function. The training set and validation set were used to develop the mastitis detection model, and the test set was used to evaluate the network’s performance. The results showed that, when the SCC threshold was 2 × 105 cells/mL, our established network exhibited an accuracy of 70.02%, a specificity of 77.93%, a sensitivity of 63.11%, and an area under the receiver operating characteristics curve (AUC) of 0.77 on the test set. The classification effect of the model was better when the SCC threshold was 4 × 105 cells/mL than when the SCC threshold was 2 × 105 cells/mL. Therefore, when SCC ≥ 4 × 105 cells/mL was defined as mastitis, our established deep neural network was determined as the most suitable model for farm on-site mastitis detection, and this network model exhibited an accuracy of 75.93%, a specificity of 80.23%, a sensitivity of 70.35%, and AUC 0.83 on the test set. This study established a 1/4 level mastitis detection model which provides a theoretical basis for mastitis detection in buffaloes mostly raised by small farmers lacking mastitis diagnostic conditions in developing countries. Full article
(This article belongs to the Special Issue Imaging Techniques and Radiation Therapy in Veterinary Medicine)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Application of palliative hemostatic radiotherapy in oral melanoma: A case report
Authors: Myounghun Kim1, Inseong Jeong2, Gijong Lee2, Cheol Park2, Youngwhan Kim2, Kidong Eom1, Jaehwan Kim1*
Affiliation: 1Department of Veterinary medical imaging, College of Veterinary Medicine, Konkuk University, Seoul, Korea, 05029 2Royal Animal Medical Center, Seoul, Korea, 02140
Abstract: Upon oral examination, a right sided oral mass with continuous bleeding, accompanied by foul odor and severe pain, was identified. Blood analysis revealed severe regenerative anemia (packed cell volume; 18.2%), necessitating a blood transfusion due to the ongoing bleeding. Cytological examination of the oral mass confirmed malignant melanoma, and the owner declined aggressive surgery. The patient received VMAT (Volumetric Modulated Arc Therapy) as part of a palliative radiation protocol, consisting of 6 fractions of 6 Gy administered once a week for the purpose of achieving hemostasis and pain relief. Two days after the initial treatment, the bleeding ceased, and eight days later, the anemia had resolved (packed cell volume; 39.3%). Furthermore, appetite increased after the 2nd treatment, and effective pain management was achieved without the need for analgesics starting from the 4th treatment. Following the final treatment, a follow-up computed tomography (CT) scan revealed an approximately 20% reduction in tumor size, indicating a stable disease response. Although the regional lymph node and lung metastasis were identified, the patient is still alive on the 38th day after the start of radiotherapy, without any further bleeding.

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