A Novel Spectral Index for Tracking Preload Change from a Wireless, Wearable Doppler Ultrasound.
Jon-Émile Stuart KennyZhen YangGeoffrey ClarkeMai ElfarnawanyChelsea E MundingAndrew M EiblJoseph K EiblJenna L TaylorChul-Ho KimBruce D JohnsonPublished in: Diagnostics (Basel, Switzerland) (2023)
A wireless, wearable Doppler ultrasound offers a new paradigm for linking physiology to resuscitation medicine. To this end, the image analysis of simultaneously-acquired venous and arterial Doppler spectrograms attained by wearable ultrasound represents a new source of hemodynamic data. Previous investigators have reported a direct relationship between the central venous pressure (CVP) and the ratio of the internal jugular-to-common carotid artery diameters. Because Doppler power is directly related to the number of red cell scatterers within a vessel, we hypothesized that (1) the ratio of internal jugular-to-carotid artery Doppler power (V/A POWER ) would be a surrogate for the ratio of the vascular areas of these two vessels and (2) the V/A POWER would track the anticipated CVP change during simulated hemorrhage and resuscitation. To illustrate this proof-of-principle, we compared the change in V/A POWER obtained via a wireless, wearable Doppler ultrasound to B-mode ultrasound images during a head-down tilt. Additionally, we elucidated the change in the V/A POWER during simulated hemorrhage and transfusion via lower body negative pressure (LBNP) and release. With these Interesting Images , we show that the Doppler V/A POWER ratio qualitatively tracks anticipated changes in CVP (e.g., cardiac preload) which is promising for both diagnosis and management of hemodynamic unrest.
Keyphrases
- blood flow
- magnetic resonance imaging
- ultrasound guided
- deep learning
- cardiac arrest
- heart rate
- optical coherence tomography
- left ventricular
- contrast enhanced ultrasound
- cardiopulmonary resuscitation
- cardiac surgery
- computed tomography
- blood pressure
- mesenchymal stem cells
- atrial fibrillation
- magnetic resonance
- convolutional neural network