F. William Mauldin

A novel ultrasound-based method to evaluate hemostatic function of whole blood

BACKGROUND Unregulated hemostasis represents a leading cause of mortality and morbidity in the developed world. Being able to recognize and quantify defects of the hemostatic process is critical to reduce mortality and implement appropriate treatment. METHODS We describe a novel ultrasound-based technology, named sonorheometry, which can assess hemostasis function from a small sample of blood. Sonorheometry uses the phenomenon of acoustic radiation force to measure the dynamic changes in blood viscoelasticity during clot formation and clot dissolution. We performed in vitro experiments using whole blood samples of 1 ml to demonstrate that sonorheometry is indicative of hemostatic functions that depend on plasma coagulation factors, platelets, and plasma fibrinolytic factors. RESULTS Sonorheometry measurements show titration effects to compounds known to alter the coagulation factors (GPRP peptide, 0 to 8 mmol/l), platelets (abciximab, 0 to 12 microg/ml), and fibrinolytic factors (urokinase, 0 to 200 U). Repeated measurements of blood samples from the same subjects yielded reproducibility errors on the order of 5%. CONCLUSIONS These data indicate that sonorheometry accurately quantifies the functional role of the components of hemostasis in vitro.

Adaptive force sonorheometry for assessment of whole blood coagulation

BACKGROUND Viscoelastic diagnostics that monitor the hemostatic function of whole blood (WB), such as thromboelastography, have been developed with demonstrated clinical utility. By measuring the cumulative effects of all components of hemostasis, viscoelastic diagnostics have circumvented many of the challenges associated with more common tests of blood coagulation. METHODS We describe a new technology, called sonorheometry, that adaptively applies acoustic radiation force to assess coagulation function in WB. The repeatability (precision) of coagulation parameters was assessed using citrated WB samples. A reference range of coagulation parameters, along with corresponding measurements from prothrombin time (PT) and partial thromboplastin time (PTT), were obtained from WB samples of 20 healthy volunteers. In another study, sonorheometry monitored anticoagulation with heparin (0-5 IU/ml) and reversal from varied dosages of protamine (0-10 IU/ml) in heparinized WB (2 IU/ml). RESULTS Sonorheometry exhibited low CVs for parameters: clot initiation time (TC1), <7%; clot stabilization time (TC2), <6.5%; and clotting angle (theta), <3.5%. Good correlation was observed between clotting times, TC1 and TC2, and PTT (r=0.65 and 0.74 respectively; n=18). Linearity to heparin dosage was observed with average linearity r>0.98 for all coagulation parameters. We observed maximum reversal of heparin anticoagulation at protamine to heparin ratios of 1.4:1 from TC1 (P=0.6) and 1.2:1 from theta (P=0.55). CONCLUSIONS Sonorheometry is a non-contact method for precise assessment of WB coagulation.

Real-time targeted molecular imaging using singular value spectra properties to isolate the adherent microbubble signal

Ultrasound-based real-time molecular imaging in large blood vessels holds promise for early detection and diagnosis of various important and significant diseases, such as stroke, atherosclerosis, and cancer. Central to the success of this imaging technique is the isolation of ligand-receptor bound adherent microbubbles from free microbubbles and tissue structures. In this paper, we present a new approach, termed singular spectrum-based targeted molecular (SiSTM) imaging, which separates signal components using singular value spectra content over local regions of complex echo data. Simulations were performed to illustrate the effects of acoustic target motion and harmonic energy on SiSTM imaging-derived measurements of statistical dimensionality. In vitro flow phantom experiments were performed under physiologically realistic conditions (2.7 cm s⁻¹ flow velocity and 4 mm diameter) with targeted and non-targeted phantom channels. Both simulation and experimental results demonstrated that the relative motion and harmonic characteristics of adherent microbubbles (i.e. low motion and large harmonics) yields echo data with a dimensionality that is distinct from free microbubbles (i.e. large motion and large harmonics) and tissue (i.e. low motion and low harmonics). Experimental SiSTM images produced the expected trend of a greater adherent microbubble signal in targeted versus non-targeted microbubble experiments (P < 0.05, n = 4). The location of adherent microbubbles was qualitatively confirmed via optical imaging of the fluorescent DiI signal along the phantom channel walls after SiSTM imaging. In comparison with two frequency-based real-time molecular imaging strategies, SiSTM imaging provided significantly higher image contrast (P < 0.001, n = 4) and a larger area under the receiver operating characteristic curve (P < 0.05, n = 4).

Binding dynamics of targeted microbubbles in response to modulated acoustic radiation force

Detection of molecular targeted microbubbles plays a foundational role in ultrasound-based molecular imaging and targeted gene or drug delivery. In this paper, an empirical model describing the binding dynamics of targeted microbubbles in response to modulated acoustic radiation forces in large vessels is presented and experimentally verified using tissue-mimicking flow phantoms. Higher flow velocity and microbubble concentration led to faster detaching rates for specifically bound microbubbles (p < 0.001). Higher time-averaged acoustic radiation force intensity led to faster attaching rates and a higher saturation level of specifically bound microbubbles (p < 0.05). The level of residual microbubble signal in targeted experiments after cessation of radiation forces was the only response parameter that was reliably different between targeted and control experiments (p < 0.05). A related parameter, the ratio of residual-to-saturated microbubble signal (Rresid), is proposed as a measurement that is independent of absolute acoustic signal magnitude and therefore able to reliably detect targeted adhesion independently of control measurements (p < 0.01). These findings suggest the possibility of enhanced detection of specifically bound microbubbles in real-time, using relatively short imaging protocols (approximately 3 min), without waiting for free microbubble clearance.

REDUCTION OF ECHO DECORRELATION VIA COMPLEX PRINCIPAL COMPONENT FILTERING

Ultrasound motion estimation is a fundamental component of clinical and research techniques that include color flow Doppler, spectral Doppler, radiation force imaging and ultrasound-based elasticity estimation. In each of these applications, motion estimates are corrupted by signal decorrelation that originates from nonuniform target motion across the acoustic beam. In this article, complex principal component filtering (PCF) is demonstrated as a filtering technique for dramatically reducing echo decorrelation in blood flow estimation and radiation force imaging. We present simulation results from a wide range of imaging conditions that illustrate a dramatic improvement over simple bandpass filtering in terms of overall echo decorrelation (< or =99.9% reduction), root mean square error (< or =97.3% reduction) and the standard deviation of displacement estimates (< or =97.4% reduction). A radiation force imaging technique, termed sonorheometry, was applied to fresh whole blood during coagulation, and complex PCF operated on the returning echoes. Sonorheometry was specifically chosen as an example radiation force imaging technique in which echo decorrelation corrupts motion estimation. At 2 min after initiation of blood coagulation, the average echo correlation for sonorheometry improved from 0.996 to 0.9999, which corresponded to a 41.0% reduction in motion estimation variance as predicted by the Cramer-Rao lower bound under reasonable imaging conditions. We also applied complex PCF to improve blood velocity estimates from the left carotid artery of a healthy 23-year-old male. At the location of peak blood velocity, complex PCF improved the correlation of consecutive echo signals from an average correlation of 0.94 to 0.998. The improved echo correlation for both sonorheometry and blood flow estimation yielded motion estimates that exhibited more consistent responses with less noise. Complex PCF reduces speckle decorrelation and improves the performance of ultrasonic motion estimation.

Ultrasound-Based Measurement of Molecular Marker Concentration in Large Blood Vessels: A Feasibility Study

Ultrasound molecular imaging has demonstrated efficacy in pre-clinical studies for cancer and cardiovascular inflammation. However, these techniques often require lengthy protocols because of waiting periods or additional control microbubble injections. Moreover, they are not capable of quantifying molecular marker concentration in human tissue environments that exhibit variable attenuation and propagation path lengths. Our group recently investigated a modulated acoustic radiation force-based imaging sequence, which was found to detect targeted adhesion independent of control measurements. In the present study, this sequence was tested against various experimental parameters to determine its feasibility for quantitative measurements of molecular marker concentration. Results indicated that measurements obtained from the sequence (residual-to-saturation ratio, Rresid) were independent of acoustic pressure and attenuation (p > 0.13, n = 10) when acoustic pressures were sufficiently low. The Rresid parameter exhibited a linear relationship with measured molecular marker concentration (R(2) > 0.94). Consequently, feasibility was illustrated in vitro, for quantification of molecular marker concentration in large vessels using a modulated acoustic radiation force-based sequence. Moreover, these measurements were independent of absolute acoustic reflection amplitude and used short imaging protocols (3 min) without control measurements.

A singular value filter for rejection of stationary artifact in medical ultrasound

A singular value filter (SVF) is proposed for rejection of stationary clutter artifact in medical ultrasound. The SVF approach operates by projecting the original data, consisting of ensembles of complex echo data, onto a new set of bases determined from principal component analysis (PCA) using singular value decomposition (SVD). The efficacy of SVF is based on the principle that a stationary clutter signal, with perfect correlation through ensemble length, can be characterized by only the first PCA basis function, whereas significant energy contribution in the secondary PCA basis functions is necessary to describe motion and decorrelation attributed to underlying tissue structures. In contrast to many other PCA-based filtering approaches, SVF determines filter coefficients adaptively from the singular value spectrum of the original data. It is demonstrated that complex echo data is critical to the efficacy of SVF as it provides singular values that exhibit a monotonic relationship with motion complexity, and thus, provide a good means of identifying local regions of clutter. SVF is compared to a separate PCA-based technique, referred to as the blind source separation (BSS) method, as well as a frequency-based finite impulse response (FIR) clutter filter. Performance is quantified in simulated lesion images and SVF is applied to experimental mouse heart imaging data acquired from a Vevo2100 scanner (VisualSonics, Toronto, Canada) at approximately 30MHz center frequency. In simulation with levels of echo correlation expected in mouse heart imaging (0.70 correlation coefficient), SVF provided superior performance (CNR = 4.5dB) over the standard B-mode image (CNR = 2.3dB), BSS-filtered image (CNR = 3.9dB), and FIR-filtered image (CNR = 3.1dB). When SVF was applied to echo data from mouse heart images, stationary artifacts were reduced or eliminated, which enabled myocardium displacement estimates of the underlying tissue structures.

Handheld Real-Time Volumetric Imaging of The Spine: Technology Development

Abstract Technical difficulties, poor image quality and reliance on pattern identifications represent some of the drawbacks of two-dimensional ultrasound imaging of spinal bone anatomy. To overcome these limitations, this study sought to develop real-time volumetric imaging of the spine using a portable handheld device. The device measured 19.2 cm × 9.2 cm × 9.0 cm and imaged at 5 MHz centre frequency. 2D imaging under conventional ultrasound and volumetric (3D) imaging in real time was achieved and verified by inspection using a custom spine phantom. Further device performance was assessed and revealed a 75-min battery life and an average frame rate of 17.7 Hz in volumetric imaging mode. The results suggest that real-time volumetric imaging of the spine is a feasible technique for more intuitive visualization of the spine. These results may have important ramifications for a large array of neuraxial procedures.

Robust motion estimation using complex principal components

This paper presents a novel motion estimator, termed the principal component displacement estimator (PCDE), which takes advantage of the signal separation capabilities of principal component analysis (PCA) to reject source signals representing decorrelation and noise. PCDE requires the computation of only a single principal component and operates on complex data, yielding computational speed in MATLAB on the same order or better than the commonly used Loupas algorithm. Synthetic ultrasound data were simulated to assess the performance of PCDE over a wide range of conditions. PCDE was also applied to experimental elastography data with reductions in the standard deviation of displacement estimates as large as 67% over other methods.

Decorrelation-based adherent microbubble identification as a faster alternative to singular spectrum-based targeted molecular (SiSTM) imaging of large blood vessels

Ultrasound-based targeted molecular imaging holds promise for early detection and diagnosis of cardiovascular disease and stroke. Current methods used to separate signal from adherent microbubbles are based on frequency domain filtering. Singular spectrum-based targeted molecular (SiSTM) imaging is a recently proposed technique that employ statistical properties, as quantified by the normalized singular spectrum area (NSSA), to more effectively separate signal components in large blood vessels. However, the computational cost to calculate NSSA is high, and thus real-time implementation is challenging. In this paper, flow phantom experiments demonstrated the NSSA-decorrelation patterns caused by different mechanisms: electronic noise, in-beam and out-of-beam movement of scatterers. Results showed that flow rates had little effect on the NSSA-decorrelation pattern caused by out-of-beam decorrelation. Based on the relationship between NSSA and decorrelation (approximately quadratic, adjusted-R2 > 0.86), decorrelation-based adherent microbubble detection was demonstrated to be a faster (2-fold) alternative while maintaining similar performance compared to the NSSA-based method (less than 3% difference).