Echocardiography as an indication of continuous-time cardiac quiescence

Ultrasound-gated computed tomography coronary angiography: Development of ultrasound transducers with improved computed tomography compatibility

PURPOSE

Cardiovascular disease (CVD) is a leading cause of death worldwide, with coronary artery disease (CAD) accounting for nearly half of all CVD deaths. The current gold standard for CAD diagnosis is catheter coronary angiography (CCA), an invasive, expensive procedure. Computed tomography coronary angiography (CTCA) represents an attractive non-invasive alternative to CCA, however, CTCA requires gated acquisition of CT data during periods of minimal cardiac motion (quiescent periods) to avoid non-diagnostic scans. Current gating methods either expose patients to high levels of radiation (retrospective gating) or lead to high rates of non-diagnostic scans (prospective gating) due to the challenge of predicting cardiac quiescence based on ECG alone. Alternatively, ultrasound (US) imaging has been demonstrated as an effective indicator of cardiac quiescence, however, ultrasound transducers produce prominent streak artifacts that disrupt CTCA scans. In this study, a proof-of-concept array transducer with improved CT-compatibility was developed for utilization in an integrated US-CTCA system.

METHODS

Alternative materials were tested radiographically and acoustically to replace the radiopaque acoustic backings utilized in low frequency (1-4 MHz) cardiac US transducers. The results of this testing were used to develop alternative acoustic backings consisting of varying concentrations of aluminum oxide in an epoxy matrix via simulations. On the basis of these simulations, single element test transducers designed to operate at 2.5 MHz were fabricated, and the performance of these devices was characterized via acoustic and radiographic testing with micro-computed tomography (micro-CT). Finally, a first proof-of-concept cardiac phased array transducer was developed and its US imaging performance was evaluated. Micro-CT images of the developed US array with improved CT-compatibility were compared with those of a conventional array.

RESULTS

Materials testing with micro-CT identified an acoustic backing with a measured radiopacity of 1008 HU, more than an order of magnitude lower than that of the acoustic backing (24,000 HU) typically used in cardiac transducers operating in the 1-4 MHz range. When utilized in a simulated transducer design, this acoustic backing yielded a -6-dB fractional bandwidth of 57%, similar to the 54% bandwidth of the transducer with the radiopaque acoustic backing. The developed 2.5 MHz, single element transducer based on these simulations exhibited a fractional bandwidth of 51% and signal-to-noise ratio (SNR) of 14.7 dB. Finally, the array transducer developed with the acoustic backing having decreased radiopacity exhibited a 56% fractional bandwidth and 10.4 dB single channel SNR, with penetration depth >10 cm in phantom and in vivo imaging using the full array.

CONCLUSIONS

The first attempt at developing a CT-compatible ultrasound transducer is described. The developed CT-compatible transducer exhibits improved radiographic compatibility relative to conventional cardiac array transducers with similar SNR, bandwidth, and penetration depth for US imaging, according to phantom and in vivo cardiac imaging. A CT-compatible US transducer might be used to identify cardiac quiescence and prospectively gate CTCA acquisition, reducing challenges associated with current gating approaches, specifically relatively high rates of non-diagnostic scans for prospective ECG gating and high radiation dose for retrospective gating.

A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating

Dual cardiac and respiratory gating is a well-known technique for motion compensation in nuclear medicine imaging. In this study, we present a new data fusion framework for dual cardiac and respiratory gating based on multidimensional microelectromechanical (MEMS) motion sensors. Our approach aims at robust estimation of the chest vibrations, that is, high-frequency precordial vibrations and low-frequency respiratory movements for prospective gating in positron emission tomography (PET), computed tomography (CT), and radiotherapy. Our sensing modality in the context of this paper is a single dual sensor unit, including accelerometer and gyroscope sensors to measure chest movements in three different orientations. Since accelerometer- and gyroscope-derived respiration signals represent the inclination of the chest, they are similar in morphology and have the same units. Therefore, we use principal component analysis (PCA) to combine them into a single signal. In contrast to this, the accelerometer- and gyroscope-derived cardiac signals correspond to the translational and rotational motions of the chest, and have different waveform characteristics and units. To combine these signals, we use independent component analysis (ICA) in order to obtain the underlying cardiac motion. From this cardiac motion signal, we obtain the systolic and diastolic phases of cardiac cycles by using an adaptive multi-scale peak detector and a short-time autocorrelation function. Three groups of subjects, including healthy controls (n = 7), healthy volunteers (n = 12), and patients with a history of coronary artery disease (n = 19) were studied to establish a quantitative framework for assessing the performance of the presented work in prospective imaging applications. The results of this investigation showed a fairly strong positive correlation (average r = 0.73 to 0.87) between the MEMS-derived (including corresponding PCA fusion) respiration curves and the reference optical camera and respiration belt sensors. Additionally, the mean time offset of MEMS-driven triggers from camera-driven triggers was 0.23 to 0.3 ± 0.15 to 0.17 s. For each cardiac cycle, the feature of the MEMS signals indicating a systolic time interval was identified, and its relation to the total cardiac cycle length was also reported. The findings of this study suggest that the combination of chest angular velocity and accelerations using ICA and PCA can help to develop a robust dual cardiac and respiratory gating solution using only MEMS sensors. Therefore, the methods presented in this paper should help improve predictions of the cardiac and respiratory quiescent phases, particularly with the clinical patients. This study lays the groundwork for future research into clinical PET/CT imaging based on dual inertial sensors.

A novel dual gating approach using joint inertial sensors: implications for cardiac PET imaging

Positron emission tomography (PET) is a non-invasive imaging technique which may be considered as the state of art for the examination of cardiac inflammation due to atherosclerosis. A fundamental limitation of PET is that cardiac and respiratory motions reduce the quality of the achieved images. Current approaches for motion compensation involve gating the PET data based on the timing of quiescent periods of cardiac and respiratory cycles. In this study, we present a novel gating method called microelectromechanical (MEMS) dual gating which relies on joint non-electrical sensors, i.e. tri-axial accelerometer and gyroscope. This approach can be used for optimized selection of quiescent phases of cardiac and respiratory cycles. Cardiomechanical activity according to echocardiography observations was investigated to confirm whether this dual sensor solution can provide accurate trigger timings for cardiac gating. Additionally, longitudinal chest motions originating from breathing were measured by accelerometric- and gyroscopic-derived respiratory (ADR and GDR) tracking. The ADR and GDR signals were evaluated against Varian real-time position management (RPM) signals in terms of amplitude and phase. Accordingly, high linear correlation and agreement were achieved between the reference electrocardiography, RPM, and measured MEMS signals. We also performed a Ge-68 phantom study to evaluate possible metal artifacts caused by the integrated read-out electronics including mechanical sensors and semiconductors. The reconstructed phantom images did not reveal any image artifacts. Thus, it was concluded that MEMS-driven dual gating can be used in PET studies without an effect on the quantitative or visual accuracy of the PET images. Finally, the applicability of MEMS dual gating for cardiac PET imaging was investigated with two atherosclerosis patients. Dual gated PET images were successfully reconstructed using only MEMS signals and both qualitative and quantitative assessments revealed encouraging results that warrant further investigation of this method.

Seismocardiography-Based Cardiac Computed Tomography Gating Using Patient-Specific Template Identification and Detection

To more accurately trigger cardiac computed tomography angiography (CTA) than electrocardiography (ECG) alone, a sub-system is proposed as an intermediate step toward fusing ECG with seismocardiography (SCG). Accurate prediction of quiescent phases is crucial to prospectively gating CTA, which is susceptible to cardiac motion and, thus, can affect the diagnostic quality of images. The key innovation of this sub-system is that it identifies the SCG waveform corresponding to heart sounds and determines their phases within the cardiac cycles. Furthermore, this relationship is modeled as a linear function with respect to heart rate. For this paper, B-mode echocardiography is used as the gold standard for identifying the quiescent phases. We analyzed synchronous ECG, SCG, and echocardiography data acquired from seven healthy subjects (mean age: 31; age range: 22–48; males: 4) and 11 cardiac patients (mean age: 56; age range: 31–78; males: 6). On average, the proposed algorithm was able to successfully identify 79% of the SCG waveforms in systole and 68% in diastole. The simulated results show that SCG-based prediction produced less average phase error than that of ECG. It was found that the accuracy of ECG-based gating is more susceptible to increases in heart rate variability, while SCG-based gating is susceptible to high cycle to cycle variability in morphology. This pilot work of prediction using SCG waveforms enriches the framework of a comprehensive system with multiple modalities that could potentially, in real time, improve the image quality of CTA.