The effects of ultrasound parameters and microbubble concentration on acoustic particle palpation.

The elasticity of tissue-an indicator of disease progression-can be imaged by ultrasound elasticity imaging technologies. An acoustic particle palpation (APP) has recently been developed-the use of ultrasonically driven acoustic particles (e.g., microbubbles)-as an alternative method of tissue deformation. APP has the potential to improve the resolution, contrast, and depth of ultrasound elasticity imaging; but the tissue displacement dynamics and its dependence on acoustic pressure, center frequency, and microbubble concentration remains unknown. Here, displacements of at least 1 µm were produced by applying ultrasound onto a microbubble solution (concentration: 10 × 106 microbubbles ml-1) placed within a tunnel surrounded by a 5% gelatin phantom. Displacements of more than 10 µm were produced using a 1, 3.5, or 5 MHz center frequency pulse with peak-rarefactional pressures of 470, 785, and 1210 kPa, respectively. The deformation of the distal wall varied spatially and temporally according to the different parameters investigated. At low pressures, the deformation increased over several milliseconds until it was held at a nearly constant value. At high pressures, a large deformation occurred within a millisecond followed by a sharp decrease and long stabilization. Ultrasound exposure in the presence of microbubbles produced tissue deformation (p < 0.05) while without microbubbles, no deformation was observed.

Optimization of the Tracking Beam Sequence in Harmonic Motion Imaging.

Harmonic motion imaging (HMI) is an ultrasound elastography technique that estimates the viscoelastic properties of tissues by inducing localized oscillatory motion using focused ultrasound (FUS). The resulting displacement, assumed to be inversely proportional to the tissue local stiffness, is estimated using an imaging array based on RF speckle tracking. In conventional HMI, this is accomplished with plane-wave (PW) imaging, which inherently suffers from low lateral resolution. Coherent PW compounding (PWC) leverages spatial and temporal resolution using synthetic focusing in transmit. In this study, we introduced focused imaging with parallel tracking in HMI and compared parallel tracking of various transmit F-numbers (F/2.6, 3, 4, and 5) qualitatively and quantitatively with PW and PWC imaging at various compounded angle ranges (6°, 12°, and 18°). An in silico model of a 56-kPa spherical inclusion (diameter: 3.6 mm) embedded in a 5.3-kPa background and a 5.3-kPa elastic phantom with cylindrical inclusions (Young's moduli: 22-56 kPa, diameters: 2.0-8.6 mm) were imaged to assess different tracking beam sequences. Speckle biasing in displacement estimation associated with parallel tracking was also investigated and concluded to be negligible in HMI. Parallel tracking in receive (Rx) resulted in 2%-7% and 8%-12% increase compared to PW imaging ( ) in HMI contrast and contrast-to-noise ratio in silico and phantoms. Focused imaging with parallel tracking in Rx was concluded to be most robust among PW and PWC imaging for displacement estimation, and its preclinical feasibility was demonstrated in postsurgical human cancerous breast tissue specimens and in vivo murine models of breast cancer.

An Efficient and Multi-Focal Focused Ultrasound Technique for Harmonic Motion Imaging.

Harmonic motion imaging (HMI) is an ultrasound-based elasticity imaging technique that utilizes oscillatory acoustic radiation force to estimate the mechanical properties of tissues, as well as monitor high-intensity focused ultrasound (HIFU) treatment. Conventionally, in HMI, a focused ultrasound (FUS) transducer generates oscillatory tissue displacements, and an imaging transducer acquires channel data for displacement estimation, with each transducer being driven with a separate system. The fixed position of the FUS focal spot requires mechanical translation of the transducers, which can be a time-consuming and challenging procedure. In this study, we developed and characterized a new HMI system with a multi-element FUS transducer with the capability of electronic focal steering of ±5 mm and ±2 mm from the geometric focus in the axial and lateral directions, respectively. A pulse sequence was developed to drive both the FUS and imaging transducers using a single ultrasound data acquisition (DAQ) system. The setup was validated on a tissue-mimicking phantom with embedded inclusions. Integrating beam steering with the mechanical translation of the transducers resulted in a consistent high contrast-to-noise ratio (CNR) for the inclusions with Young's moduli of 22 and 44 kPa within a 5-kPa background while the data acquisition speed is increased by 4.5-5.2-fold compared to the case when only mechanical movements were applied. The feasibility of simultaneous generation of multiple foci and tracking the induced displacements is demonstrated in phantoms for applications where imaging or treatment of a larger region is needed. Moreover, preliminary feasibility is shown in a human subject with a breast tumor, where the mean HMI displacement within the tumor was about 4 times lower than that within perilesional tissues. The proposed HMI system facilitates data acquisition in terms of flexibility and speed and can be potentially used in the clinic for breast cancer imaging and treatment.

The impact of amplitude modulation frequency in harmonic motion imaging on inclusion characterization.

OBJECTIVE: Ultrasound elasticity imaging techniques aim to provide a non-invasive characterization of tissue mechanical properties to detect pathological changes and monitor disease progression. Harmonic motion imaging (HMI) is an ultrasound-based elasticity imaging technique that utilizes an oscillatory acoustic radiation force to induce localized displacements and estimate relative tissue stiffness. Previous studies have applied a low amplitude modulation (AM) frequency of 25 or 50 Hz in HMI to assess the mechanical properties of different tissue types. In this study, we investigate the dependence of AM frequency in HMI and whether the frequency can be adjusted based on the size and mechanical properties of the underlying medium for enhanced image contrast and inclusion detection. METHODS: A tissue-mimicking phantom with embedded inclusions at different sizes and stiffnesses was imaged within a range of AM frequencies from 25 to 250 Hz at 25-Hz step size. DISCUSSION: The AM frequency at which the maximum contrast and CNR are achieved depends on the size and stiffness of the inclusions. A general trend shows that contrast and CNR peak at higher frequencies for smaller inclusions. In addition, for some inclusions with the same size but different stiffnesses, the optimized AM frequency increases with the stiffness of the inclusion. Nevertheless, there is a shift between the frequencies at which the contrast peaks and those with maximum CNR. Finally, in agreement with the phantom findings, imaging an ex-vivo human specimen with a 2.7-cm breast tumor at a range of AM frequencies showed that the highest contrast and CNR are achieved at the AM frequency of 50 Hz. CONCLUSION: These findings indicate that the AM frequency can be optimized in different applications of HMI, especially in the clinic, for improved detection and characterization of tumors with different geometries and mechanical properties.

Feasibility of Harmonic Motion Imaging Using a Single Transducer: In Vivo Imaging of Breast Cancer in a Mouse Model and Human Subjects.

Harmonic motion imaging (HMI) interrogates the mechanical properties of tissues by simultaneously generating and tracking harmonic oscillation using focused ultrasound and imaging transducers, respectively. Instead of using two transducers, the objective of this work is to develop a single transducer HMI (ST-HMI) to both generate and track harmonic motion at "on-axis" to the force for facilitating data acquisition. In ST-HMI, the amplitude-modulated force was generated by modulating excitation pulse duration and tracking of motion was performed by transmitting tracking pulses interleaved between excitation pulses. The feasibility of ST-HMI was performed by imaging two elastic phantoms with three inclusions (N = 6) and comparing it with acoustic radiation force impulse (ARFI) imaging, in vivo longitudinal monitoring of 4T1, orthotropic breast cancer mice (N = 4), and patients (N = 3) with breast masses in vivo. Six inclusions with Young's moduli of 8, 10, 15, 20, 40, and 60 kPa were embedded in a 5 kPa background. The ST-HMI-derived peak-to-peak displacement (P2PD) successfully detected all inclusions with [Formula: see text] of the linear regression between the P2PD ratio of background to inclusion versus Young's moduli ratio of inclusion to background. The contrasts of 10 and 15 kPa inclusions were higher in ST-HMI than ARFI-derived images. In the mouse study, the median P2PD ratio of tumor to non-cancerous tissues was 3.0, 5.1, 6.1, and 7.7 at 1, 2, 3, and 4 weeks post-injection of the tumor cells, respectively. In the clinical study, ST-HMI detected breast masses including fibroadenoma, pseudo angiomatous stromal hyperplasia, and invasive ductal carcinoma with a P2PD ratio of 1.37, 1.61, and 1.78, respectively. These results indicate that ST-HMI can assess the mechanical properties of tissues via generation and tracking of harmonic motion "on-axis" to the ARF. This study is the first step towards translating ST-HMI in clinics.

Synchronous temperature variation monitoring during ultrasound imaging and/or treatment pulse application: a phantom study.

Ultrasound attenuation through soft tissues can produce an acoustic radiation force (ARF) and heating. The ARF-induced displacements and temperature evaluations can reveal tissue properties and provide insights into focused ultrasound (FUS) bio-effects. In this study, we describe an interleaving pulse sequence tested in a tissue-mimicking phantom that alternates FUS and plane-wave imaging pulses at a 1 kHz frame rate. The FUS is amplitude modulated, enabling the simultaneous evaluation of tissue-mimicking phantom displacement using harmonic motion imaging (HMI) and temperature rise using thermal strain imaging (TSI). The parameters were varied with a spatial peak temporal average acoustic intensity (I spta ) ranging from 1.5 to 311 W.cm-2, mechanical index (MI) from 0.43 to 4.0, and total energy (E) from 0.24 to 83 J.cm-2. The HMI and TSI processing could estimate displacement and temperature independently for temperatures below 1.80°C and displacements up to ~117 µm (I spta <311 W.cm-2, MI<4.0, and E<83 J.cm-2) indicated by a steady-state tissue-mimicking phantom displacement throughout the sonication and a comparable temperature estimation with simulations in the absence of tissue-mimicking phantom motion. The TSI estimations presented a mean error of ±0.03°C versus thermocouple estimations with a mean error of ±0.24°C. The results presented herein indicate that HMI can operate at diagnostic-temperature levels (i.e., <1°C) even when exceeding diagnostic acoustic intensity levels (720 mW.cm-2 < I spta < 207 W.cm-2). In addition, the combined HMI and TSI can potentially be used for simultaneous evaluation of safety during tissue elasticity imaging as well as FUS mechanism involved in novel ultrasound applications such as ultrasound neuromodulation and tumor ablation.

Iterative Curve Fitting of the Bioheat Transfer Equation for Thermocouple-Based Temperature Estimation In Vitro and In Vivo.

Temperature measurements with thin thermocouples embedded in ultrasound fields are strongly subjected to a viscous heating artifact (VHA). The artifact contribution decays over time; therefore, it can be minimized at late temperature readings. However, previous studies have failed to demonstrate a rigorous method for determining the optimal time point at which the artifact contribution is negligible. In this study, we present an iterative processing method based on successive curve fittings using an artifact-independent model. The fitting starting point moves at each iteration until the maximum R2 indicates where the viscous heating is minimum. A solution of the bioheat transfer equation is used to account for blood perfusion, thus enabling in vivo measurements. Three T-type thermocouples with different diameters and sensitivities were assessed in an excised canine liver and in the mouse brain in vivo. We found that the artifact constitutes up to 81% ± 5% of wire thermocouple readings. The best-fit time varied in the liver samples ( n = 3 ) from 0 to 3.335 ± 0.979 s and in the mouse brain ( n = 5 ) from 0 to 0.498 ± 0.457 s at variable experimental conditions, which clearly demonstrates the need of the method for finding the appropriate starting time point of the fit. This study introduces a statistical method to determine the best time to fit a curve that can back-estimate temperature in tissues under ultrasound exposure using thermocouples. This method allows temperature evaluation in vivo and in vitro during a validation and safety assessment of a wide range of therapeutic and diagnostic ultrasound modalities.

Harmonic motion imaging of human breast masses: an in vivo clinical feasibility.

Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion imaging (HMI) is an elasticity imaging technique that uses acoustic radiation force to evaluate the localized mechanical properties of the underlying tissue. Herein, we studied the in vivo feasibility of a clinical HMI system to differentiate breast tumors based on their relative HMI displacements, in human subjects. We performed HMI scans in 10 female subjects with breast masses: five benign and five malignant masses. Results revealed that both benign and malignant masses were stiffer than the surrounding tissues. However, malignant tumors underwent lower mean HMI displacement (1.1 ± 0.5 µm) compared to benign tumors (3.6 ± 1.5 µm) and the adjacent non-cancerous tissue (6.4 ± 2.5 µm), which allowed to differentiate between tumor types. Additionally, the excised breast specimens of the same patients (n = 5) were imaged post-surgically, where there was an excellent agreement between the in vivo and ex vivo findings, confirmed with histology. Higher displacement contrast between cancerous and non-cancerous tissue was found ex vivo, potentially due to the lower nonlinearity in the elastic properties of ex vivo tissue. This preliminary study lays the foundation for the potential complementary application of HMI in clinical practice in conjunction with the B-mode to classify suspicious breast masses.

Noninvasive Young's modulus visualization of fibrosis progression and delineation of pancreatic ductal adenocarcinoma (PDAC) tumors using Harmonic Motion Elastography (HME) in vivo.

Background and aims: Poor specificity and predictive values of current cross-sectional radiological imaging methods in evaluation of pancreatic adenocarcinoma (PDAC) limit the clinical capability to accurately stage the tumor pre-operatively and provide optimal surgical treatment and improve patient outcomes. Methods: In this study, we applied Harmonic Motion Elastography (HME), a quantitative ultrasound-based imaging method to calculate Young's modulus (YM) in PDAC mouse models (n = 30) and human pancreatic resection specimens of PDAC (n=32). We compared the YM to the collagen assessment by Picrosirius red (PSR) stain on corresponding histologic sections. Results: HME is capable of differentiating between different levels of fibrosis in transgenic mice. In mice without pancreatic fibrosis, the measured YM was 4.2 ± 1.3 kPa, in fibrotic murine pancreata, YM was 5.5 ± 2.0 kPa and in murine PDAC tumors, YM was 11.3 ± 1.7 kPa. The corresponding PSR values were 2.0 ± 0.8 %, 9.8 ± 3.4 %, and 13.2 ± 1.2%, respectively. In addition, three regions within each human surgical PDAC specimen were assessed: tumor, which had both the highest Young's modulus (YM > 40 kPa) and collagen density (PSR > 40 %); non-neoplastic adjacent pancreas, which had the lowest Young's modulus (YM < 15 kPa) and collagen density (PSR < 10%) and a transitional peri-lesional region between the tumor and non-neoplastic pancreas with an intermediate value of measured Young's modulus (15 kPa < YM < 40 kPa) and collagen density (15% < PSR < 35 %). Conclusion: In conclusion, a non-invasive, quantitative imaging tool for detecting, staging and delineating PDAC tumor margins based on the change in collagen density was developed.

Harmonic Motion Imaging of Pancreatic Tumor Stiffness Indicates Disease State and Treatment Response.

PURPOSE: Pancreatic ductal adenocarcinoma (PDA) is a common, deadly cancer that is challenging both to diagnose and to manage. Its hallmark is an expansive, desmoplastic stroma characterized by high mechanical stiffness. In this study, we sought to leverage this feature of PDA for two purposes: differential diagnosis and monitoring of response to treatment. EXPERIMENTAL DESIGN: Harmonic motion imaging (HMI) is a functional ultrasound technique that yields a quantitative relative measurement of stiffness suitable for comparisons between individuals and over time. We used HMI to quantify pancreatic stiffness in mouse models of pancreatitis and PDA as well as in a series of freshly resected human pancreatic cancer specimens. RESULTS: In mice, we learned that stiffness increased during progression from preneoplasia to adenocarcinoma and also effectively distinguished PDA from several forms of pancreatitis. In human specimens, the distinction of tumors versus adjacent pancreatitis or normal pancreas tissue was even more stark. Moreover, in both mice and humans, stiffness increased in proportion to tumor size, indicating that tuning of mechanical stiffness is an ongoing process during tumor progression. Finally, using a brca2-mutant mouse model of PDA that is sensitive to cisplatin, we found that tissue stiffness decreases when tumors respond successfully to chemotherapy. Consistent with this observation, we found that tumor tissues from patients who had undergone neoadjuvant therapy were less stiff than those of untreated patients. CONCLUSIONS: These findings support further development of HMI for clinical applications in disease staging and treatment response assessment in PDA.

Technical Note: In vivo Young's modulus mapping of pancreatic ductal adenocarcinoma during HIFU ablation using harmonic motion elastography (HME).

PURPOSE: Noninvasive quantitative assessment of coagulated tissue during high-intensity focused ultrasound (HIFU) ablation is one of the essential steps for tumor treatment, especially in such cases as the Pancreatic Ductal Adenocarcinoma (PDA) that has low probability of diagnosis at the early stages and high probability of forming solid carcinomas resistant to chemotherapy treatment at the late stages. METHODS: Harmonic motion elastography (HME) is a technique for the localized estimation of tumor stiffness. This harmonic motion imaging (HMI)-based technique is designed to map the tissue Young's modulus or stiffness noninvasively. A focused ultrasound (FUS) transducer generates an oscillating, acoustic radiation force in its focal region. The two-dimensional (2D) shear wave speed, and consequently the Young's modulus maps, is generated by tracking the radio frequency (RF) signals acquired at high frame rates. By prolonging the sonication for more than 50 s using the same methodology, the 2D Young's modulus maps are reconstructed while HIFU is applied and ablation is formed on PDA murine tumors. RESULTS: The feasibility of this technique in measuring the regional Young's modulus was first assessed in tissue-mimicking phantoms. The contrast-to-noise ratio (CNR) was found to be higher than 11.7 dB for each 2D reconstructed Young's modulus map. The mean error in this validation study was found to be equal to less than 19%. Then HME was applied on two transgenic mice with pancreatic ductal adenocarcinoma tumors. The Young's modulus median value of this tumor at the start of the HIFU application was equal to 2.1 kPa while after 45 s of sonication it was found to be approximately three times stiffer (6.7 kPa). CONCLUSIONS: The HME was described herein and showed its capability of measuring tissue stiffness noninvasively by measuring the shear wave speed propagation inside the tissue and reconstructing a 2D Young's modulus map. Application of the methodology in vivo and during HIFU were thus reported here for the first time.