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Animals
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Imaging Techniques and Radiation Therapy in Veterinary Medicine
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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 3058

Special Issue Editors

Prof. Dr. Massimo Vignoli

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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
Special Issues, Collections and Topics in MDPI journals
Dr. Francesca Del Signore

E-Mail Website
Guest Editor
Department of Veterinary Medicine, University of Teramo, Località Piano D’ Accio, 64100 Teramo, Italy
Interests: ultrasound; magnetic resonance imaging; radiology; computed tomography
Dr. Julia Buchholz

E-Mail Website
Guest Editor
IVC Evidensia Small Animal Clinic Hofheim, 65719 Hofheim am Taunus, Germany
Interests: photodynamic therapy in veterinary oncology and veterinary antimicrobial inactivation

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 (4 papers)

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Research

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11 pages, 946 KiB  
Communication
Optimization of Fair Arterial Spin Labeling Magnetic Resonance Imaging (ASL-MRI) for Renal Perfusion Quantification in Dogs: Pilot Study
by Amber Hillaert, Luis Carlos Sanmiguel Serpa, Yangfeng Xu, Myriam Hesta, Stephanie Bogaert, Katrien Vanderperren and Pim Pullens
Animals 2024, 14(12), 1810; https://doi.org/10.3390/ani14121810 - 17 Jun 2024
Viewed by 452
Abstract
Arterial spin labeling (ASL) MRI allows non-invasive quantification of renal blood flow (RBF) and shows great potential for renal assessment. To our knowledge, renal ASL-MRI has not previously been performed in dogs. The aim of this pilot study was to determine parameters essential [...] Read more.
Arterial spin labeling (ASL) MRI allows non-invasive quantification of renal blood flow (RBF) and shows great potential for renal assessment. To our knowledge, renal ASL-MRI has not previously been performed in dogs. The aim of this pilot study was to determine parameters essential for ALS-MRI-based quantification of RBF in dogs: T1, blood (longitudinal relaxation time), λ (blood tissue partition coefficient) and TI (inversion time). A Beagle was scanned at 3T with a multi-TI ASL sequence, with TIs ranging from 250 to 2500 ms, to determine the optimal TI value. The T1 of blood for dogs was determined by scanning a blood sample with a 2D IR TSE sequence. The water content of the dog’s kidney was determined by analyzing kidney samples from four dogs with a moisture analyzer and was subsequently used to calculate λ. The optimal TI and the measured values for T1,blood, and λ were 2000 ms, 1463 ms and 0.91 mL/g, respectively. These optimized parameters for dogs resulted in lower RBF values than those obtained from inline generated RBF maps. In conclusion, this study determined preliminary parameters essential for ALS-MRI-based RBF quantification in dogs. Further research is needed to confirm these values, but it may help guide future research. Full article
(This article belongs to the Special Issue Imaging Techniques and Radiation Therapy in Veterinary Medicine)
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11 pages, 8471 KiB  
Article
Two-Dimensional Shear-Wave Elastography of the Thyroid in Clinically Healthy Dogs in Different Age Groups
by Denise Jaques Ramos, Tamiris Disselli, Diego Rodrigues Gomes, Luiz Paulo Nogueira Aires, Stéfany Tagliatela Tinto, Diana Villa Verde Salazar, Mariane Magno Ferreira Pereira, Brenda Santos Pompeu de Miranda, Ana Paula Luiz de Oliveira, Bruna Bressianini Lima, Ricardo Andres Ramirez Uscategui and Marcus Antônio Rossi Feliciano
Animals 2024, 14(11), 1528; https://doi.org/10.3390/ani14111528 - 22 May 2024
Viewed by 523
Abstract
The thyroid of dogs has not been extensively studied in 2D shear-wave elastography, making it challenging to apply this technique in the diagnosis of thyroid diseases in a non-invasive manner. The aim of this study is to evaluate the thyroid glands of healthy [...] Read more.
The thyroid of dogs has not been extensively studied in 2D shear-wave elastography, making it challenging to apply this technique in the diagnosis of thyroid diseases in a non-invasive manner. The aim of this study is to evaluate the thyroid glands of healthy dogs using 2D shear-wave elastography in order to establish qualitative and quantitative parameters of tissue stiffness in dogs in different age groups. A total of 31 dogs of various breeds, sexes, and sizes were evaluated. Animals with clinical signs or ultrasound findings indicative of endocrine disease or thyroid lesions were excluded from the study. The shear-wave velocity data in meters per second (m/s) and color elastograms were evaluated and calculated using QelaXto™ 2D software. A healthy thyroid exhibits a blue-color elastogram, indicative of low stiffness. The reference range for the shear-wave velocity of thyroid tissue assessed by 2D shear-wave elastography can be between 1.6 and 2.0 m/s, with a variation of ±0.889 in adult and senior dogs. Full article
(This article belongs to the Special Issue Imaging Techniques and Radiation Therapy in Veterinary Medicine)
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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 1023
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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9 pages, 4715 KiB  
Case Report
Application of Palliative Hemostatic Radiotherapy in Canine Unresectable Oral Melanoma: A Case Report
by Myounghun Kim, Inseong Jeong, Gijong Lee, Cheol Park, Youngwhan Kim, Kidong Eom and Jaehwan Kim
Animals 2024, 14(12), 1746; https://doi.org/10.3390/ani14121746 - 9 Jun 2024
Viewed by 583
Abstract
A 9-year-old castrated male Schnauzer dog, weighing 11.6 kg, presented with a persistent hemorrhagic oral mass. An oral examination revealed a right maxillary oral mass characterized by continuous bleeding, halitosis, and severe pain. A cytological examination led to a provisional diagnosis of malignant [...] Read more.
A 9-year-old castrated male Schnauzer dog, weighing 11.6 kg, presented with a persistent hemorrhagic oral mass. An oral examination revealed a right maxillary oral mass characterized by continuous bleeding, halitosis, and severe pain. A cytological examination led to a provisional diagnosis of malignant melanoma, and, despite the option of aggressive surgery, the owner declined. The blood analysis indicated severe hemorrhagic anemia (hematocrit, 18.2%) requiring a blood transfusion. The patient underwent volumetric modulated arc therapy (VMAT) as part of a palliative radiation protocol, receiving six fractions of 6 Gy weekly for hemostasis and clinical improvement. The hemorrhaging ceased after the second fraction, with a subsequent rise in the hematocrit levels and the resolution of the anemia. Additionally, the intake increased following the second fraction, and effective pain management was achieved in the fourth fraction. Following the last fraction, computed tomography revealed a 20% reduction in the tumor size. This case highlights the potential use of radiotherapy for hemostasis in cases of inoperable hemorrhagic oral melanoma and represents the first report on the application of hemostatic radiotherapy in dogs. Full article
(This article belongs to the Special Issue Imaging Techniques and Radiation Therapy in Veterinary Medicine)
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