AI for surgical planning
While the application of artificial intelligence is incredibly broad, it has found particular success in the field of image analysis including image classification and object recognition. This application of AI has particular significance in preoperative planning, where patient scans can be analysed to improve diagnosis and optimise procedures.
Examples of such applications include the detection of polyps from colonoscopy procedures, as well as powering intraoperative augmented reality systems, identifying anatomical landmarks in real-time to improve surgical outcomes.
Transcatheter aortic valve implantation (TAVI) is a procedure performed on patients with severe aortic stenosis who are often deemed to have a high risk of mortality from standard surgical aortic valve replacement. TAVI is a relatively new surgical procedure, however, the number of TAVI procedures is rapidly rising in the UK, from under 2000 in 2013/14 to over 7500 in 2022/23. Additionally, the relative number of urgent cases is rising, from 17% in 2016/17 to 25% in 2022/23. While TAVI procedures are relatively common, the 30-day mortality rate is 1.3% overall and 3.1% for urgent cases. With the large increase in procedures and significant mortality rate, there is a clear need for improved surgical planning to ensure that as this procedure becomes more common the associated complications are reduced.
DASI Simulations, based in Dublin, Ohio, have developed a surgical planning software which leverages AI to improve the planning of TAVI surgery.
The DASI system not only provides a computational model of a patient’s heart from CT angiogram images by identifying and measuring cardiac structures, but in addition, the system can provide interactive simulations results, predicting surgical outcomes across a range of scenarios.
This is an extremely powerful tool for surgeons given that the TAVI procedure requires decisions on the optimal valve type, size and position, all of which can be investigated using the DASI system.
DASI Simulations was founded as a start-up in 2019 in collaboration with Ohio State University. Through rapid development of their products, they have gained FDA approval for both their Precision TAVI (simulating surgical outcomes) and DASI Dimensions (measuring cardiac structures) software, as well as being used in over 80 hospitals in the US.
DASI have 4 published patent families, with the earliest filing being in June 2021. Given their Ohio base and the large market size, it is no surprise that DASI filed their first applications in the US.
In order to pursue protection abroad, they subsequently filed corresponding PCT applications.
So far, only 1 of the 4 PCT applications has reached the 30/31 month deadline to enter the national/regional phase. In this one case, DASI have entered the national/regional phase in Australia, Canada, Europe and Japan, following a typical patent filing strategy targeting the major healthcare markets.
The US case in this family (US2022392642A1) faced a series of challenges at the USPTO, with the first office action rejecting the claims due to non-patentable subject matter, lack of sufficiency and clarity, and obviousness. A series of amendments to the independent claims was made in a single response, successfully overcoming all rejections, such that a notice of allowance was issued less than 5 months after the first office action. It remains to be seen if DASI follow this approach in other jurisdictions. Decisive factors in DASI’s patent strategy of pursuing patent protection domestically and abroad are likely to be the rapid increase in TAVI procedures, as well as the fast-moving nature of AI related systems.
For those operating in the AI MedTech sector, there is significant opportunity to leverage AI for image analysis, allowing the generation of accurate patient-specific models. As shown by DASI Simulations, these models can then be used to further support surgeons by providing prediction capabilities. This is of particular relevance in relatively new procedures such as TAVI surgery.
Regarding patent strategy, due to the fast-paced nature of the industry, gaining rapid patent protection can be key to establishing one’s position in the market. As illustrated in the above example, sufficiency and excluded subject matter can present significant challenges in patenting AI inventions. As such, applicants must carefully balance patentability requirements with considerations around drafting and prosecution and a desire for rapid grant, to obtain a commercially valuable claim scope.
"The MedTech industry has an extremely fast-paced nature, gaining rapid patent protection can be key to establishing one’s position in the market."
LET'S TALK
Joe Egelstaff - Patent Technical Assistant
© 2025 Mewburn Ellis
