The core of the HeartFlow Analysis rests on deep learning, computational fluid dynamics and cloud computing. HeartFlow uses deep learning technology applied to image data from a cardiac CTA scan to create a personalised 3D model of the patient’s coronary arteries. We then apply computational fluid dynamics to the model to calculate blood flow and assess the impact of blockages on coronary blood flow. This information aids physicians in the diagnosis of CHD and the determination of optimal treatment. The deep learning and computational fluid dynamics algorithms all run in the cloud, which is necessary in order to provide the HeartFlow Analysis at scale to serve a large population of patients.
HeartFlow also employs web and mobile applications in order to communicate with the hospital IT infrastructure. One important security measure is that only coronary CT image data is sent to HeartFlow in the United States via the cloud for analysis, and any patient identifying information remains in the country of origin. Once the analysis is complete, the 3D model is matched back to the patient identifier information and then sent back to the web interface so that doctors can review their analyses.