Veterinary imaging is a branch of advanced veterinary medicine that helps obtain medical images of animals for disease diagnosis in companion animals, livestock animals, large animals, and others. The economic analysis of animal disease outbreaks has been conventionally focused on the assessment of direct costs linked to veterinary service expenditures, health risks, disease control reactions, trade losses, and production. According to Inkwood Research, the global veterinary imaging market is anticipated to record a CAGR of 5.86% over the forecast years of 2023-2032.
As per estimations by the Australian Government, a foot & mouth disease outbreak would cost farmers AUD$80 billion in direct expenses over a decade. Furthermore, as per the Food and Agriculture Organization (FAO), following an outbreak of avian influenza in Mexico, the price of eggs increased by 82%. Hence, the need for timely disease diagnoses and treatment is continually rising across the globe.
Modern Veterinary Imaging – The Advent of Advanced Anatomical Diagnostics
Traditional veterinary anatomy mainly relied on detailed dissections of dead animals to generate anatomical illustrations. However, over the years, there have been significant advancements in the development of advanced imaging solutions in veterinary medicine. Moreover, the quality of veterinary diagnostic imaging equipment has also greatly improved, with the wide availability of novel technologies in computed tomography (CT) scanning, ultrasound, and digital radiography.
As per the estimations by the World Organisation for Animal Health (WOAH), one in five farm animals is lost to diseases each year, while several other animals suffer the adverse effects of illnesses. Accordingly, as the animal disease burden rises, modern imaging modalities continue to represent a significant resource that facilitates non-invasive and relatively faster visualizations in living animals for research, diagnostic as well as clinical purposes.
Recent developments made in advanced veterinary imaging, specifically related to nuclear medicine (SPECT, PET), dual imaging modalities (PET/CT, SPECT/CT, and PET/MR), and cross-sectional modalities (MRI and CT), have become widely available, as well, thus resulting in increased demands and expectations from veterinary clients. Aligning with this, the magnetic resonance imaging (MRI) systems segment, under the instrument category, is expected to grow with the highest CAGR during the forecast period, 2023-2032. (Source: Inkwood Research). Furthermore, with around 20% of animals lost to preventable diseases, these modalities can be of considerable value in terms of the propagation of clinical diagnosis as well as anatomical studies.
Scanning the Potential of Veterinary Cancer Diagnosis
On account of the growing prevalence of various diseases, like blood in the abdomen, cysts, arthritis, periodontal diseases, and cancer, the demand for veterinary diagnosis and imaging, particularly in the field of oncology, is increasing. Breast (mammary), skin, bone, mouth (oral), connective tissue (sarcomas), and lymphatic tissue cancers (lymphomas) are most frequently found in pets (Source: MSD Veterinary Manual). The American Veterinary Medical Association (AVMA) also projects that cancer causes nearly 50% of deaths in pets over the age of 10.
In this regard, positron emission tomography (PET) is a technique predominantly used in oncology, cardiology, and neurology research for the detailed evaluation of several diseases. Although PET’s application is mainly focused on oncogenic diseases, various reports also evaluate the use of PET in non-oncologic applications, such as the detection of inflammation related to neurologic conditions, the evaluation of lameness in a dog, and others.
Novel technologies in digital radiography, ultrasound, and computed tomography (CT) scanning are now widely available in veterinary oncology. Likewise, AI-powered image analysis is also helping to identify and monitor the progression of cancer, providing a more personalized approach to treatment. While these developments are set to bolster the demand for veterinary imaging, this factor also plays a pivotal role in positioning the oncology segment as the fastest-growing application during the forecast years 2023-2032.
Future of Veterinary Imaging: Will AI Revolutionize Animal Diagnostics?
Technical advancements have had a tremendous impact on veterinary medicine, especially in the realm of contemporary radiology. Aligning with this, as per Inkwood Research’s analysis, radiography systems is expected to be the dominating instrument in the global veterinary imaging market over the projection period 2023-2032. However, there exists a limited pool of veterinary radiologists, despite the surging need for expert interpretation of radiographs and more advanced diagnostic imaging modalities. This factor, in turn, presents a remarkable opportunity for the development of artificial intelligence (AI) as well as related technologies to save time and resources, better address demand, and potentially improve clinical knowledge and outcomes.
With regard to artificial intelligence in medical imaging, the present realities include facial recognition in cloud photograph albums, automated hand-written character recognition, and context-relevant information displayed on smartphones. Accordingly, major companies and healthcare pioneers are also establishing significant efforts to bolster the adoption of artificial intelligence in the field of veterinary imaging. For instance –
- Fujifilm Sonosite Inc (United States) entered into a strategic partnership with Partners HealthCare, re-branded as Mass General Brigham, one of the leading not-for-profit healthcare systems in the United States. The partnership aims to apply artificial intelligence in order to improve the utility and functionality of portable ultrasound.
- IMV Imaging (United States) provides veterinary and medical-assisted reproduction technologies as well as veterinary imaging. The company also offers artificial intelligence and electronic transmission (AI & ET) centers, in addition to veterinarians and breeders, with consumables and equipment.
- Allen Institute of Artificial Intelligence (AI2) Incubator, the builder of AI-first start-ups, announced a collaboration with Fujifilm Sonosite Inc to interpret ultrasound images with AI. This collaboration is set to enable new ultrasound applications integrated with enhanced accuracy.
Yet, research on the application of AI in veterinary medicine lags far behind the exponential growth in the human field. For example, in 2021 alone, while more than 2000 peer-reviewed papers were published on AI in human diagnostic imaging, only 10 veterinary papers were published in this field, according to global veterinary teleradiology and teleconsulting specialists, VetCT.
Evidently, artificial intelligence, as well as machine learning in veterinary radiology, is a relatively unexploited yet booming area for research and innovation. Subsequently, this aspect provides key players operating in the global veterinary imaging market with lucrative growth prospects.
FAQs:
What are the main functions of diagnostic tools and solutions used by veterinarians?
Veterinarians utilize a variety of tools to diagnose diseases, analyze the response to a particular therapy, monitor disease progression, and screen for the presence of underlying conditions in seemingly healthy animals.
What are the key challenges faced by the global veterinary imaging market?
Although modern imaging modalities are well-established in developed countries worldwide, it is still in the nascent stage across veterinary practices in developing nations. This is primarily accredited to heavy initial investment and high maintenance costs, the need for specialized technical staff and adjustable machines to accommodate the different range of animal sizes, and a lack of expert interpretation.