Non-contact optical imaging of tissue deformation enables in vivo cardiovascular monitoring
Lefebvre, A. T.; Steiner, N. E.; Wang, S.; Rodriguez, C. L.; Bar-Kochba, E.; Shi, Y.; Cho, S.-M.; Blodgett, D. W.; Mirski, M.
Show abstract
Significance: Continuous, non-invasive monitoring of cardiovascular physiology provides critical information for clinical decision-making and patient care. Emerging optical sensors enable non-contact measurement of physiological parameters such as heart rate and respiratory rate, but current methods are limited in their ability to capture spatially resolved physiological waveforms. Aim: We aimed to extend the capabilities of non-contact cardiovascular monitoring by using an imaging-based approach from which spatially resolved physiological waveforms can be extracted and cardiovascular biomarkers can be derived in vivo. Approach: We implemented a digital holographic imaging sensor to continuously measure calibrated tissue motion for in vivo assessment of cardiovascular biomarkers in six adult male Sprague-Dawley rats, with validation against electrocardiographic and invasive arterial blood pressure measurements. Results: Heart rate and pulse arrival time-derived pulse wave velocity calculated from digital holographic imaging demonstrate strong agreement with reference-derived metrics (concordance correlation coefficient [≥] 0.98). Heart rate variability shows moderate agreement with reference-derived metrics (concordance correlation coefficient [≥] 0.59).
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Development and evaluation of a wearable peripheral vascular compensation sensor in a swine model of hemorrhage 94%
- Characterization of a fiber-coupled SPAD camera system for deep-tissue blood-flow measurement using diffuse correlation spectroscopy 94%
- Interferometric imaging of thermal expansion for temperature control in retinal laser therapy 93%
Similar papers in this journal
- Method for in vivo assessment of cancer tissue inhomogeneity and accurate histology-like morphological segmentation based on Optical Coherence Elastography 92%
- Clinical characterization of respiratory droplet production during common airway procedures using high-speed imaging 92%
- Machine learning-enabled cancer diagnostics with widefield polarimetric second-harmonic generation microscopy 92%
Similar papers in this journal
- A Sparse Deep Learning Approach for Automatic Segmentation of Human Vasculature in Multispectral Optoacoustic Tomography 93%
- Ultrasound-guided Photoacoustic image Annotation Toolkit in MATLAB (PHANTOM) for preclinical applications 92%
- In-bore MRI-compatible Transrectal Ultrasound and Photoacoustic Imaging 92%
Similar papers in this journal
- A coupled atrioventricular-aortic setup for in-vitro hemodynamic study of the systemic circulation: Design, Fabrication, and Physiological relevancy 91%
- Open-Source Low-Cost Cardiac Optical Mapping System 91%
- Toward Automated Classification of Pathological Transcranial Doppler Waveform Morphology via Spectral Clustering 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.