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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.

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.

Ultrasound neuromodulation is an emerging technology. A significant amount of effort has been devoted to investigating the feasibility of noninvasive ultrasound retinal stimulation. Recent studies have shown that ultrasound can activate neurons in healthy and degenerated retinas. Specifically, high-frequency ultrasound can evoke localized neuron responses and generate patterns in visual circuits. In this review, we recapitulate pilot studies on ultrasound retinal stimulation, compare it with other neuromodulation technologies, and discuss its advantages and limitations. An overview of the opportunities and challenges to develop a noninvasive retinal prosthesis using high-frequency ultrasound is also provided.

Current elastography techniques in the field of ophthalmology usually target one specific tissue, such as the cornea or the sclera. However, the eye is an inter-related organ, and some ocular diseases can alter the biomechanical properties of multiple anatomical structures. Hence, there is a need to develop an imaging tool that can non-invasively, quantitatively, and accurately characterize dynamic changes among these biomechanical properties.A high resolution ultrasound elastography system was developed to achieve this goal. The efficacy and accuracy of the system was first validated on tissue-mimicking phantoms while mechanical testing measurements served as the gold standard. Next, an in vivo elevated intraocular pressure (IOP) model was established in rabbits to further test our system. In particular, elastography measurements were obtained at 5 IOP levels, ranging from 10 mmHg to 30 mmHg in 5 mmHg increments. Spatial-temporal maps of the multiple ocular tissues (cornea, lens, iris, optic nerve head, and peripapillary sclera) were obtained.The spatial-temporal maps were acquired simultaneously for the ocular tissues at the 5 different IOP levels. The statistical analysis of the elastic wave speed was presented for ocular tissues. Finally, the mapping for the elastic wave speed of each ocular component was acquired at each IOP level.Our elastography system can concurrently assess the biomechanical properties of multiple ocular structures and detect changes in biomechanical properties associated with changes in IOP.This system provides a novel tool to measure and quantify the biomechanical properties of the whole eye.

There is uncertainty about deep vein thrombosis standard treatment as thrombus stiffness alters each case. Here, we investigated thrombus' stiffness of different compositions and ages using shear wave elastography (SWE). We then studied the effectiveness of ultrasound-thrombolysis on different thrombus compositions.Shear waves generated through mechanical shaker and traveled along thrombus of different hematocrit (HCT) levels, whereas 18-MHz ultrasound array used to detect wave propagation. Thrombus' stiffness was identified by the shear wave speed (SWS). In thrombolysis, a 3.2 MHz focused transducer was applied to different thrombus compositions using different powers. The thrombolysis rate was defined as the percentage of weight loss.The estimated average SWS of 20%, 40%, and 60% HCT thrombus were 0.75 m/s, 0.44 m/s, and 0.32 m/s, respectively. For Thrombolysis, the percentage weight loss at 8 MPa Negative pressure for the same HCT groups were 23.1%, 35.29%, and 39.66% respectively.SWS is inversely related to HCT level and positively related to thrombus age. High HCT thrombus had higher weight loss compared to low HCT. However, the difference between 20% and 40% HCT was more significant than between 40% and 60% HCT in both studies. Our results suggest that thrombus with higher SWS require more power to achieve the same thrombolysis rate as thrombus with lower SWS.Characterizing thrombus elastic property undergoing thrombolysis enables evaluation of ultrasound efficacy for fractionating thrombus and reveals the appropriate ultrasound parameters selection to achieve a certain thrombolysis rate in the case of a specific thrombus stiffness.

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. ( ${p} , 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.

Since the emergence of the COVID-19 pandemic in December of 2019, clinicians and scientists all over the world have faced overwhelming new challenges that not only threaten their own communities and countries but also the world at large. These challenges have been enormous and debilitating, as the infrastructure of many countries, including developing ones, had little or no resources to deal with the crisis. Even in developed countries, such as Italy, health systems have been so inundated by cases that health care facilities became oversaturated and could not accommodate the unexpected influx of patients to be tested. Initially, resources were focused on testing to identify those who were infected. When it became clear that the virus mainly attacks the lungs by causing parenchymal changes in the form of multifocal pneumonia of different levels of severity, imaging became paramount in the assessment of disease severity, progression, and even response to treatment. As a result, there was a need to establish protocols for imaging of the lungs in these patients. In North America, the focus was on chest X-ray and computed tomography (CT) as these are widely available and accessible at most health facilities. However, in Europe and China, this was not the case, and a cost-effective and relatively fast imaging modality was needed to scan a large number of sick patients promptly. Hence, ultrasound (US) found its way into the hands of Chinese and European physicians and has since become an important imaging modality in those locations. US is a highly versatile, portable, and inexpensive imaging modality that has application across a broad spectrum of conditions and, in this way, is ideally suited to assess the lungs of COVID-19 patients in the intensive care unit (ICU). This bedside test can be done with little to no movement of the patients from the unit that keeps them in their isolated rooms, thereby limiting further exposure to other health personnel. This article presents a basic introduction to COVID-19 and the use of the US for lung imaging. It further provides a high-level overview of the existing US technologies that are driving development in current and potential future US imaging systems for lung, with a specific emphasis on portable and 3-D systems.

To develop a dual-modal neural network model to characterize ultrasound (US) images of breast masses. 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. 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. The dual-modal model can be used to assess breast masses at a level comparable to that of an experienced radiologist. • 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.

In this paper, Smoothed Particle Hydrodynamics (SPH) method is introduced into the study of the temperature characteristics of the cathode micro-protrusion with considering the resistive heating caused by field emission current. Firstly, the partial differential equations for hydrodynamics with material strength are established. Then, the kernel approximation is used to approximate the field function in the partial differential equations, and the particle approximation is used to discretize the kernel approximation equations in order to obtain a series of SPH governing equations. At the same time, the heat conduction equation with considering Joule heat is introduced into the SPH governing equations. Based on the source code of SPH, the mathematical model of cathode micro-protrusion is established. The SPH equations are solved by using the explicit integration method. The temperature distributions of cathode micro-protrusion with different field emission current Joule heat are simulated. The results can provide theoretical guidance for the quantitative study of the physical mechanism of vacuum breakdown induced by field emission.

The prediction and pre-evaluation of the thermal properties and combustion-related problems (e.g., emissions and ash-related problems) are critical to reducing emissions and improving combustion efficiency during the agricultural crop residues combustion process. This study integrated the higher heating value (HHV) model, specific heat model, and fuel indices as a new systematic approach to characterize the agricultural crop residues. Sixteen linear and non-linear regression models were developed from three main compositions of the ultimate analysis (e.g., C, H, and O) to predict the HHV of the agricultural crop residues. Newly developed HHV models have been validated with lower estimation errors and a higher degree of accuracy than the existing models. The specific heat of flue gas during the combustion process was estimated from the concentrations of C, H, O, S, and ash content under various excess air (EA) ratios and flue gas temperatures. The specific heat of agricultural crop residues was between 1.033 to 1.327 kJ/kg·K, while it was increased by decreasing the EA ratios and elevating the temperature of the flue gas. Combustion-related problems, namely corrosions, PM1.0 emissions, SOx, HCl, and ash-related problems were predicted using the fuel indices along with S and Cl concentrations, and ash compositions. Results showed that agricultural crop residues pose a severe corrosion risk and lower ash sintering temperature. This integrated approach can be applied to a wide range of biomass before the actual combustion process which may predict thermal-chemical properties and reduce the potential combustion-related emissions.

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 2D ultrasonic array-based optical coherence elastography imaging, which combines the advantages of 3D dynamic electronic steering of the 2D ultrasonic array and high-resolution optical coherence tomography (OCT). The 3D steering capability of the 2D array was first validated using a hydrophone. Then, the combined 2D 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 2D 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.

We characterized the stiffness and anisotropy of the equatorial sclera and its dependence on intraocular pressure (IOP). Porcine eyes were tested using ultrasound elastography under IOP control. Shear waves were induced using a mechanical shaker, and an off-axis 17.8 MHz transducer used to track the wave propagation in the equatorial and anterior-posterior directions. Wave speed was measured and used to estimate directional Young’s moduli. Anisotropy was defined as the ratio of the equatorial moduli to the anterior-posterior moduli. Sclera was stiffer in the equatorial direction, with anisotropy decreasing with IOP, from, 5.1 at 10 mmHg to 3.7 at 30 mmHg.

Background Quantitatively investigating the biomechanics of retina with a retinal prosthetic electrode, we explored the effects of the prosthetic electrode on the retina, and further supplemented data for a potential clinical trial. Methods Biomechanical properties were assessed with a high resolution optical coherence tomography (OCT) based elastography (OCE) system. A shaker was used to initiate elastic waves and an OCT system was used to track axial displacement along with wave propagation. Rabbits received surgery to implant the retinal prosthetic electrode, and elastic wave speed was measured before and after implantation; anatomical B-mode images were also acquired. Results Spatial-temporal maps of each layer in retina with and without prosthetic electrodes were acquired. Elastic wave speed of nerve fiber to inner plexiform layer, inner nuclear to outer nuclear layer, retinal pigmented epithelium layer and choroid to sclera layer without prosthetic electrode were found to be 3.66±0.36, 5.33±0.07, 6.85±0.37, and 9.69±0.24 m/s, respectively. With prosthetic electrode, the elastic wave speed was found to be 4.09±0.26, 5.14±0.11, 6.88±0.70, and 9.99±0.73 m/s, respectively in each layer. Conclusions Our results show that the elastic wave speed in each layer of retina is slightly faster with the retinal electrode, and further demonstrate that the retinal prosthetic electrode does not affect biomechanical properties significantly. In the future, we expect OCE technology to be used by clinicians where it could become part of routine testing and evaluation of the biomechanical properties of the retina in response to long term use of prosthetic electrodes in patients.

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.

Alzheimer's disease (AD) causes severe cognitive dysfunction and has long been studied for the underlining physiological and pathological mechanisms. Several biomedical imaging modalities have been applied, including MRI, PET, and high-resolution optical microscopy, for research purposes. However, there is still a strong need for imaging tools that can provide high spatiotemporal resolutions with relatively deep penetration to enhance our understanding of AD pathology and monitor treatment progress in fundamental research. Photoacoustic (PA) imaging and ultrasound (US) imaging can potentially address these unmet needs in AD research. PA imaging provides functional information with endogenous and/or exogenous contrast, while US imaging provides structural information. Recent studies have demonstrated the ability to monitor physiological parameters in small-animal brains with PA and US imaging as well as the feasibility of using US imaging as a therapeutic tool for AD. This concise review aims to introduce recent advances in AD research using PA and US imaging, provide the fundamentals, and discuss the potentials and challenges for future advances.

Currently, blindness cannot be cured and patients' living quality can be compromised severely. Ultrasonic neuromodulation is a promising technology for the development of non-invasive cortical visual prosthesis. We investigated the feasibility of transcranial focused ultrasound (tFUS) for noninvasive stimulation of the visual cortex to develop improved visual prosthesis. tFUS was used to successfully evoke neural activities in the visual cortex (VC) of both normal and retinal degenerate (RD) blind rats. Our results showed that blind rats showed more robust responses to ultrasound stimulation compared to normal rats. (p

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.

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.

Age-related macular degeneration (AMD) is a progressive retinal disease and becomes the leading cause of blindness. It is well established that early detection is the key to preservation of functional vision. However, it is very difficult to diagnose AMD in very early stages, before structural changes are evident. Consequently, investigating the biomechanical properties of the retina maybe essential for understanding its physiological function. In this study, we present a shear wave-based quantitative method for estimating the elasticity of the posterior eye using shaker-based optical coherence elastography. This technique has been developed and validated on both a homogeneous phantom and a healthy rabbit in vivo. The shear wave speed from the ganglion side to the photoreceptor side of the rabbit eye is 4.1 m/s, 4.9 m/s, and 6.7 m/s, respectively. In addition, the most stiff sclera region has an average shear wave speed of 9.1 m/s. The results demonstrate the feasibility of using this technique to quantify biomechanical properties of the posterior eye and its potential translation to the clinical study. Impact statement Herein, we propose a potentially clinical applicable shaker-based optical coherence elastography (OCE) technique to characterize the biomechanical properties of the posterior eye, including different layers of the retina. Compared with either acoustic radiation force OCE or air-puff OCE, the newly developed method can induce sufficient shear wave propagation at the posterior eye with high resolution and large field of view.

Iron cyanide complexes are common contaminants at former manufactured gas plant sites. Although combined forms of cyanide have low toxicity, iron cyanide complexes can be decomposed to HCN through photolysis. This experiment was designed to evaluate the efficiency of phytoremediation and investigate potential toxic effect for iron cyanide complexes (i.e., ferric ferrocyanide) using the cyanogenic and non-cyanogenic plants in soil. Results showed that Sorghum (a cyanogenic plant) had the highest cyanide degradation in the root zone with the removal of approximately 32% while Switchgrass (a non-cyanogenic plant) and Flax (a cyanogenic plant) had 21% and 17% removal, respectively, with 4% dissipation in unvegetated soil. It was found that roots had higher cyanide concentrations than plant shoots. Water-soluble cyanide and the weak acid dissociable (WAD) fraction in the soil had increased at the end of the experiment, suggesting that plant may enhance the mobility and bioavailability of cyanide by root exudation. The risk associated with the leaching of cyanide compounds was assessed with the toxicity assay (Microtox). However, results indicated that the leachate from the pots was not toxic.

In the past few decades, water and air were commonly used as working fluid to evaluate shell and tube heat exchanger (STHE) performance. This study was undertaken to estimate heat transfer coefficients and evaluate performance in the pilot-scale twisted tube-based STHE using the flue gas from biomass co-combustion as working fluid. Theoretical calculation along with experimental results were used to calculate the specific heat of flue gas. A simplified model was then developed from the integration of two heat transfer methods to predict the overall heat transfer coefficient without tedious calculation of individual heat transfer coefficients and fouling factors. Performance including water and trailer temperature, heat load, effectiveness, and overall heat transfer coefficient were jointly investigated under variable operating conditions. Results indicated that the specific heat of flue gas from co-combustion ranging between 1.044 and 1.338 kJ/kg·K while specific heat was increased by increasing flue gas temperature and decreasing excess air ratio. The developed mathematical model was validated to have relatively small errors to predict the overall heat transfer coefficient. A flue gas mass flow rate of 61.3–98.8 kg/h, a water flow rate of 13.7–14.1 L/min, and a parallel arrangement of two water-to-air heaters in an empty trailer were found to be optimal conditions for space heating purpose. In addition, a lower poultry litter feeding rate decreased heat loss of flue gas and increased heat gain of water, while a lower water flow rate also provided a lower maximum possible heat transfer rate with a higher actual heat transfer rate to quickly achieve heat equilibrium that ultimately improves the performance. This study demonstrates the possibility of collecting residual heat from the flue gas using the pilot-scale STHE system while outlining a systematic approach and process for evaluating its performance.

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. An explainable deep-learning system prospectively predicts clinical scores for breast cancer risk from multimodal breast-ultrasound images as accurately as experienced radiologists.