Federal Ministry of Education and Research promotes KMU-innovativ project at ICM
As part of the BMBF funding program "KMU-innovativ: Medizintechnik" "Medical technology solutions for digital healthcare", our project AI (artificial intelligence)-based therapy support for cardiology ("ArtiCardio") is funded under the funding code 13GW0208B.
Cardiovascular diseases are the leading cause of death in Germany. The total costs for the treatment of heart valve defects alone amount to 4.6 billion € with 31,000 operations per year. Due to the aging population, the demand will continue to increase in the future. The treating physician makes a treatment decision based on clinical guidelines and individual experience. However, guidelines are general, not evidence-based and do not sufficiently take into account differences between patients.
With the help of innovative software, the physician will be supported in making therapy decisions so that he or she can quickly, efficiently and safely determine the necessity, timing and type of individual therapy. The primary focus is on aortic stenosis, the most common congenital heart defect, and valvular heart defects, the most common acquired heart diseases.
The starting point for digital therapy support is the patient's individual anatomy, which is obtained using magnetic resonance imaging (MRI). Mathematical methods are then used to characterize anatomies and calculate flow conditions in the blood vessels so that the outcome of various surgical therapies can be predicted. Since such calculations cannot currently be performed efficiently either online or on commercially available hardware, a novel method based on artificial intelligence is being researched in this project. This should enable practical and economical integration into everyday clinical practice, so that ultimately every patient can benefit from improved treatment. Individual therapy planning should help to shorten operation times, avoid ineffective therapies or follow-up operations, and thus reduce treatment costs for the healthcare system by up to 30%. The results of the project will also be applicable to other circulatory diseases.
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