Low-cost screening for future cardiovascular disease incidence with opportunistic CT
Project information
Project duration
-
Project funder
Project coordinator
University of Oulu
Unit and faculty
Contact information
Project leader
- Assistant Professor
- Associate Professor (University Researcher), MSK Radiologist
Project description
This project aims to tackle the challenge of predicting the incidence of future cardiovascular disease (CVD). To date, there exist over 350 models for this purpose, but none of them have found their place in clinical practice since clinical workflows globally may not contain the required data. In this project, we propose to screen for future incidence of CVD opportunistically, relying on abdominal CT images, which are collected routinely in an emergency department. Body composition (BC) can be assessed from these data efficiently, they have been shown to be predictive of CVD and other comorbidities. Using 12 years of imaging, textual and CVD outcomes data, readily available to the team from the Pohde welfare area, we will develop novel trustworthy Deep Learning methods, which have the potential to change current processes of CVD management and save lives globally.