Focused Ultrasound Steering for Harmonic Motion Imaging

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.

Innovative Experimental Ultrasound and US-Related Techniques Using the Murine Model in Pancreatic Ductal Adenocarcinoma: A Systematic Review

Pancreatic ductal adenocarcinoma (PDAC) is a cancer with one of the highest mortality rates in the world. Several studies have been conductedusing preclinical experiments in mice to find new therapeutic strategies. Experimental ultrasound, in expert hands, is a safe, multifaceted, and relatively not-expensive device that helps researchers in several ways. In this systematic review, we propose a summary of the applications of ultrasonography in a preclinical mouse model of PDAC. Eighty-eight studies met our inclusion criteria. The included studies could be divided into seven main topics: ultrasound in pancreatic cancer diagnosis and progression (n: 21); dynamic contrast-enhanced ultrasound (DCE-US) (n: 5); microbubble ultra-sound-mediated drug delivery; focused ultrasound (n: 23); sonodynamic therapy (SDT) (n: 7); harmonic motion elastography (HME) and shear wave elastography (SWE) (n: 6); ultrasound-guided procedures (n: 9). In six cases, the articles fit into two or more sections. In conclusion, ultrasound can be a really useful, eclectic, and ductile tool in different diagnostic areas, not only regarding diagnosis but also in therapy, pharmacological and interventional treatment, and follow-up. All these multiple possibilities of use certainly represent a good starting point for the effective and wide use of murine ultrasonography in the study and comprehensive evaluation of pancreatic 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.

FUS-Net: U-Net-Based FUS Interference Filtering

Imaging applications tailored towards ultrasound-based treatment, such as high intensity focused ultrasound (FUS), where higher power ultrasound generates a radiation force for ultrasound elasticity imaging or therapeutics/theranostics, are affected by interference from FUS. The artifact becomes more pronounced with intensity and power. To overcome this limitation, we propose FUS-net, a method that incorporates a CNN-based U-net autoencoder trained end-to-end on 'clean' and 'corrupted' RF data in Tensorflow 2.3 for FUS artifact removal. The network learns the representation of RF data and FUS artifacts in latent space so that the output of corrupted RF input is clean RF data. We find that FUS-net perform 15% better than stacked autoencoders (SAE) on evaluated test datasets. B-mode images beamformed from FUS-net RF shows superior speckle quality and better contrast-to-noise (CNR) than both notch-filtered and adaptive least means squares filtered RF data. Furthermore, FUS-net filtered images had lower errors and higher similarity to clean images collected from unseen scans at all pressure levels. Lastly, FUS-net RF can be used with existing cross-correlation speckle-tracking algorithms to generate displacement maps. FUS-net currently outperforms conventional filtering and SAEs for removing high pressure FUS interference from RF data, and hence may be applicable to all FUS-based imaging and therapeutic methods.

Multifocused Ultrasound Therapy for Controlled Microvascular Permeabilization and Improved Drug Delivery

Focused ultrasound (FUS) exposure of micro-bubble (MB) contrast agents can transiently increase microvascular permeability allowing anticancer drugs to extravasate into a targeted tumor tissue. Either fixed or mechanically steered in space, most studies to date have used a single element focused transducer to deliver the ultrasound (US) energy. The goal of this study was to investigate various multi-FUS strategies implemented on a programmable US scanner (Vantage 256, Verasonics Inc.) equipped with a linear array for image guidance and a 128-element therapy transducer (HIFUPlex-06, Sonic Concepts). The multi-FUS strategies include multi-FUS with sequential excitation (multi-FUS-SE) and multi-FUS with temporal sequential excitation (multi-FUS-TSE) and were compared to single-FUS and sham treatment. This study was performed using athymic mice implanted with breast cancer cells ( N = 20 ). FUS therapy experiments were performed for 10 min after a solution containing MBs (Definity, Lantheus Medical Imaging Inc.) and near-infrared (NIR, surrogate drug) dye were injected via the tail vein. The fluorescent signal was monitored using an in vivo optical imaging system (Pearl Trilogy, LI-COR) to quantify intratumoral dye accumulation at baseline and again at 0.1, 24, and 48 h after receiving US therapy. Animals were then euthanized for ex vivo dye extraction analysis. At 48 h, fluorescent tracer accumulation within the tumor space for the multi-FUS-TSE therapy group animals was found to be 67.3%, 50.3%, and 36.2% higher when compared to sham, single-FUS, and multi-FUS-SE therapy group measures, respectively. Also, dye extraction and fluorescence measurements from excised tumor tissue found increases of 243.2%, 163.1%, and 68.1% for the multi-FUS-TSE group compared to sham, single-FUS, and multi-FUS-SE therapy group measures, respectively. In summary, experimental results revealed that for a multi-FUS sequence, increased microvascular permeability was considerably influenced by both the spatial and temporal aspects of the applied US therapy.

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.