Advances in the Clinical Diagnostics to Equine Back Pain: A Review of Imaging and Functional Modalities

Back pain is common in ridden horses. Back diseases in horses include Impinging Dorsal Spinous Processes, Ventral Spondylosis, Osteoarthritis of Articular Process, Intervertebral Discs Disease, Vertebral Fractures, Conformational Abnormalities, Desmopathy of the Supraspinous Ligament, Desmopathy of the Intraspinous Ligament, and Longissimus Muscle Strain. Back pain may also develop as a result of lameness (particularly hindlimb lameness). A poorly fitting saddle and an unbalanced rider are also considered important factors influencing the development of back pain in horses. The conventional diagnosis of equine back pain includes a clinical examination and diagnostic imaging examination using ultrasound, radiography, and thermography. Advanced diagnostic modalities of equine back pain involve the objectification of standard procedures through the use of algometers, a lameness locator, biometric mats, and the geometric morphometrics method. In addition to modern diagnostic methods, such as computed tomography and scintigraphy, advances in the diagnosis of equine back pain include the use of electromyography and functional electrical stimulation. The aim of this review article is to familiarize clinicians with the usefulness and capabilities of conventional diagnostic protocols and advanced diagnostic modalities. Although orthopedic examination and traditional diagnostic methods will remain the foundation of the diagnosis of back diseases, modern methods meet the growing expectations towards high-performance horses and allow for deeper diagnostics and objective monitoring of rehabilitation and training progress

Causes, Effects and Methods of Monitoring Gas Exchange Disturbances during Equine General Anaesthesia

Horses, due to their unique anatomy and physiology, are particularly prone to intraoperative cardiopulmonary disorders. In dorsally recumbent horses, chest wall movement is restricted and the lungs are compressed by the abdominal organs, leading to the collapse of the alveoli. This results in hypoventilation, leading to hypercapnia and respiratory acidosis as well as impaired tissue oxygen supply (hypoxia). The most common mechanisms disturbing gas exchange are hypoventilation, atelectasis, ventilation–perfusion (V/Q) mismatch and shunt. Gas exchange disturbances are considered to be an important factor contributing to the high anaesthetic mortality rate and numerous post-anaesthetic side effects. Current monitoring methods, such as a pulse oximetry, capnography, arterial blood gas measurements and spirometry, may not be sufficient by themselves, and only in combination with each other can they provide extensive information about the condition of the patient. A new, promising, complementary method is near-infrared spectroscopy (NIRS). The purpose of this article is to review the negative effect of general anaesthesia on the gas exchange in horses and describe the post-operative complications resulting from it. Understanding the changes that occur during general anaesthesia and the factors that affect them, as well as improving gas monitoring techniques, can improve the post-aesthetic survival rate and minimize post-operative complications

From Keratoma to Anaplastic Malignant Melanoma in a Horse’s Hoof

Melanomas in horses are most often associated with gray, older horses with an average age of over 16 years. Anaplastic malignant melanoma, however, can very rarely affect non-gray horses. Herein, we report a case of a 16-year-old Wielkopolski gelding with a chronic lameness caused by a mass in the hoof. The first resection of the lesion and histopathological examination confirmed the presence of a keratoma. The regrown mass and persistent lameness resulted in another mass resection. The second histopathological examination result suggested a neoplastic growth of melanocytic origin with a low histological malignancy. Less than 2 years after the first resection, the horse returned to the clinic with deformation of the hoof capsule and severe lameness. The result of the third histopathological examination indicated low-differentiated malignant neoplasm. The result of the immunohistochemically test indicates a tumor of melanocytic origin with high malignancy

Application of Hyperbaric Oxygen Therapy (HBOT) as a Healing Aid after Extraction of Incisors in the Equine Odontoclastic Tooth Resorption and Hypercementosis Syndrome

Hyperbaric Oxygen Therapy (HBOT) is a stress-free, relatively safe method supporting the treatment of many different diseases. Although it is widely used in human medicine (including dentistry), in veterinary medicine, especially in the treatment of horses, there are not many scientifically described and documented cases of its use. Equine Odontoclastic Tooth Resorption and Hypercementosis syndrome is a disease that affects older horses and significantly reduces their quality of life. The only effective treatment for this condition is extraction of the incisors. The described case compares the recovery process of the alveolar area after extraction of incisors during the course of EOTRH syndrome without and with the use of a chamber, in horses with the same clinical picture of the disease, of the same age, and living in the same conditions. According to the authors’ knowledge, the presented case describes the use of a chamber in equine dentistry for the first time

Selection of Filtering and Image Texture Analysis in the Radiographic Images Processing of Horses’ Incisor Teeth Affected by the EOTRH Syndrome

Equine odontoclastic tooth resorption and hypercementosis (EOTRH) is one of the horses’ dental diseases, mainly affecting the incisor teeth. An increase in the incidence of aged horses and a painful progressive course of the disease create the need for improved early diagnosis. Besides clinical findings, EOTRH recognition is based on the typical radiographic findings, including levels of dental resorption and hypercementosis. This study aimed to introduce digital processing methods to equine dental radiographic images and identify texture features changing with disease progression. The radiographs of maxillary incisor teeth from 80 horses were obtained. Each incisor was annotated by separate masks and clinically classified as 0, 1, 2, or 3 EOTRH degrees. Images were filtered by Mean, Median, Normalize, Bilateral, Binomial, CurvatureFlow, LaplacianSharpening, DiscreteGaussian, and SmoothingRecursiveGaussian filters independently, and 93 features of image texture were extracted using First Order Statistics (FOS), Gray Level Co-occurrence Matrix (GLCM), Neighbouring Gray Tone Difference Matrix (NGTDM), Gray Level Dependence Matrix (GLDM), Gray Level Run Length Matrix (GLRLM), and Gray Level Size Zone Matrix (GLSZM) approaches. The most informative processing was selected. GLCM and GLRLM return the most favorable features for the quantitative evaluation of radiographic signs of the EOTRH syndrome, which may be supported by filtering by filters improving the edge delimitation

Application of Two-Dimensional Entropy Measures to Detect the Radiographic Signs of Tooth Resorption and Hypercementosis in an Equine Model

Dental disorders are a serious health problem in equine medicine, their early recognition benefits the long-term general health of the horse. Most of the initial signs of Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) syndrome concern the alveolar aspect of the teeth, thus, the need for early recognition radiographic imaging. This study is aimed to evaluate the applicability of entropy measures to quantify the radiological signs of tooth resorption and hypercementosis as well as to enhance radiographic image quality in order to facilitate the identification of the signs of EOTRH syndrome. A detailed examination of the oral cavity was performed in eighty horses. Each evaluated incisor tooth was assigned to one of four grade–related EOTRH groups (0–3). Radiographs of the incisor teeth were taken and digitally processed. For each radiograph, two–dimensional sample (SampEn2D), fuzzy (FuzzEn2D), permutation (PermEn2D), dispersion (DispEn2D), and distribution (DistEn2D) entropies were measured after image filtering was performed using Normalize, Median, and LaplacianSharpening filters. Moreover, the similarities between entropy measures and selected Gray–Level Co–occurrence Matrix (GLCM) texture features were investigated. Among the 15 returned measures, DistEn2D was EOTRH grade–related. Moreover, DistEn2D extracted after Normalize filtering was the most informative. The EOTRH grade–related similarity between DistEn2D and Difference Entropy (GLCM) confirms the higher irregularity and complexity of incisor teeth radiographs in advanced EOTRH syndrome, demonstrating the greatest sensitivity (0.50) and specificity (0.95) of EOTRH 3 group detection. An application of DistEn2D to Normalize filtered incisor teeth radiographs enables the identification of the radiological signs of advanced EOTRH with higher accuracy than the previously used entropy–related GLCM texture features