Automatic Aortic Aneurysm Detection System through Deep-Learning

­An aortic aneurysm is a bulge that occurs in the aorta wall, which carries blood from the heart to the rest of the body. In 2019, aortic aneurysms caused more than 9,000 deaths, with about 60% affecting men. Smoking accounts for the condition's leading risk factor and leads to 75% of all aortic aneurysms. Unfortunately, current diagnostic tools for aortic aneurysms are limited in accuracy and require significant time to evaluate.

This invention describes deep learning software for evaluating and analyzing computed-aided tomography (CT) scans of patients with aortic aneurysms. The software rapidly determines the size of an aneurysm while providing a risk assessment for the patient based on patient history and demographics.

Competitive Advantages

• Automatic analysis of CT scans to determine the size and risk of an aortic aneurysm.
• May reduce the evaluation time of CT scans by up to 50%.
• Does not require a contrast agent for analysis, reducing the amount of radiation to the patient.
• Early detection has the potential to lead to rapid treatment and improved clinical outcomes.

Opportunity

• The market for CT diagnosis of cardiovascular diseases was $2.2 billion in 2017 and is expected to reach $2.8 billion by 2022 at a CAGR of 4.9%. 
• The growing incidence of cardiovascular disease due to unhealthy lifestyles and the rising incidence of metabolic disease is driving the growth of CT imaging.

Rowan University is seeking a partner(s) for further development and potential commercialization of this technology. The inventor is available to collaborate with interested companies.