Abstract
Objective:Ultrasound is an effective tool for rapid non-invasive assessment of cardiac structure and function. Determining the cardiorespiratory phases of each frame in the ultrasound video and capturing the cardiac function at a much higher temporal resolution is essential in many applications. Fulfilling these requirements is particularly challenging in preclinical studies involving small animals with high cardiorespiratory rates, requiring cumbersome and expensive specialized hardware.Methods:We present a novel method for the retrospective estimation of cardiorespiratory phases directly from the ultrasound videos. It transforms the videos into a univariate time-series preserving the evidence of periodic cardiorespiratory motion, decouples the signatures of cardiorespiratory motion with a trend extraction technique, and estimates the cardiorespiratory phases using a Hilbert transform approach. We also present a robust nonparametric regression technique for respiratory gating and a novel kernel-regression model for reconstructing images at any cardiac phase facilitating temporal super-resolution.Results:We validated our methods using 2D echocardiography videos and electrocardiogram (ECG) recordings of 6 mice. Our cardiac phase estimation method provides accurate phase estimates with a mean-phase-error-range of 3–6% against ECG derived phase and outperforms three previously published methods in locating ECGs R-wave peak frames with a mean-frame-error-range of 0.73–1.36. Our kernel-regression model accurately reconstructs images at any cardiac phase with a mean-normalized-correlation-range of 0.81–0.85 over 50 leave-one-out-cross-validation rounds.Conclusion and Significance:Our methods can enable tracking of cardiorespiratory phases without additional hardware and reconstruction of respiration-free single cardiac-cycle videos at a much higher temporal resolution.
Highlights
C ARDIOVASCULAR disease is the leading cause of death worldwide and ultrasound is an effective tool for rapid non-invasive assessment of cardiac structure and function [1]– [3]
We present a method for retrospective estimation of instantaneous cardiac and respiratory phases directly from cardiac ultrasound videos
We presented a novel method for retrospective estimation of instantaneous cardio-respiratory phases directly from cardiac ultrasound videos, thereby eliminating the need of additional hardware to track them in, for example, small animal studies
Summary
C ARDIOVASCULAR disease is the leading cause of death worldwide and ultrasound is an effective tool for rapid non-invasive assessment of cardiac structure and function [1]– [3]. Cardiac phase is tracked by a simultaneously acquired ECG or pulse-oximetry signal and respiratory phase is tracked by motion of markers placed on the subject’s body [6]–[8]. Setting up such hardware is cumbersome in pre-clinical studies involving small animals [1]. Previous studies have shown that frame rates of up to 2000–2700 Hz (250–350 frames/cardiac cycle) were required to capture the minute deformations for cardiac strain estimation [11] To achieve such high frame rates, specialized hardware (e.g., retrospective ECG gating, plane wave imaging) has typically been utilized [3], [9], [10]
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