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Ultrasound imaging is a highly valuable tool in imaging human tissues due to its non-invasive and easily accessible nature. Despite advances in the field of ultrasound research, conventional transducers with frequencies lower than 20 MHz face limitations in resolution for cellular applications. To address this challenge, we employed ultrahigh frequency (UHF) transducers and demonstrated their potential applications in the field of biomedical engineering, specifically for cell imaging and acoustic tweezers. The lateral resolution achieved with a 110 MHz UHF transducer was 20 µm, and 6.5 µm with a 410 MHz transducer, which is capable of imaging single cells. The results of our experiments demonstrated the successful imaging of a single PC-3 cell and a 15 µm bead using an acoustic scanning microscope equipped with UHF transducers. Additionally, the dual-mode multifunctional UHF transducer was used to trap and manipulate single cells and beads, highlighting its potential for single-cell studies in areas such as cell deformability and mechanotransduction.

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This study aimed to automatically classify live cells based on their cell type by analyzing the patterns of backscattered signals of cells with minimal effect on normal cell physiology and activity. Our previous studies have demonstrated that label-free acoustic sensing using high-frequency ultrasound at a high pulse repetition frequency (PRF) can capture and analyze a single object from a heterogeneous sample. However, eliminating possible errors in the manual setting and time-consuming processes when postprocessing integrated backscattering (IB) coefficients of backscattered signals is crucial. In this study, an automated cell-type classification system that combines a label-free acoustic sensing technique with deep learning-empowered artificial intelligence models is proposed. We applied an one-dimensional (1D) convolutional autoencoder to denoise the signals and conducted data augmentation based on Gaussian noise injection to enhance the robustness of the proposed classification system to noise. Subsequently, denoised backscattered signals were classified into specific cell types using convolutional neural network (CNN) models for three types of signal data representations, including 1D CNN models for waveform and frequency spectrum analysis and two-dimensional (2D) CNN models for spectrogram analysis. We evaluated the proposed system by classifying two types of cells (e.g., RBC and PNT1A) and two types of polystyrene microspheres by analyzing their backscattered signal patterns. We attempted to discover cell physical properties reflected on backscattered signals by controlling experimental variables, such as diameter and structure material. We further evaluated the effectiveness of the neural network models and efficacy of data representations by comparing their accuracy with that of baseline methods. Therefore, the proposed system can be used to classify reliably and precisely several cell types with different intrinsic physical properties for personalized cancer medicine development.

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Mechanical properties of the anterior anatomical structures of the eye, such as the cornea and ciliary body, play a key role in the ocular function and homeostasis. However, measuring the biomechanical properties of the anterior ocular structures, especially deeper structures, such as the ciliary body, remains a challenge due to the lack of high-resolution imaging tools. Herein, we implement a mechanical shaker-based high-frequency ultrasound elastography technique that can track the induced elastic wave propagation to assess the linear and nonlinear elastic properties of anterior ocular structures. The findings of this study advance our understanding of the role of anterior ocular structures in the pathogenesis of different ocular disorders, such as glaucoma.

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Cell deformability is a useful feature for diagnosing various diseases (e.g., the invasiveness of cancer cells). Existing methods commonly inflict pressure on cells and observe changes in cell areas, diameters, or thickness according to the degree of pressure. Then, the Young's moduli (i.e., a measure of deformability) of cells are estimated based on the assumption that the degrees of the changes are inversely proportional to Young's moduli. However, manual measurements of the physical changes in cells are labor-intensive, and the subjectivity of the operators can intervene during this step, thereby causing considerable uncertainty. Further, because the shapes of cells are nonuniform, we cannot ensure the assumption for linear correlations of physical changes in cells with their deformability. Therefore, this study aims at measuring non-linear elastic moduli of live cells (degrees of cell deformability) automatically by employing conventional neural networks (CNN) and multilayer perceptrons (MLP) while preserving (or enhancing) the accuracy of the manual methods. First, we obtain photomicrographs of cells on multiple pressure levels using single-beam acoustic tweezers, and then, we suggest an image preprocessing method for emphasizing changes in cell areas on the photomicrographs. The CNN model is trained to measure the ratios of the cell area change at each pressure level. Then, we apply the multilayer perceptron (MLP) to learn the correlations of the cell area change ratios according to the pressure levels with cell deformability. The accuracy of the CNN was evaluated using two types of breast cancer cells: MDA-MB-231 (invasive) and MCF-7 (noninvasive). The MLP was assessed using five different beads (Young's moduli from 0.214 to 9.235 kPa), which provides standardized reference data of the non-linear elastic moduli of live cells. Finally, we validated the practicality of the proposed system by examining whether the non-linear elastic moduli estimated by the proposed system can distinguish invasive breast cancer cells from noninvasive ones.

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Ultrasound single-beam acoustic tweezer system has attracted increasing attention in the field of biomechanics. Cell biomechanics play a pivotal role in leukemia cell functions. To better understand and compare the cell mechanics of the leukemia cells, herein, we fabricated an acoustic tweezer system in-house connected with a 50-MHz high-frequency cylinder ultrasound transducer. Selected leukemia cells (Jurkat, K562, and MV-411 cells) were cultured, trapped, and manipulated by high-frequency ultrasound single beam, which was transmitted from the ultrasound transducer without contacting any cells. The relative deformability of each leukemia cell was measured, characterized, and compared, and the leukemia cell (Jurkat cell) gaining the highest deformability was highlighted. Our results demonstrate that the high-frequency ultrasound single beam can be utilized to manipulate and characterize leukemia cells, which can be applied to study potential mechanisms in the immune system and cell biomechanics in other cell types.

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Ultrasound is extensively studied for biomedical engineering applications. As the core part of the ultrasonic system, the ultrasound transducer plays a significant role. For the purpose of meeting the requirement of precision medicine, the main challenge for the development of ultrasound transducer is to further enhance its performance. In this article, an overview of recent developments in ultrasound transducer technologies that use a variety of material strategies and device designs based on both the piezoelectric and photoacoustic mechanisms is provided. Practical applications are also presented, including ultrasound imaging, ultrasound therapy, particle/cell manipulation, drug delivery, and nerve stimulation. Finally, perspectives and opportunities are also highlighted.

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Objective. Retinal degeneration involving progressive deterioration and loss of function of photoreceptors is a major cause of permanent vision loss worldwide. Strategies to treat these incurable conditions incorporate retinal prostheses via electrically stimulating surviving retinal neurons with implanted devices in the eye, optogenetic therapy, and sonogenetic therapy. Existing challenges of these strategies include invasive manner, complex implantation surgeries, and risky gene therapy. Methods and Results. Here, we show that direct ultrasound stimulation on the retina can evoke neuron activities from the visual centers including the superior colliculus and the primary visual cortex (V1), in either normal-sighted or retinal degenerated blind rats in vivo. The neuron activities induced by the customized spherically focused 3.1 MHz ultrasound transducer have shown both good spatial resolution of 250 µm and temporal resolution of 5 Hz in the rat visual centers. An additional customized 4.4 MHz helical transducer was further implemented to generate a static stimulation pattern of letter forms. Conclusion. Our findings demonstrate that ultrasound stimulation of the retina in vivo is a safe and effective approach with high spatiotemporal resolution, indicating a promising future of ultrasound stimulation as a novel and noninvasive visual prosthesis for translational applications in blind patients.

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OBJECTIVE: The ocular vascular system plays an important role in preserving the visual function. Alterations in either anatomy or hemodynamics of the eye may have adverse effects on vision. Thus, an imaging approach that can monitor alterations of ocular blood flow of the deep eye vasculature ranging from capillary-level vessels to large supporting vessels would be advantageous for detection of early stage retinal and optic nerve diseases. METHODS: We propose a super-resolution ultrasound localization microscopy (ULM) technique that can assess both the microvessel and flow velocity of the deep eye with high resolution. Ultrafast plane wave imaging was acquired using an L22-14v linear array on a high frequency Verasonics Vantage system. A robust microbubble localization and tracking technique was applied to reconstruct ULM images. The experiment was first performed on pre-designed flow phantoms in vitro and then tested on a New Zealand white rabbit eye in vivo calibrated to various intraocular pressures (IOP) - 10 mmHg, 30 mmHg and 50 mmHg. RESULTS: We demonstrated that retinal/choroidal vessels, central retinal artery, posterior ciliary artery, and vortex vein were all visible at high resolution. In addition, reduction of vascular density and flow velocity were observed with elevated IOPs. CONCLUSION: These results indicate that super-resolution ULM is able to image the deep ocular tissue while maintaining high resolution that is comparable with optical coherence tomography angiography. SIGNIFICANCE: Capability to detect subtle changes of blood flow may be clinically important in detecting and monitoring eye diseases such as glaucoma.

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Prostate cancer is the second leading cause of cancer death in men. Its current treatment includes various physical and chemical approaches for the localized and advanced prostate cancer [e.g. metastatic castrate resistant prostate cancer (mCRPC)]. Although many new drugs are now available for prostate cancer, none is suitable for local treatment that can reduce adverse effects often associated with the current physical treatment. Of the drugs approved by FDA for mCRPC, the best mean improvement in overall survival is only about 4.8 months. Therefore, there is a need for improved treatment approaches for prostate cancer, especially drug-resistant cancer.Ultrasound therapy represents a useful new physical approach for the drug-resistant cancer treatment by facilitating the entry of the related chemotherapy drug into the target cancer cells. There are two versions of ultrasound: High Intensity Focused Ultrasound (HIFU) and Low Intensity Pulsed Ultrasound (LIPUS). HIFU has been a promising treatment option for prostate cancer due to its noninvasiveness and various biological effects on cancer tissue. It has been approved for the treatment of cancer and in recent years there have been numerous findings suggesting HIFU can reduce cancer cell viability and possibly reverse the spread of cancerous tumors. LIPUS is currently being studied as an alternative treatment option for prostate cancer. Preliminary studies have found LIPUS to reduce cancer cell viability without the side effects seen in HIFU. Reversible cell membrane damage caused by LIPUS could allow increased uptake of anticancer drugs, enhancing cytotoxicity and death of cancer cells. In this way, a low dose of anticancer drug is more effective toward cancer cells while there is less damage to normal cells. The combination of LIPUS with certain chemotherapeutic agents can be an exciting physical-chemical combination therapy for prostate cancer. This review will focus on this topic as well as the clinical use of HIFU to provide an understanding of their current use and future potential role for prostate cancer therapy.

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The clinical application of breast ultrasound for the assessment of cancer risk and of deep learning for the classification of breast-ultrasound images has been hindered by inter-grader variability and high false positive rates and by deep-learning models that do not follow Breast Imaging Reporting and Data System (BI-RADS) standards, lack explainability features and have not been tested prospectively. Here, we show that an explainable deep-learning system trained on 10,815 multimodal breast-ultrasound images of 721 biopsy-confirmed lesions from 634 patients across two hospitals and prospectively tested on 912 additional images of 152 lesions from 141 patients predicts BI-RADS scores for breast cancer as accurately as experienced radiologists, with areas under the receiver operating curve of 0.922 (95% confidence interval (CI) = 0.868-0.959) for bimodal images and 0.955 (95% CI = 0.909-0.982) for multimodal images. Multimodal multiview breast-ultrasound images augmented with heatmaps for malignancy risk predicted via deep learning may facilitate the adoption of ultrasound imaging in screening mammography workflows.

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Currently, blindness cannot be cured and patients' living quality can be compromised severely. Ultrasonic (US) neuromodulation is a promising technology for the development of noninvasive cortical visual prosthesis. We investigated the feasibility of transcranial focused ultrasound (tFUS) for noninvasive stimulation of the visual cortex (VC) to develop improved visual prosthesis. tFUS was used to successfully evoke neural activities in the VC of both normal and retinal degenerate (RD) blind rats. Our results showed that blind rats showed more robust responses to ultrasound stimulation when compared with normal rats. ( , two-sample t-test). Three different types of ultrasound waveforms were used in the three experimental groups. Different types of cortical activities were observed when different US waveforms were used. In all rats, when stimulated with continuous ultrasound waves, only short-duration responses were observed at "US on and off" time points. In comparison, pulsed waves (PWs) evoked longer low-frequency responses. Testing different parameters of PWs showed that a pulse repetition frequency higher than 100 Hz is required to obtain the low-frequency responses. Based on the observed cortical activities, we inferred that acoustic radiation force (ARF) is the predominant physical mechanism of ultrasound neuromodulation.

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PURPOSE: To quantitatively investigate both optic nerve head (ONH) and peripapillary sclera (PPS) biomechanical properties of porcine eyes through an ultrasonic elastography imaging system in response to both increasing and decreasing intraocular pressure (IOP). METHODS: The Young's modulus of the ONH and PPS were assessed using our high resolution ultrasonic imaging system which utilized a mechanical shaker to induce shear waves and an off-axis aligned 40 MHz needle transducer to track micron-level displacement along the direction of wave propagation. In this study, imaging on a total of 8 ex vivo porcine eyes preloaded with IOPs from 6 mmHg to 30 mmHg was performed. To have a better understanding of the effect of varying IOP on biomechanics, both increasing and decreasing IOPs were investigated. RESULTS: The increase of the Young's modulus of ONH (92.4 ± 13.9 kPa at 6 mmHg to 224.7 ± 71.1 kPa at 30 mmHg) and PPS (176.8 ± 14.3 kPa at 6 mmHg to 573.5 ± 64.4 kPa at 30 mmHg) following IOP elevation could be observed in the reconstructed Young's modulus of the shear wave elasticity (SWE) imaging while the B-mode structural images remained almost unchanged. In addition, for the same IOP level, both ONH and PPS have a tendency to be stiffer with decreasing IOP as compared to increasing IOP. CONCLUSIONS: Our results demonstrate the feasibility of using our ultrasonic elastography system to investigate the stiffness mapping of posterior eye with high resolution in both increasing and decreasing IOPs, making this technique potentially useful for glaucoma.

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Mechanical properties of biological tissues are significant biomarkers for diagnosing various diseases. Assessing the viscoelastic properties of multi-layer tissues has remained challenging for a long time. Some shear wave models have been proposed to estimate thin-layer tissues' viscoelasticity recently. However, the potential applications of these models are highly restricted since few biological tissues are single-layered. Here we proposed a multi-layer model for layer-specific viscoelasticity estimation of biological tissues. Integrating the theoretical model and ultrasonic micro-elastography imaging system, the viscoelasticity of both layers was assessed. Dual-layer phantoms and ex vivo porcine eyes were used to verify the proposed model. Results obtained from the mechanical test and shear wave rheological model using bulk phantoms were provided as validation criteria. The representative phantom had two layers with elastic moduli of 1.6 ± 0.2 kPa and 18.3 ± 1.1 kPa, and viscosity moduli of 0.56 ± 0.16 Pa·s and 2.11 ± 0.28 Pa·s, respectively. The estimated moduli using the proposed model were 1.3 ± 0.2 kPa and 16.20 ± 1.8 kPa, and 0.80 ± 0.31 Pa·s and 1.87 ± 0.67 Pa·s, more consistent with the criteria (one-tailed t-test, p < 0.1). By contrast, other methods, including the group velocity method and single-layer Rayleigh-Lamb model, generate significant errors in their estimates. For the ex vivo porcine eye, the estimated viscoelasticity was 23.2 ± 8.3 kPa and 1.0 ± 0.4 Pa·s in the retina, and 158.0 ± 17.6 kPa and 1.2 ± 0.4 Pa·s in the sclera. This study demonstrated the potential of the proposed method to significantly improve accuracy and expand clinical applications of shear wave elastography.

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Acoustic radiation force optical coherence elastography (ARF-OCE) has been successfully implemented to characterize the biomechanical properties of soft tissues, such as the cornea and the retina, with high resolution using single-element ultrasonic transducers for ARF excitation. Most currently proposed OCE techniques, such as air puff and ARF, have less capability to control the spatiotemporal information of the induced region of deformation, resulting in limited accuracy and low temporal resolution of the shear wave elasticity imaging. In this study, we propose a new method called 2-D ultrasonic array-based OCE imaging, which combines the advantages of 3-D dynamic electronic steering of the 2-D ultrasonic array and high-resolution optical coherence tomography (OCT). The 3-D steering capability of the 2-D array was first validated using a hydrophone. Then, the combined 2-D ultrasonic array OCE system was calibrated using a homogenous phantom, followed by an experiment on ex vivo rabbit corneal tissue. The results demonstrate that our newly developed 2-D ultrasonic array-based OCE system has the capability to map tissue biomechanical properties accurately, and therefore, has the potential to be a vital diagnostic tool in ophthalmology.

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Focused ultrasound (FUS) is a rapidly developing stimulus technology with the potential to uncover novel mechanosensory dependent cellular processes. Since it is non-invasive, it holds great promise for future therapeutic applications in patients used either alone or as a complement to boost existing treatments. For example, FUS stimulation causes invasive but not non-invasive cancer cell lines to exhibit marked activation of calcium signaling pathways. Here, we identify the membrane channel PANNEXIN1 (PANX1) as a mediator for activation of calcium signaling in invasive cancer cells. Knockdown of PANX1 decreases calcium signaling in invasive cells, while PANX1 overexpression enhances calcium elevations in non-invasive cancer cells. We demonstrate that FUS may directly stimulate mechanosensory PANX1 localized in endoplasmic reticulum to evoke calcium release from internal stores. This process does not depend on mechanosensory stimulus transduction through an intact cytoskeleton and does not depend on plasma membrane localized PANX1. Plasma membrane localized PANX1, however, plays a different role in mediating the spread of intercellular calcium waves via ATP release. Additionally, we show that FUS stimulation evokes cytokine/chemokine release from invasive cancer cells, suggesting that FUS could be an important new adjuvant treatment to improve cancer immunotherapy.

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Drug resistance is an obstacle in the therapy of acute lymphoblastic leukemia (ALL). Whether the physical properties such as the motility of the cells contribute to the survival of ALL cells after drug treatment has recently been of increasing interest, as they could potentially allow the metastasis of solid tumor cells and the migration of leukemia cells. We hypothesized that chemotherapeutic treatment may alter these physical cellular properties. To investigate the motility of chemotherapeutics-treated B-cell ALL (B-ALL) cells, patient-derived B-ALL cells were treated with chemotherapy for 7 days and left for 12 h without chemotherapeutic treatment. Two parameters of motility were studied, velocity and migration distance, using a time-lapse imaging system. The study revealed that compared to non-chemotherapeutically treated B-ALL cells, B-ALL cells that survived chemotherapy treatment after 7 days showed reduced motility. We had previously shown that Tysabri and P5G10, antibodies against the adhesion molecules integrins α4 and α6, respectively, may overcome drug resistance mediated through leukemia cell adhesion to bone marrow stromal cells. Therefore, we tested the effect of integrin α4 or α6 blockade on the motility of chemotherapeutics-treated ALL cells. Only integrin α4 blockade decreased the motility and velocity of two chemotherapeutics-treated ALL cell lines. Interestingly, integrin α6 blockade did not affect the velocity of chemoresistant ALL cells. This study explores the physical properties of the movements of chemoresistant B-ALL cells and highlights a potential link to integrins. Further studies to investigate the underlying mechanism are warranted.

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In glucose-stimulated insulin secretion (GSIS) of pancreatic ß-cells, the rise of free cytosolic Ca2+ concentration through voltage-gated calcium channels (VGCCs) triggers the exocytosis of insulin-containing granules. Recently, mechanically induced insulin secretion pathways were also reported, which utilize free cytosolic Ca2+ ions as a direct regulator of exocytosis. In this study, we aimed to investigate intracellular Ca2+ responses on the HIT-T15 pancreatic ß-cell line upon low-intensity pulsed ultrasound (LIPUS) stimulation and found that ultrasound induces two distinct types of intracellular Ca2+ oscillation, fast-irregular and slow-periodic, from otherwise resting cells. Both Ca2+ patterns depend on the purinergic signaling activated by the rise of extracellular ATP or ADP concentration upon ultrasound stimulation, which facilitates the release through mechanosensitive hemichannels on the plasma membrane. Further study demonstrated that two subtypes of purinergic receptors, P2X and P2Y, are working in a competitive manner depending on the level of glucose in the cell media. The findings can serve as an essential groundwork providing an underlying mechanism for the development of a new therapeutic approach for diabetic conditions with further validation.

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Single-beam acoustic tweezers (SBAT) is a widely used trapping technique to manipulate microscopic particles or cells. Recently, the characterization of a single cancer cell using high-frequency (>30 MHz) SBAT has been reported to determine its invasiveness and metastatic potential. Investigation of cell elasticity and invasiveness is based on the deformability of cells under SBAT's radiation forces, and in general, more physically deformed cells exhibit higher levels of invasiveness and therefore higher metastatic potential. However, previous imaging analysis to determine substantial differences in cell deformation, where the SBAT is turned ON or OFF, relies on the subjective observation that may vary and requires follow-up evaluations from experts. In this study, we propose an automatic and reliable cancer cell classification method based on SBAT and a convolutional neural network (CNN), which provides objective and accurate quantitative measurement results. We used a custom-designed 50 MHz SBAT transducer to obtain a series of images of deformed human breast cancer cells. CNN-based classification methods with data augmentation applied to collected images determined and validated the metastatic potential of cancer cells. As a result, with the selected optimizers, precision, and recall of the model were found to be greater than 0.95, which highly validates the classification performance of our integrated method. CNN-guided cancer cell deformation analysis using SBAT may be a promising alternative to current histological image analysis, and this pretrained model will significantly reduce the evaluation time for a larger population of cells.

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OBJECTIVE: The choroidal vessels, which supply oxygen and nutrient to the retina, may play a pivotal role in eye disease pathogenesis such as diabetic retinopathy and glaucoma. In addition, the retrobulbar circulation that feeds the choroid shows an important pathophysiologic role in myopia and degenerative myopia. Owing to the light-absorbing retinal pigment epithelium (RPE) and optically opaque sclera, choroidal and retrobulbar vasculature were difficult to be observed using clinically accepted optical coherence tomography angiography (OCT-A) technique. Here, we have developed super-resolution ultrasound microvessel imaging technique to visualize the deep ocular vasculature. METHODS: An 18-MHz linear array transducer with compounding plane wave imaging technique and contrast agent - microbubble was implemented in this study. The centroid intensity of each microbubble was detected using image deconvolution algorithm with spatially variant point spread function, and then accumulated in successive frames in order to reconstruct microvasculature. The image deconvolution technique was first evaluated in a simulation study and experimental flow phantoms. The performance was then validated on normal rabbit eyes in vivo. RESULTS: The image deconvolution based super-resolution ultrasound microvessel imaging technique shows good performance on either simulation study or flow phantoms. In vivo rabbit eye study indicated that the micron-level choroidal and retrobulbar vessels around the optic nerve head were successfully reconstructed in multiple 2D views and 3D volume imaging. CONCLUSIONS: Our results demonstrate the capability of using super-resolution ultrasound microvessel imaging technique to image the microvasculature of the posterior pole of the eye. This efficient approach can potentially lead to a routinely performed diagnostic procedure in the field of ophthalmology.

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OBJECTIVES: To develop a dual-modal neural network model to characterize ultrasound (US) images of breast masses. MATERIALS AND METHODS: A combined US B-mode and color Doppler neural network model was developed to classify US images of the breast. Three datasets with breast masses were originally detected and interpreted by 20 experienced radiologists according to Breast Imaging-Reporting and Data System (BI-RADS) lexicon ((1) training set, 103212 masses from 45,433 + 12,519 patients. (2) held-out validation set, 2748 masses from 1197 + 395 patients. (3) test set, 605 masses from 337 + 78 patients). The neural network was first trained on training set. Then, the trained model was tested on a held-out validation set to evaluate agreement on BI-RADS category between the model and the radiologists. In addition, the model and a reader study of 10 radiologists were applied to the test set with biopsy-proven results. To evaluate the performance of the model in benign or malignant classifications, the receiver operating characteristic curve, sensitivities, and specificities were compared. RESULTS: The trained dual-modal model showed favorable agreement with the assessment performed by the radiologists (κ = 0.73; 95% confidence interval, 0.71-0.75) in classifying breast masses into four BI-RADS categories in the validation set. For the binary categorization of benign or malignant breast masses in the test set, the dual-modal model achieved the area under the ROC curve (AUC) of 0.982, while the readers scored an AUC of 0.948 in terms of the ROC convex hull. CONCLUSION: The dual-modal model can be used to assess breast masses at a level comparable to that of an experienced radiologist. KEY POINTS: • A neural network model based on ultrasonic imaging can classify breast masses into different Breast Imaging-Reporting and Data System categories according to the probability of malignancy. • A combined ultrasonic B-mode and color Doppler neural network model achieved a high level of agreement with the readings of an experienced radiologist and has the potential to automate the routine characterization of breast masses.

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