Non-Invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-driven or Model-based?

Yingyu Yang (1) , Stephane Gillon (2) , Jaume Banus (3) , Pamela Moceri (2) , Maxime Sermesant (3)

1 CRISAM - Inria Sophia Antipolis - Méditerranée
2 CHU - Hôpital Pasteur [Nice]
3 EPIONE - E-Patient : Images, données & mOdèles pour la médeciNe numériquE

Right heart catheterisation is considered as the gold standard for the assessment of patients with suspected pulmonary hyper-tension. It provides clinicians with meaningful data, such as pulmonary capillary wedge pressure and pulmonary vascular resistance, however its usage is limited due to its invasive nature. Non-invasive alternatives, like Doppler echocardiography could present insightful measurements of right heart but lack detailed information related to pulmonary vascu-lature. In order to explore non-invasive means, we studied a dataset of 95 pulmonary hypertension patients, which includes measurements from echocardiography and from right-heart catheterisation. We used data extracted from echocardiography to conduct cardiac circulation model per-sonalisation and tested its prediction power of catheter data. Standard machine learning methods were also investigated for pulmonary artery pressure prediction. Our preliminary results demonstrated the potential prediction power of both data-driven and model-based approaches.

Mots clés: Cardiac modelling; Machine learning; Pulmonary hypertension

Domaines: Informatique [cs]; Modélisation et simulation

Yingyu Yang, Stephane Gillon, Jaume Banus, Pamela Moceri, Maxime Sermesant. Non-Invasive Pressure Estimation in Patients with Pulmonary Arterial Hypertension: Data-driven or Model-based?. STACOM 2019 - 10th Workshop on Statistical Atlases and Computational Modelling of the Heart, Oct 2019, Shenzhen, China. ⟨hal-02382941⟩