Plantar Perfusion Imaging for Peripheral Arterial Disease Screening: A Proof-of-Concept Study

The diagnosis of peripheral artery disease (PAD) typically relies on specialized equipment such as ultrasound. The delayed PAD detection of these approaches may lead to amputation and even death. To achieve rapid and ubiquitous PAD screening, we propose a novel concept of camera-based plantar perfusion imaging (CPPI) for PAD diagnosis and severity classification. Specifically, we performed a simulation trial that used an RGB camera to record the plantar video of 20 subjects and a cuff with different pressures applied to the left leg to simulate different degrees of lower limb blockage. We generated the plantar perfusion maps using remote photoplethysmography imaging and proposed a multi-view perfusion (MVP) feature set to represent the perfusion maps for PAD classification. The experimental results show that the Pearson correlation coefficients between MVP and Doppler ultrasound (clinical reference) features were larger than 0.9. MVP feature combined with Support Vector Machine obtains 91.47% accuracy in distinguishing the normal and obstructed states, and 76.48% accuracy in differentiating four different degrees of vascular obstruction. The clinical benchmark demonstrated the potential of CPPI as a rapid, sensitive, and easy-to-use diagnostic tool for PAD, suitable for large-scale screening in home or community settings.