Machine Independence of Ultrasound-Based Quantification of Vitreous Echodensities.

Purpose: Quantitative ultrasound (QUS) provides objective indices of Vision Degrading Myodesopsia (VDM) that correlate with contrast sensitivity (CS). To date, QUS methods were only tested on a single ultrasound machine. Here, we evaluate whether QUS measurements are machine independent. Methods: In this cross-sectional study, 47 eyes (24 subjects; age = 53.2 ± 14.4 years) were evaluated with Freiburg acuity contrast testing (%Weber), and ultrasonography using 2 machines: one with a 15-MHz single-element transducer and one with a 5-ring, 20-MHz annular-array. Images were acquired from each system in sequential scans. Artifact-free, log-compressed envelope data were processed to yield three parameters (mean amplitude, M; energy, E; and percentage filled by echodensities, P50) and a composite score (C). A B-mode normalization method was applied to the 20-MHz datasets to match QUS parameters at both frequencies. Statistical analyses were performed to evaluate correlations among CS, E, M, P50, and C for both machines. Results: QUS parameters from each machine correlated with CS (R ≥ 0.57, P < 0.001) and there was correlation between machines (R ≥ 0.84, P < 0.001). Correlations between CS and QUS parameters were statistically similar for both machines (P ≥ 0.14) except when the 20-MHz data were normalized (P = 0.04). Reproducibility of QUS parameters computed from 20-MHz data were satisfactory (52.3%-96.3%) with intraclass correlation values exceeding 0.80 (P < 0.001). Conclusions: The high correlation between QUS parameters from both machines combined with a statistically similar correlation to CS suggests QUS is an effective, machine-independent, quantitative measure of vitreous echodensities. Translational Relevance: QUS may be applied across clinical ophthalmic ultrasound scanners and imaging frequencies to effectively evaluate VDM.

Advanced Topics in Quantitative Acoustic Microscopy.

Quantitative acoustic microscopy (QAM) reconstructs two-dimensional (2D) maps of the acoustic properties of thin tissue sections. Using ultrahigh frequency transducers (≥ 100 MHz), unstained, micron-thick tissue sections affixed to glass are raster scanned to collect radiofrequency (RF) echo data and generate parametric maps with resolution approximately equal to the ultrasound wavelength. 2D maps of speed of sound, mass density, acoustic impedance, bulk modulus, and acoustic attenuation provide unique and quantitative information that is complementary to typical optical microscopy modalities. Consequently, many biomedical researchers have great interest in utilizing QAM instruments to investigate the acoustic and biomechanical properties of tissues at the micron scale. Unfortunately, current state-of-the-art QAM technology is costly, requires operation by a trained user, and is accompanied by substantial experimental challenges, many of which become more onerous as the transducer frequency is increased. In this chapter, typical QAM technology and standard image formation methods are reviewed. Then, novel experimental and signal processing approaches are presented with the specific goal of reducing QAM instrument costs and improving ease of use. These methods rely on modern techniques based on compressed sensing and sparsity-based deconvolution methods. Together, these approaches could serve as the basis of the next generation of QAM instruments that are affordable and provide high-resolution QAM images with turnkey solutions requiring nearly no training to operate.

High-frequency ultrasound point-of-care device to quantify myopia-induced microstructural changes in the anterior sclera.

PURPOSE: To develop a point-of-care (POC) device using high-frequency ultrasound (US) for evaluating microstructural changes in the anterior sclera associated with myopia. METHODS: The proposed POC device must satisfy four primary requirements for effective clinical use: the measurement component is handheld; the software must be simple and provide real-time feedback; patient safety and health data security requirements set forth by relevant governing bodies must be satisfied and the measurement data must have sufficient signal-to-noise ratio (SNR) and repeatability. Radiofrequency (RF) echo data acquired by the POC device will be processed using our quantitative US methods to characterise tissue microstructure and biomechanical properties. RESULTS: All stated requirements have been met in the developed POC device. The high-frequency transducer is housed in a custom, 3D-printed, pen-like holder that allows for easy measurements of the anterior sclera. Custom software provides a simple interface for data acquisition, real-time data display and secure data storage. Exposimetry measurements of the US pressure field indicate device compliance with United States Food and Drug Administration limits for ophthalmic US. In vivo measurements on a volunteer suggest the RF data SNR and acquisition consistency are suitable for quantitative analysis. CONCLUSIONS: A fully functioning POC device using high-frequency US has been created for evaluating the microstructure of the anterior sclera. Planned studies using the POC device to scan the eyes of myopia patients will help clarify how the anterior sclera microstructure may be affected by myopia. If effective, this portable, inexpensive and user-friendly system could be an important part of routine eye examinations.

RECURRENT FLOATERS AFTER LIMITED VITRECTOMY FOR VISION DEGRADING MYODESOPSIA.

PURPOSE: Limited vitrectomy improves vision degrading myodesopsia, but the incidence of recurrent floaters postoperatively is not known. We studied patients with recurrent central floaters using ultrasonography and contrast sensitivity (CS) testing to characterize this subgroup and identify the clinical profile of patients at risk of recurrent floaters. METHODS: A total of 286 eyes (203 patients, 60.6 ± 12.9 years) undergoing limited vitrectomy for vision degrading myodesopsia were studied retrospectively. Sutureless 25G vitrectomy was performed without intentional surgical posterior vitreous detachment (PVD) induction. CS (Freiburg Acuity Contrast test: Weber index, %W) and vitreous echodensity (quantitative ultrasonography) were assessed prospectively. RESULTS: No eyes (0/179) with preoperative PVD experienced new floaters. Recurrent central floaters occurred in 14/99 eyes (14.1%) without complete preoperative PVD (mean follow-up = 39 months vs. 31 months in 85 eyes without recurrent floaters). Ultrasonography identified new-onset PVD in all 14 (100%) recurrent cases. Young (younger than 52 years; 71.4%), myopic (≥-3D; 85.7%), phakic (100%) men (92.9%) predominated. Reoperation was elected by 11 patients, who had partial PVD preoperatively in 5/11 (45.5%). At study entry, CS was degraded (3.55 ± 1.79 %W) but improved postoperatively by 45.6% (1.93 ± 0.86 %W, P = 0.033), while vitreous echodensity reduced by 86.6% ( P = 0.016). New-onset PVD postoperatively degraded CS anew, by 49.4% (3.28 ± 0.96 %W; P = 0.009) in patients electing reoperation. Repeat vitrectomy normalized CS to 2.00 ± 0.74%W ( P = 0.018). CONCLUSION: Recurrent floaters after limited vitrectomy for vision degrading myodesopsia are caused by new-onset PVD, with younger age, male sex, myopia, and phakic status as risk factors. Inducing surgical PVD at the primary operation should be considered in these select patients to mitigate recurrent floaters.

Classification of Metastatic Lymph Nodes In Vivo Using Quantitative Ultrasound at Clinical Frequencies.

Quantitative ultrasound (QUS) methods characterizing the backscattered echo signal have been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods have been successful in detecting metastases in surgically excised lymph nodes (LNs), but limited evidence exists regarding the efficacy of QUS for evaluating LNs in vivo at clinical frequencies (2-10 MHz). In this study, a clinical scanner and 10-MHz linear probe were used to collect radiofrequency (RF) echo data of LNs in vivo from 19 cancer patients. QUS methods were applied to estimate parameters derived from the backscatter coefficient (BSC) and statistics of the envelope-detected RF signal. QUS parameters were used to train classifiers based on linear discriminant analysis (LDA) and support vector machines (SVMs). Two BSC-based parameters, scatterer diameter and acoustic concentration, were the most effective for accurately detecting metastatic LNs, with both LDA and SVMs achieving areas under the receiver operating characteristic (AUROC) curve ≥0.94. A strategy of classifying LNs based on the echo frame with the highest cancer probability improved performance to 88% specificity at 100% sensitivity (AUROC = 0.99). These results provide encouraging evidence that QUS applied at clinical frequencies may be effective at accurately identifying metastatic LNs in vivo, helping in diagnosis while reducing unnecessary biopsies and surgical treatments.

Biomechanical changes in myopic sclera correlate with underlying changes in microstructure.

Myopia alters the microstructural and biomechanical properties of the posterior sclera, which is characterized as a layered structure with potentially different inter-layer collagen fibril characteristics. Scanning acoustic microscopy (SAM) has been used to investigate how the micron-scale bulk mechanical properties of the posterior sclera are affected by myopia. Other investigators have employed second harmonic generation (SHG) imaging to characterize the collagen microstructure of tissues. In the present study, SAM and SHG imaging were used to investigate the existence of biomechanically-distinct scleral layers and identify relationships between mechanical properties and tissue microstructure in myopic guinea pig (GP) eyes. Diffusers were worn over the right eyes of six, 1-week-old GPs for one week to induce unilateral form-deprivation myopia. GPs were euthanized, enucleated, and eyes were cryosectioned. Twelve-micron-thick adjacent vertical cryosections were scanned with SAM or SHG. SAM maps of bulk modulus, mass density, and acoustic attenuation were estimated. A fiber-extraction algorithm applied to SHG images estimated collagen fiber length, width, straightness, alignment, and number density. Results revealed that the posterior sclera may exhibit biomechanically distinct layers that are affected differently in myopia. Specifically, a layered structure was observed in the mechanical-parameter maps of control eyes that was less apparent in myopic eyes. Collagen fibers in myopic eyes had smaller diameters and were more aligned. Myopia-associated biomechanical changes were most significant in the outermost and innermost scleral layers. SAM-measured mechanical parameters were correlated with collagen fiber microstructure, particularly fiber length, alignment, and number density, which may imply the biomechanical parameters estimated from SAM measurements are related to tissue microstructure. Interestingly, some changes were greatest in more-peripheral regions, suggesting interventions to strengthen the sclera may be effective away from the optic nerve and efficacy may be achieved best when intervention is applied to the outermost layer.

A data-driven approach to characterizing nonlinear elastic behavior of soft materials.

The Autoprogressive (AutoP) method is a data-driven inverse method that leverages finite element analysis (FEA) and machine learning (ML) techniques to build constitutive relationships from measured force and displacement data. Previous applications of AutoP in tissue-like media have focused on linear elastic mechanical behavior as the target object is infinitesimally compressed. In this study, we extended the application of AutoP in characterizing nonlinear elastic mechanical behavior as the target object undergoes finite compressive deformation. Guided by the prior of nonlinear media, we modified the training data generated by AutoP to speed its ability to learn to model deformations. AutoP training was validated using both synthetic and experimental data recorded from 3D objects. Force-displacement measurements were obtained using ultrasonic imaging from heterogeneous agar-gelatin phantoms. Measurement on samples of phantom components were analyzed to obtain independent measurements of material properties. Comparisons validated the material properties found from neural network constitutive models (NNCMs) trained using AutoP. Results were found to be robust to measurement errors and spatial variations in material properties.

Experimental Validation of Perfusion Imaging With HOSVD Clutter Filters.

Novel pulsed-Doppler methods for perfusion imaging are validated using dialysis cartridges as perfusion phantoms. Techniques that were demonstrated qualitatively at 24 MHz, in vivo, are here examined quantitatively at 5 and 12.5 MHz using phantoms with the blood-mimicking fluid flow within cellulose microfibers. One goal is to explore a variety of flow states to optimize measurement sensitivity and flow accuracy. The results show that 2-3-s echo acquisitions at roughly 10 frames/s yield the highest sensitivity to flows of 1-4 mL/min. A second goal is to examine methods for setting the parameters of higher order singular value decomposition (HOSVD) clutter filters. For stationary or moving clutter, the velocity of the blood-mimicking fluid in the microfibers is consistently estimated within measurement uncertainty (mean coefficient of variation = 0.26). Power Doppler signals were equivalent for stationary and moving clutter after clutter filtering, increasing approximately 3 dB/mL/min of blood-mimicking fluid flow for 0 ≤ q ≤ 4 mL/min. Comparisons between phantom and preclinical images show that peripheral perfusion imaging can be reliably achieved without contrast enhancement.

Physics-guided machine learning for 3-D quantitative quasi-static elasticity imaging.

We present a 3D extension of the Autoprogressive Method (AutoP) for quantitative quasi-static ultrasonic elastography (QUSE) based on sparse sampling of force-displacement measurements. Compared to current model-based inverse methods, our approach requires neither geometric nor constitutive model assumptions. We build upon our previous report for 2D QUSE and demonstrate the feasibility of recovering the 3D linear-elastic material property distribution of gelatin phantoms under compressive loads. Measurements of boundary geometry, applied surface forces, and axial displacements enter into AutoP where a Cartesian neural network constitutive model (CaNNCM) interacts with finite element analyses to learn physically consistent material properties with no prior constitutive model assumption. We introduce a new regularization term uniquely suited to AutoP that improves the ability of CaNNCMs to extract information about spatial stress distributions from measurement data. Results of our study demonstrate that acquiring multiple sets of force-displacement measurements by moving the US probe to different locations on the phantom surface not only provides AutoP with the necessary information for a CaNNCM to learn the 3D material property distribution, but may significantly improve the accuracy of the Young's modulus estimates. Furthermore, we investigate the trade-offs of decreasing the contact area between the US transducer and phantom surface in an effort to increase sensitivity to surface force variations without additional instrumentation. Each of these modifications improves the ability of CaNNCMs trained in AutoP to learn the spatial distribution of Young's modulus from force-displacement measurements.

Data-Driven Elasticity Imaging Using Cartesian Neural Network Constitutive Models and the Autoprogressive Method.

Quasi-static elasticity imaging techniques rely on model-based mathematical inverse methods to estimate mechanical parameters from force-displacement measurements. These techniques introduce simplifying assumptions that preclude exploration of unknown mechanical properties with potential diagnostic value. We previously reported a data-driven approach to elasticity imaging using artificial neural networks (NNs) that circumvents limitations associated with model-based inverse methods. NN constitutive models can learn stress-strain behavior from force-displacement measurements using the autoprogressive (AutoP) method without prior assumptions of the underlying constitutive model. However, information about internal structure was required. We invented Cartesian NN constitutive models (CaNNCMs) that learn the spatial variations of material properties. We are presenting the first implementation of CaNNCMs trained with AutoP to develop data-driven models of 2-D linear-elastic materials. Both simulated and experimental force-displacement data were used as input to AutoP to show that CaNNCMs are able to model both continuous and discrete material property distributions with no prior information of internal object structure. Furthermore, we demonstrate that CaNNCMs are robust to measurement noise and can reconstruct reasonably accurate Young's modulus images from a sparse sampling of measurement data. CaNNCMs are an important step toward clinical use of data-driven elasticity imaging using AutoP.

An information-based machine learning approach to elasticity imaging.

An information-based technique is described for applications in mechanical property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for this purpose. The Autoprogressive method is a computational technique that combines knowledge of object shape and a sparse distribution of force and displacement measurements with finite-element analyses and artificial neural networks to estimate a complete set of stress and strain vectors. Elasticity imaging parameters are then computed from estimated stresses and strains. We introduce the technique using ultrasonic pulse-echo measurements in simple gelatin imaging phantoms having linear-elastic properties so that conventional finite-element modeling can be used to validate results. The Autoprogressive algorithm does not require any assumptions about the material properties and can, in principle, be used to image media with arbitrary properties. We show that by selecting a few well-chosen force-displacement measurements that are appropriately applied during training and establish convergence, we can estimate all nontrivial stress and strain vectors throughout an object and accurately estimate an elastic modulus at high spatial resolution. This new method of modeling the mechanical properties of tissue-like materials introduces a unique method of solving the inverse problem and is the first technique for imaging stress without assuming the underlying constitutive model.

Prediction and suppression of HIFU-induced vessel rupture using passive cavitation detection in an ex vivo model.

BACKGROUND: Occlusion of blood vessels using high-intensity focused ultrasound (HIFU) is a potential treatment for arteriovenous malformations and other neurovascular disorders. However, attempting HIFU-induced vessel occlusion can also cause vessel rupture, resulting in hemorrhage. Possible rupture mechanisms include mechanical effects of acoustic cavitation and heating of the vessel wall. METHODS: HIFU exposures were performed on 18 ex vivo porcine femoral arteries with simultaneous passive cavitation detection. Vessels were insonified by a 3.3-MHz focused source with spatial-peak, temporal-peak focal intensity of 15,690-24,430 W/cm(2) (peak negative-pressure range 10.92-12.52 MPa) and a 50% duty cycle for durations up to 5 min. Time-dependent acoustic emissions were recorded by an unfocused passive cavitation detector and quantified within low-frequency (10-30 kHz), broadband (0.3-1.1 MHz), and subharmonic (1.65 MHz) bands. Vessel rupture was detected by inline metering of saline flow, recorded throughout each treatment. Recorded emissions were grouped into 'pre-rupture' (0-10 s prior to measured point of vessel rupture) and 'intact-vessel' (>10 s prior to measured point of vessel rupture) emissions. Receiver operating characteristic curve analysis was used to assess the ability of emissions within each frequency band to predict vessel rupture. Based on these measurements associating acoustic emissions with vessel rupture, a real-time feedback control module was implemented to monitor acoustic emissions during HIFU treatment and adjust the ultrasound intensity, with the goal of maximizing acoustic power delivered to the vessel while avoiding rupture. This feedback control approach was tested on 10 paired HIFU exposures of porcine femoral and subclavian arteries, in which the focal intensity was stepwise increased from 9,117 W/cm(2) spatial-peak temporal-peak (SPTP) to a maximum of 21,980 W/cm(2), with power modulated based on the measured subharmonic emission amplitude. Time to rupture was compared between these feedback-controlled trials and paired controller-inactive trials using a paired Wilcoxon signed-rank test. RESULTS: Subharmonic emissions were found to be the most predictive of vessel rupture (areas under the receiver operating characteristic curve (AUROC) = 0.757, p < 10(-16)) compared to low-frequency (AUROC = 0.657, p < 10(-11)) and broadband (AUROC = 0.729, p < 10(-16)) emissions. An independent-sample t test comparing pre-rupture to intact-vessel emissions revealed a statistically significant difference between the two groups for broadband and subharmonic emissions (p < 10(-3)), but not for low-frequency emissions (p = 0.058). In a one-sided paired Wilcoxon signed-rank test, activation of the control module was shown to increase the time to vessel rupture (T - = 8, p = 0.0244, N = 10). In one-sided paired t tests, activation of the control module was shown to cause no significant difference in time-averaged focal intensity (t = 0.362, p = 0.363, N = 10), but was shown to cause delivery of significantly greater total acoustic energy (t = 2.037, p = 0.0361, N = 10). CONCLUSIONS: These results suggest that acoustic cavitation plays an important role in HIFU-induced vessel rupture. In HIFU treatments for vessel occlusion, passive monitoring of acoustic emissions may be useful in avoiding hemorrhage due to vessel rupture, as shown in the rupture suppression experiments.

Relations between acoustic cavitation and skin resistance during intermediate- and high-frequency sonophoresis.

Enhanced skin permeability is known to be achieved during sonophoresis due to ultrasound-induced cavitation. However, the mechanistic role of cavitation during sonophoresis has been extensively investigated only for low-frequency (LFS, <100 kHz) applications. Here, mechanisms of permeability-enhancing stable and inertial cavitation were investigated by passively monitoring subharmonic and broadband emissions arising from cavitation isolated within or external to porcine skin in vitro during intermediate- (IFS, 100-700 kHz) and high-frequency sonophoresis (HFS, >1 MHz). The electrical resistance of skin, a surrogate measure of the permeability of skin to a variety of compounds, was measured to quantify the reduction and subsequent recovery of the skin barrier during and after exposure to pulsed (1 second pulse, 20% duty cycle) 0.41 and 2.0 MHz ultrasound over a range of acoustic powers (0-21.7 W) for 30 min. During IFS, significant skin resistance reductions and acoustic emissions from cavitation were measured exclusively when cavitation was isolated outside of the skin. Time-dependent skin resistance reductions measured during IFS correlated significantly with subharmonic and broadband emission levels. During HFS, significant skin resistance reductions were accompanied by significant acoustic emissions from cavitation measured during trials that isolated cavitation activity either outside of skin or within skin. Time-dependent skin resistance reductions measured during HFS correlated significantly greater with subharmonic than with broadband emission levels. The reduction of the skin barrier due to sonophoresis was reversible in all trials; however, effects incurred during IFS recovered more slowly and persisted over a longer period of time than HFS. These results quantitatively demonstrate the significance of cavitation during sonophoresis and suggest that the mechanisms and post-treatment longevity of permeability enhancement due to IFS and HFS treatments are different.