Harmonic Motion Imaging Research Articles

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.

Harmonic Motion Imaging-Guided Focused Ultrasound Ablation: Comparison of Three Focused Ultrasound Interference Filtering Methods

Harmonic motion imaging (HMI) is an acoustic radiation force-based elasticity imaging technique, which can be used to monitor changes in tissue mechanical properties caused by focused ultrasound (FUS)-induced thermal ablation. In conventional HMI, the amplitude-modulated FUS sequence and imaging pulse are transmitted simultaneously. With this method, the high-amplitude FUS signal must be separated from the imaging data for tissue displacement estimation. Frequency domain notch filtering and bandpass filtering were previously used to filter FUS interference from imaging data. However, FUS interference becomes more pronounced at the increased intensities and durations necessary for thermal ablation, rendering frequency domain filtering challenging. In this study, three methods for FUS interference filtering during HMI-guided FUS ablation (HMIgFUS) were compared. The methods were notch filtering; interleaved HMIgFUS, with interleaved FUS and imaging pulses; and FUS-net, a convolutional neural network-based U-Net autoencoder developed by our group for FUS interference filtering in radiofrequency data. FUS-net was applied here for the first time for the purpose of ablation displacement monitoring. The three filtering methods were tested during 20 HMIgFUS acquisitions in an ex vivo canine liver using a range of peak positive pressures from 11 to 18 MPa and durations ranging from 60 to 180 seconds. The B-mode mean squared errors (MSEs) and displacement amplitude contrast-to-noise ratios (CNRs) of the three methods were calculated and compared. The interleaved method for HMIgFUS was found to be significantly robust in avoiding FUS interference in all tested cases for FUS ablation monitoring, especially cases with high FUS pressure and long durations, as opposed to traditional notch filtering and FUS-net filtering. CNRs obtained from displacement amplitude maps in the interleaved data set were significantly higher in all cases than those obtained from the notch filtered and FUS-net data sets. There was not a significant trend in displacement CNR between the FUS-net and notch filtered data sets. However, B-mode MSE was found to be significantly higher when comparing the FUS-net and interleaved data sets as opposed to the notch filtered and interleaved data sets, suggesting further potential of FUS-net as an FUS interference filtering method. These findings indicate the robustness of interleaved HMIgFUS in avoiding FUS interference during HMIgFUS monitoring and the advantages, limitations and future potential of FUS-net and notch filtering.

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

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. 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. 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. 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.

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.

An analytical model of full-field displacement and strain induced by amplitude-modulated focused ultrasound in harmonic motion imaging

The majority of disease processes involves changes in the micro-structure of the affected tissue, which can translate to changes in the mechanical properties of the corresponding tissue. Harmonic motion imaging (HMI) is an elasticity imaging technique that allows the study of the mechanical parameters of tissue by detecting the tissue response by a harmonic motion field, which is generated by oscillatory acoustic radiation force. HMI has been demonstrated in tumor detection and characterization as well as monitoring of ablation procedures. In this study, an analytical HMI model is demonstrated and compared with a finite element model (FEM), allowing rapid and accurate computation of the displacement, strain, and shear wave velocity (SWV) at any location in a homogenous linear elastic material. Average absolute differences between the analytical model and the FEM were respectively 1.2% for the displacements and 0.5% for the strains for 41 940 force voxels at 0.22 s per displacement evaluation. A convergence study showed that the average difference could be further decreased to 1.0% and 0.15% for the displacements and strains, respectively, if force resolution is increased. SWV fields, as calculated with the FEM and the analytical model, have regional differences in velocities up to 0.57 m s−1 with an average absolute difference of 0.11 ± 0.07 m s−1, primarily due to imperfections in the non-reflecting FEM boundary conditions. The apparent SWV differed from the commonly used plane-wave approximation by up to 1.2 m s−1 due to near and intermediate field effects. Maximum displacement amplitudes for a model with an inclusion stabilize within 10% of the homogenous model at an inclusion radius of 10 mm while the maximum strain reacts faster, stabilizing at an inclusion radius of 3 mm. In conclusion, an analytical model for HMI stiffness estimation is presented in this paper. The analytical model has advantages over FEM as the full-field displacements do not need to be calculated to evaluate the model at a single measurement point. This advantage, together with the computational speed, makes the analytical model useful for real-time imaging applications. However, the analytical model was found to have restrictive assumptions on tissue homogeneity and infinite dimensions, while the FEM approaches were shown adaptable to variable geometry and non-homogenous 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.

Feasibility of a single-transducer harmonic motion imaging using frequency-based simultaneous multiple harmonic oscillation excitation pulses

Single-transducer harmonic motion imaging (ST-HMI) uses a single transducer to generate the harmonic motion at a particular frequency by modulating excitation pulse duration and then, estimate the motion by collecting tracking pulses in-between the excitation pulses, unlike the conventional HMI which uses focused ultrasound and an imaging transducer. Instead of oscillating at a single frequency, the objective is to use ST-HMI for simultaneously exciting the tissue at multiple frequencies. Six excitation pulses per period were selected by sampling a continuous signal which was generated by summing sinusoids with fundamental and harmonics of 100 Hz and 200–1000 Hz, respectively. A mean peak to peak displacement (MP2PD) image was generated by a weighted average of P2PD at each frequency with a weighting factor derived from the Fourier transform. The new method is evaluated by imaging four inclusions (INC, Young's modulus: 6, 9, 32, and 75 kPa) embedded in 18 kPa background (BKD) and HIFU ablated excised canine liver. The MP2PD image successfully differentiated all four inclusions with R2 = 0.99 of the linear regression between the MP2PD ratio of BKD to INC versus Young's modulus ratio of INC to BKD. The MP2PD image detected the ablated region with the MP2PD ratio of non-ablated versus ablated regions of 1.64. These results demonstrate the feasibility of simultaneously exciting the tissue at multiple frequencies. Ongoing studies entail the translation of this new elasticity imaging method of detecting breast masses in humans.

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.

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

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. 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. 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. 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).

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. 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 50s using the same methodology, the 2D Young's modulus maps are reconstructed while HIFU is applied and ablation is formed on PDA murine tumors. 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 11.7dB 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 2.1kPa while after 45s of sonication it was found to be approximately three times stiffer (6.7kPa). 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 invivo and during HIFU were thus reported here for the first time.

Focused Ultrasound Steering for Harmonic Motion Imaging.

Harmonic motion imaging (HMI) is a radiation-force-based ultrasound elasticity imaging technique, which is designed for both tissue relative stiffness imaging and reliable high-intensity focused ultrasound treatment monitoring. The objective of this letter is to develop and demonstrate the feasibility of 2-D focused ultrasound (FUS) beam steering for HMI using a 93-element, FUS phased array. HMI with steered FUS beam was acquired in tissue-mimicking phantoms. The HMI displacement was imaged within the steering range of ±1.7 mm laterally and ±2 mm axially. Using the steered FUS beam, HMI can be used to image a larger tissue volume with higher efficiency and without requiring mechanical movement of the transducer.

Real-time ablation monitoring and lesion quantification using harmonic motion imaging guided focused ultrasound (HMIgFUS)

High-Intensity Focused Ultrasound (HIFU) monitoring is currently hindered by time- and cost-inefficient or inconclusive warranting, thus an imaging technique for efficient and reliable guidance. Harmonic Motion Imaging (HMI) uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI also uses ultrasound imaging with parallel beamforming and estimates and maps the tissue dynamic motion in response to the oscillatory force at the same frequency based on consecutive RF frames. HMI has already been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animal tumor models in vivo. Using an FUS beam, HMI can also be seamlessly integrated with thermal ablation using HIFU, which leads to changes in the tumor stiffness. In this paper, an overview of HMI will be provided, including the capability of HMI to characterize and image the tumor prior to ablation, localize the beam for treatment planning, as well as monitor subsequent lesioning in real time. The findings demonstrate that HMI is capable of both detecting and characterizing the tumor prior to HIFU ablation as well as correctly depict and quantify the lesion during treatment. More importantly, HMI is shown capable of distinguishing the tumor margins from those of the thermal lesion in vivo in order to accurately determine treatment success. HMI thus constitutes an integrated, real-time method for efficient HIFU monitoring.

Fast lesion mapping during HIFU treatment using harmonic motion imaging guided focused ultrasound (HMIgFUS) in vitro and in vivo

The successful clinical application of high intensity focused ultrasound (HIFU) ablation depends on reliable monitoring of the lesion formation. Harmonic motion imaging guided focused ultrasound (HMIgFUS) is an ultrasound-based elasticity imaging technique, which monitors HIFU ablation based on the stiffness change of the tissue instead of the echo intensity change in conventional B-mode monitoring, rendering it potentially more sensitive to lesion development. Our group has shown that predicting the lesion location based on the radiation force-excited region is feasible during HMIgFUS. In this study, the feasibility of a fast lesion mapping method is explored to directly monitor the lesion map during HIFU. The harmonic motion imaging (HMI) lesion map was generated by subtracting the reference HMI image from the present HMI peak-to-peak displacement map, as streamed on the computer display. The dimensions of the HMIgFUS lesions were compared against gross pathology. Excellent agreement was found between the lesion depth (r2 = 0.81, slope = 0.90), width (r2 = 0.85, slope = 1.12) and area (r2 = 0.58, slope = 0.75). In vivo feasibility was assessed in a mouse with a pancreatic tumor. These findings demonstrate that HMIgFUS can successfully map thermal lesions and monitor lesion development in real time in vitro and in vivo. The HMIgFUS technique may therefore constitute a novel clinical tool for HIFU treatment monitoring.

Elasticity mapping of murine abdominal organs in vivo using harmonic motion imaging (HMI)

Recently, ultrasonic imaging of soft tissue mechanics has been increasingly studied to image otherwise undetectable pathologies. However, many underlying mechanisms of tissue stiffening remain unknown, requiring small animal studies and adapted elasticity mapping techniques. Harmonic motion imaging (HMI) assesses tissue viscoelasticity by inducing localized oscillation from a periodic acoustic radiation force. The objective of this study was to evaluate the feasibility of HMI for in vivo elasticity mapping of abdominal organs in small animals. Pathological cases, i.e. chronic pancreatitis and pancreatic cancer, were also studied in vivo to assess the capability of HMI for detection of the change in mechanical properties. A 4.5 MHz focused ultrasound transducer (FUS) generated an amplitude-modulated beam resulting in 50 Hz harmonic tissue oscillations at its focus. Axial tissue displacement was estimated using 1D-cross-correlation of RF signals acquired with a 7.8 MHz diagnostic transducer confocally aligned with the FUS. In vitro results in canine liver and kidney showed the correlation between HMI displacement and Young’s moduli measured by rheometry compression testing. HMI was capable of providing reproducible elasticity maps of the mouse abdominal region in vivo allowing the identification of, from stiffest to softest, the murine kidney, pancreas, liver, and spleen. Finally, pancreata affected by pancreatitis and pancreatic cancer showed HMI displacements 1.7 and 2.2 times lower than in the control case, respectively, indicating higher stiffness. The HMI displacement amplitude was correlated with the extent of fibrosis as well as detecting the very onset of stiffening even before fibrosis could be detected on H&E. This work shows that HMI can produce reliable elasticity maps of mouse abdominal region in vivo, thus providing a potentially critical tool to assess pathologies affecting organ elasticity.

Tumor characterization and treatment monitoring of postsurgical human breast specimens using harmonic motion imaging (HMI).

BackgroundHigh-intensity focused ultrasound (HIFU) is a noninvasive technique used in the treatment of early-stage breast cancer and benign tumors. To facilitate its translation to the clinic, there is a need for a simple, cost-effective device that can reliably monitor HIFU treatment. We have developed harmonic motion imaging (HMI), which can be used seamlessly in conjunction with HIFU for tumor ablation monitoring, namely harmonic motion imaging for focused ultrasound (HMIFU). The overall objective of this study was to develop an all ultrasound-based system for real-time imaging and ablation monitoring in the human breast in vivo.MethodsHMI was performed in 36 specimens (19 normal, 15 invasive ductal carcinomas, and 2 fibroadenomas) immediately after surgical removal. The specimens were securely embedded in a tissue-mimicking agar gel matrix and submerged in degassed phosphate-buffered saline to mimic in vivo environment. The HMI setup consisted of a HIFU transducer confocally aligned with an imaging transducer to induce an oscillatory radiation force and estimate the resulting displacement.Results3D HMI displacement maps were reconstructed to represent the relative tissue stiffness in 3D. The average peak-to-peak displacement was found to be significantly different (p = 0.003) between normal breast tissue and invasive ductal carcinoma. There were also significant differences before and after HMIFU ablation in both the normal (53.84 % decrease) and invasive ductal carcinoma (44.69 % decrease) specimens.ConclusionsHMI can be used to map and differentiate relative stiffness in postsurgical normal and pathological breast tissues. HMIFU can also successfully monitor thermal ablations in normal and pathological human breast specimens. This HMI technique may lead to a new clinical tool for breast tumor imaging and HIFU treatment monitoring.

Real-time Monitoring of High Intensity Focused Ultrasound (HIFU) Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound (HMIFU).

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a technique that can perform and monitor high-intensity focused ultrasound (HIFU) ablation. An oscillatory motion is generated at the focus of a 93-element and 4.5 MHz center frequency HIFU transducer by applying a 25 Hz amplitude-modulated signal using a function generator. A 64-element and 2.5 MHz imaging transducer with 68kPa peak pressure is confocally placed at the center of the HIFU transducer to acquire the radio-frequency (RF) channel data. In this protocol, real-time monitoring of thermal ablation using HIFU with an acoustic power of 7 W on canine livers in vitro is described. HIFU treatment is applied on the tissue during 2 min and the ablated region is imaged in real-time using diverging or plane wave imaging up to 1,000 frames/second. The matrix of RF channel data is multiplied by a sparse matrix for image reconstruction. The reconstructed field of view is of 90° for diverging wave and 20 mm for plane wave imaging and the data are sampled at 80 MHz. The reconstruction is performed on a Graphical Processing Unit (GPU) in order to image in real-time at a 4.5 display frame rate. 1-D normalized cross-correlation of the reconstructed RF data is used to estimate axial displacements in the focal region. The magnitude of the peak-to-peak displacement at the focal depth decreases during the thermal ablation which denotes stiffening of the tissue due to the formation of a lesion. The displacement signal-to-noise ratio (SNRd) at the focal area for plane wave was 1.4 times higher than for diverging wave showing that plane wave imaging appears to produce better displacement maps quality for HMIFU than diverging wave imaging.

Real-time Monitoring of High Intensity Focused Ultrasound (HIFU) Ablation of &lt;em&gt;In Vitro&lt;/em&gt; Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound (HMIFU)

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a technique that can perform and monitor high-intensity focused ultrasound (HIFU) ablation. An oscillatory motion is generated at the focus of a 93-element and 4.5 MHz center frequency HIFU transducer by applying a 25 Hz amplitude-modulated signal using a function generator. A 64-element and 2.5 MHz imaging transducer with 68kPa peak pressure is confocally placed at the center of the HIFU transducer to acquire the radio-frequency (RF) channel data. In this protocol, real-time monitoring of thermal ablation using HIFU with an acoustic power of 7 W on canine livers in vitro is described. HIFU treatment is applied on the tissue during 2 min and the ablated region is imaged in real-time using diverging or plane wave imaging up to 1,000 frames/second. The matrix of RF channel data is multiplied by a sparse matrix for image reconstruction. The reconstructed field of view is of 90° for diverging wave and 20 mm for plane wave imaging and the data are sampled at 80 MHz. The reconstruction is performed on a Graphical Processing Unit (GPU) in order to image in real-time at a 4.5 display frame rate. 1-D normalized cross-correlation of the reconstructed RF data is used to estimate axial displacements in the focal region. The magnitude of the peak-to-peak displacement at the focal depth decreases during the thermal ablation which denotes stiffening of the tissue due to the formation of a lesion. The displacement signal-to-noise ratio (SNRd) at the focal area for plane wave was 1.4 times higher than for diverging wave showing that plane wave imaging appears to produce better displacement maps quality for HMIFU than diverging wave imaging.

Combined Therapeutic and Monitoring Ultrasonic Catheter for Cardiac Ablation Therapies

This study evaluated the feasibility of a combined therapeutic and diagnostic ultrasonic catheter for cardiac ablation therapies. Ultrasound can be used to determine when diseased cardiac tissues have become fully coagulated through a method known as local harmonic motion imaging (LHMI). LHMI is an imaging modality for treatment monitoring that uses acoustic radiation force, displacement tracking and the different mechanical properties of viable and ablated tissues. In this study, we developed catheters that are capable of LHMI measurements. Experiments were conducted in phantoms, exvivo cardiac samples and the invivo beating hearts of healthy porcine subjects. Invivo experiments revealed that four of four epicardial sonications revealed a decrease in measured displacements from LHMI experiments and that when lower power was used, no lesions formed and there was no corresponding decrease in measured displacement amplitudes. In addition, two of three endocardial lesions were confirmed and corresponded to a decrease in the measured displacement amplitude.

Radiation-force-based estimation of acoustic attenuation using harmonic motion imaging (HMI) in phantoms and in vitro livers before and after HIFU ablation

Acoustic attenuation represents the energy loss of the propagating wave through biological tissues and plays a significant role in both therapeutic and diagnostic ultrasound applications. Estimation of acoustic attenuation remains challenging but critical for tissue characterization. In this study, an attenuation estimation approach was developed using the radiation-force-based method of harmonic motion imaging (HMI). 2D tissue displacement maps were acquired by moving the transducer in a raster-scan format. A linear regression model was applied on the logarithm of the HMI displacements at different depths in order to estimate the acoustic attenuation. Commercially available phantoms with known attenuations () and in vitro canine livers () were tested, as well as HIFU lesions in in vitro canine livers (). Results demonstrated that attenuations obtained from the phantoms showed a good correlation () with the independently obtained values reported by the manufacturer with an estimation error (compared to the values independently measured) varying within the range of 15–35%. The estimated attenuation in the in vitro canine livers was equal to 0.32 ± 0.03 dB cm−1 MHz−1, which is in good agreement with the existing literature. The attenuation in HIFU lesions was found to be higher (0.58 ± 0.06 dB cm−1 MHz−1) than that in normal tissues, also in agreement with the results from previous publications. Future potential applications of the proposed method include estimation of attenuation in pathological tissues before and after thermal ablation.