1pBA6 – Tickling neurons with ultrasound

Elisa Konofagou, Ph.D. – ek2191@columbia.edu
Department of Biomedical Engineering
Columbia University
351 Engineering Terrace, mail code 8904
1210 Amsterdam Avenue
New York, NY 10027

Popular version of paper 1pBA6
Presented Monday morning, May 7, 2018
175th ASA Meeting, Minneapolis, MN

Stimulation of the brain has been a topic of curiosity of humans since the beginning of time. Being able to selectively stimulate the brain to enhance performance such as think deeper and remember faster remains, a formidable challenge. Mapping the circuitry of the entire healthy human brain remains an equally unattainable goal. Brain mapping entails the study of biological functions of different regions in the brain. Although many regions of the brain have already been identified, there is very little known as to how the different regions communicate and whether activation patterns observed during specific behaviors are causally related to those behaviors. Such a brain map would not only further the understanding of the brain itself, but also potentially lead to novel cures or treatments for neurological conditions. One way to aid the progress in brain mapping is neurostimulation, a technique used to stimulate or activate neurons in the brain, usually by means of an electrode. When the electrode delivers a stimulus pulse to a targeted brain region, the biological response associated with that area will occur. Ultrasound has been consistently reported for neuronal stimulation for several decades in both animals and humans including eliciting brain activity detected by functional MRI and electroencephalography. In addition, this knowledge can be used to understand the differences between normal and pathological brains to treat patients.

In the peripheral nervous system, ultrasound has been reported since 1929 to stimulate nerves in excised frog muscle fibers and to this day the majority of the studies so far have entailed stimulation of excised nerves. The leading technique to treat peripheral neurological disorders is implantation of electrodes along the peripheral nerve and stimulating the nerve with electrical current. A noninvasive alternative that could treat neuropathic pain and suppress nerve activity constitutes thus an important challenge in interventional neurology.

i) ii)
iii)neurons iv)

Figure 1: i) FUS setup for neuromodulation, cameras recording hind limb and tail movements and pupil dilation and eye movement. ii) Recorded left hind paw movement (before (purple) after (green) movement), iii) FUS-induced motor response elicitation: EMG of the right hind limb during contralateral evoked response for different acoustic pressure levels with the success rate increasing at larger pressures and iv) contralateral paw movement elicited by FUS neurostimulation.

Our group has been studying the noninvasive stimulation or inhibition of both the central and peripheral nervous system in live animals. In the brain, we have shown that focused ultrasound is capable of noninvasively stimulating paw movement as well as sensory responses such as pupil dilation and eye movement when different brain regions are targeted, showing for the first time that ultrasound can tap into both the motor and sensory brain regions (Fig. 1). In the periphery, when the ultrasound beam is focused on the sciatic nerve in a live, anesthetized animal, the thigh muscle becomes activated and muscle twitches can be induced at low ultrasonic intensities while the same twitches can be inhibited at higher intensities due to associated temperature rise that inhibits nerve firing. Cellular and fiber responses in excised tissue have confirmed the live animal responses (Fig. 2).

a)neurons
b)

Figure 2:  FUS compared to electrical modulation: a) Ex vivo measurements of action potentials in a nerve bundle through FUS (red) and electrical stimulation; b) in vivo EMG responses in murine leg muscle at different FUS pressures and duty cycles. FUS elicits very similar motor responses as electrical stimulation (E.S.; dashed horizontal line), especially at higher pressures and duty cycles.

4pBA5 – Plane-wave vector-flow imaging of adult mouse heart

Jeffrey Ketterling– jketterling@riversideresearch.org
Lizzi Center for Biomedical Engineering
Riverside Research
New York, NY 10038

Akshay Shekhar, Orlando Aristizabal
Skirball Institute of Biomolecular Medicine
NYU School of Medicine
New York, NY

Anthony Podkowa
Electrical and Computer Engineering
4251 Beckman Institute MC 251
405 N. Mathews, Urbana Illinois 61801

Billy Y.S. Yiu, Alfred C.H. Yu
Department of Electrical and Computer Engineering
University of Waterloo
Waterloo, ON, Canada

Popular version of paper 4pBA5, “Plane-wave vector-flow imaging of adult mouse heart”
Presented Thursday afternoon, December 6, 2017, 4:30 PM
175th ASA Meeting, Minneapolis

heart

The blood injected in the left ventricle of the mouse heart results in a vortex pattern just as in humans.

Doppler ultrasound is a well established clinical technique to measure blood flow in humans. The method makes use of the Doppler effect to detect small changes in position over time. It is used extensively for cardiovalscular evaluations to detect abnormal blood flow conditions. Traditional Doppler is used either to detect the presence of blood or to assess flow conditions in blood vessels where the flow is more or less steady. Traditional Doppler is only able to assess the flow in the direction normal to the transducer or essentially in the direction that the ultrasound propogates. To estimate the flow velocity that is not in the normal direction, an estimate must be made of the angle between the normal direction and the flow direction. Traditional Doppler is not very effective when trying to image complex flow patterns such as those found in the heart where vortex patterns are formed.

In recent years, advances in ultrasound equipment and computational power have permitted the detection of flow patterns through estimates of local flow vectors using Doppler and other approaches. The methods have been used on humans and the equipment required to perform this type of blood-flow imaging is becoming more widespread and clinical applications are slowly emerging.

Mice are used extensively for cardiovascular studies because many diseases in humans are represented in mouse models. Specialized ultrasound equipment is available to perform Doppler studies on mice. The main difference between the equipment for humans and the equipment for mice is the operating ultrasound frequency. Humans require around 10 MHz frequencies and mice upwards of 20 MHz. Because of this, the vector-flow methods applied to humans have not yet been adapted to imaging mice. The ability to apply the vector-flow approaches to mice would allow for direct translational studies that would facilitate understanding how the complex blood flow patterns in the heart related to healthy heart function.

We undertook initial studies to obtain vector flow information from the left ventricle of a mouse. Data were acquired transmitted ultrasound at an absolute rate of 30,000 frames per second. The effective frame rate after processing was 10,000 frames per second. In terms of flow, the maximum velocity that can be resolved before aliasing in the direction of the ultrasound was 21 cm/s. A video clip [movie] showing 3 hearts cycles, spanning 300 ms, is shown. The flow is indicated by vectors that point in the direction of flow and are colored based on the flow velocity.  Over the heart cycle, the left ventricle can clearly be seen filling via the mitral valve [Fig 1] before developing a vortex pattern [Fig 2] and then the blood is ejected through the aortic valve.

heartFigure 1. Blood flow into the left ventricle through the mitral valve. The flow velocity is near 100 cm/s. Doppler spectrogram from a region near mitral valve. heartFigure 2. After the mitral valve close, a vortex pattern has developed prior to ejection of the blood in the left ventricle.

These initial studies show that the sophisticated methods used to image cardiac mechanics and hemodynamics in humans can be translated to mice. Having similar tools for mice and men will assist in developing applications using vector flow and for understanding fundamental properties of cardiovascular function as they relate to blood flow, mechanics and the related forces between the two. 

This movie shows several heart cycles and the blood flow patterns.

[1] B. Y. S. Yiu and A. C. H. Yu, “Least-squares multi-angle Doppler estimators for plane wave vector flow imaging.” IEEE Trans Ultrason Ferroelectr Freq Control, vol. 63, no. 11, pp. 1733–1744, 2016.

[2] 2.  J.A. Ketterling, O. Aristizábal, B.Y.S. Yiu, D.H. Turnbull, C.K.L. Phoon, A.C.H. Yu and R.H. Silverman, “High-speed, high-frequency ultrasound,  in utero vector-flow imaging of mouse embryos,” Scientific Reports, 7, 16558 (2017)

2pBA5 – Sensing Osteoporosis by Acoustic Waves of Ultrasound

Siavash Ghavami – roudsari.seyed@mayo.edu
Max Denis – denis.max@mayo.edu
Adriana Gregory – gregory.adriana@mayo.edu
Jeremy Webb – webb.jeremy@mayo.edu
Mahdi Bayat – bayat.mahdi@mayo.edu
Mostafa Fatemi – fatemi.mostafa@mayo.edu
Azra Alizad – alizad.azra@mayo.edu

Mayo Clinic, College of Medicine and Science,
Department of Radiology, Department of Physiology and Biomedical Engineering
200 1st St SW, Rochester, MN 55905, USA

Popular version of paper 2pBA5, “Vibro-Acoustic Method for Detection of Osteopenia and Osteoporosis”
Presented Tuseday afternoon, May 8, 2018, 2:15-2:30 PM, GREENWAY F/G
175th ASA Meeting, Minneapolis

Osteoporosis, a condition with low bone mass and micro-architectural deterioration, is the most common bone disease in adults that leads to skeletal fragility and increased risk of fracture. Age-related osteoporosis is by far the most common form of the disease, most commonly in women after menopause and older men. Osteopenia refers to bone density that is lower than normal peak density, but not low enough to be classified as osteoporosis. Bone density is a measurement of how dense and strong the bones are. If the bone density is low compared to the normal peak density, the bone is said to have osteopenia. Having osteopenia means there is a greater risk that, as time passes, it may develop bone density that is very low compared to normal, known as osteoporosis.

Assessment of bone mass and bone quality is essential for early detection of osteopenia and osteoporosis in people at risk as well as for monitoring the efficacy of various therapeutic regimens projected to reduce fractures associated with these diseases. Estimations of bone mineral density (BMD) and double energy X-ray absorptiometry (DXA) have played an important role in bone evaluation and prediction of fractures risks in recent years. Although DXA is now the gold standard for bone mass measurements in adults, this method uses x-ray which can be harmful especially if used repeatedly.

In this study, a new noninvasive method is proposed for detection of osteoporosis and osteopenia. In this method a pulse of ultrasound is used to induces vibrations in the bone, where these vibrations produce an acoustic wave that is measured by a sensitive hydrophone placed on the skin. The resulting acoustic signals are used to measure wave velocity in the bone, which in turn used to assess the bone quality. The accuracy of wave velocity estimation in the bone is affected by the complex acoustic environment. The acoustic wave in this environment can be thought of as a composition of several simpler wave components. We used an efficient technique to decompose received signal into constructing components. This allowed us to choose the wave component that represents bone vibration. Using this component we estimate wave velocity in the bone and used it to decide about the bone abnormality.

The study was done on 27 volunteers, out of those 8 had osteopenia, 6 had osteoprosis, and 13 were healthy with no bone abnormality. For each volunteer the right and left tibia (the long bone in lower leg) were tested. By comparing the wave velocities, we were able to correctly identify those osteoporosis and osteopenia from healthy individual in up to 89% of the cases. This technique can provide physicians a safe, low-cost, and portable tool for diagnosis of osteoporosis and osteopenia in patients.

Osteoporosis

Fig. 1. Estimated wave velocity in osteopenic osteoporotic and normal bones.

2pBA2 – Medical ultrasound imaging for the detection of netrin-1 in breast cancer

Jennifer Wischhusen- jennifer.wischhusen@inserm.fr
Rodolfo Molina
Frederic Padilla
LabTAU U1032, INSERM
French National Institute of Health and Medical Research
University of Lyon
Lyon, France

Jean-Guy Delcros
Benjamin Gibert
Patrick Mehlen
Cancer Research Center Lyon
French National Institute of Health and Medical Research
University of Lyon
Lyon, France

Katheryne E. Wilson
Juergen K. Willmann
Radiology, MIPS, School of Medicine
Stanford University
Stanford, CA, United States

Popular version of paper 2pBA2, “Ultrasound molecular imaging of the secreted tumor marker Netrin-1 in multiple breast cancer models”
Presented Monday, December 04, 2017, 1:15-1:30 PM, Balcony N
174th ASA meeting, New Orleans

Cancer is a disease that is defined by uncontrolled growth of cells in our body. The aberrant growth is caused by genetic errors which lead either to the gain of growth signals or the loss of growth inhibitors. Both scenarios result in normal cells growing and replicating in abnormal ways and leading to tumors. Today, molecularly targeted therapies aim at re-establishing the equilibrium of cell growth regulators in order to stop tumor growth. Unfortunately, the abnormal signals causing tumors can vary between patients. In fact, even different tumors in the same patient can have different underlying growth signals. This phenomenon is called heterogeneity. It is crucial to understand which abnormal signaling molecules are causing the patient’s tumor prior to treatment. With this information, a physician can make a more educated decision on treatment choices for each patient and their particular tumor in order to increase the chances for a positive response to therapy. This new approach is known as personalized or precision medicine.

breast cancer

Figure 1: Differences in molecular composition between different tumors. The tumor of the right patient presents netrin-1 and makes the patient eligible for netrin-1-targeted therapy. The patient on the left lacks netrin-1 and requires an alternative therapy.

Netrin-1 is a tumor-stimulating molecule which was discovered to contribute to tumor growth in different types of cancer, including 60% of metastatic breast cancer (most frequent type of cancer in women worldwide). A therapy was developed aiming at the inhibition of netrin-1’s activity and reducing tumor growth. Only tumors presenting netrin-1 are expected to benefit from netrin-1-targeted therapy while tumors without netrin-1 require alternative therapies (Figure 1). To identify breast cancer patients presenting netrin-1, we propose the use of medical ultrasound imaging. To do so, we used microbubbles, which serve as a contrast medium in ultrasound imaging. These microbubbles were modified to recognize the netrin-1 molecule when injected into the blood circulation (Figure 2).

breast cancer

Figure 2: With medical ultrasound, microbubble contrast medium can be detected. In tumors lacking netrin-1, no microbubbles accumulate and only weak background signal is detected. In tumors presenting netrin-1, netrin-1-targeting microbubbles accumulate and generate a strong signal in ultrasound imaging.

In an imaging study, the signal of netrin-1-targeted microbubbles and control microbubbles was collected from breast tumors that were known to either present netrin-1 or lack netrin-1. Our results showed an increased signal with netrin-1-targeted microbubbles in netrin-1-presenting tumors while a much lower signal was observed with control microbubbles in the same tumors (Figure 3). Tumors that lacked netrin-1 showed no accumulation of netrin-1-targeted microbubbles.

breast cancer

Figure 3: Medical ultrasound imaging with netrin-1-targeted microbubbles. Netrin-1-targeted microbubbles accumulate in breast tumors that present netrin-1 and were shown to cause a higher imaging signal than control microbubbles. The difference in imaging signal was verified by statistical analysis (*: with an e

In conclusion, our imaging study showed that these netrin-1-targeted microbubbles enable the non-invasive and near real-time visualization of netrin-1 in breast tumors using medical ultrasound imaging. We are convinced that medical ultrasound imaging can allow the detection of tumor-promoting molecules, such as netrin-1, and enable personalized medicine, which means to diagnose the molecular profile of breast cancer patients and adapt the therapy approach to the specific needs of the patient.

2pBA3 – Semi-Automated Smart Detection of Prostate Cancer using Machine Learning and a Novel Near-Microscopic Imaging Platform

Daniel Rohrbach- drohrbach@RiversideResearch.org , Jonathan Mamou and Ernest Feleppa
Lizzi Center for Biomedical Engineering, Riverside Research
New York, NY, USA, 10038

Brian Wodlinger and Jerrold Wen
Exact Imaging, Markham
Ontario, Canada, L3R 2N2

Popular version of paper 2pBA3, “Quantitative-ultrasound-based prostate-cancer imaging by means of a novel micro-ultrasound scanner”
Presented Tuesday, December 05, 2017, 1:45-2:00 PM, Balcony M
174th ASA meeting, New Orleans

Prostate cancer is the second-leading cause of male cancer-related death in the U.S. with approximately 1 in 7 men being diagnosed with prostate cancer during their lifetime[i].  Detection and diagnosis of this significant disease presents a major clinical challenge because the current standard-of-care imaging method, conventional transrectal ultrasound, cannot reliably distinguish cancerous from non-cancerous prostate tissue.  Therefore, prostate biopsies for definitively diagnosing cancer are currently delivered in a systematic but “blind” pattern.  Other imaging methods, such as MRI, have been investigated for guiding biopsies, but MRI involves complicated procedures, is costly, is poorly tolerated by most patients, and  demonstrates significant variability among clinical sites and practitioners.  Our study investigated sophisticated tissue-typing algorithms for possible use in a novel, fine-resolution, ultrasound instrument called the ExactVu™ micro-ultrasound instrument by Exact Imaging, Markham, Ontario.  The ExactVu recently has been approved for commercial sale in North America and Europe.  The term micro-ultrasound refers to the near-microscopic resolution of the device.  This new, fine-resolution instrument allows clinicians to visualize previously unseen features of the prostate in real time and enables them to differentiate suspicious regions of the prostate so that they can “target” biopsies to those suspicious regions.  To enable more-objective interpretation of tissue features made visible by the ExactVu, a cancer-risk-identification protocol – called PRI-MUS™ (prostate risk Identification using micro-ultrasound)[ii] – has been developed and validated to distinguish benign prostate tissue from tissue that has a high probability of being cancerous based on its appearance in a micro-ultrasound image.

The paper, “High-frequency quantitative ultrasound for prostate-cancer imaging using a novel micro-ultrasound scanner, which is being presented at the 174th Acoustical Society of America, shows promising results from a collaborative research project undertaken by Riverside Research, a leading biomedical research institution in New York, NY, and Exact Imaging.  The paper describes an approach that successfully applies a combination of (1) sophisticated ultrasound signal processing methods known as quantitative ultrasound and (2) machine-learning and artificial intelligence to analysis of fine-resolution data acquired with the novel micro-ultrasound imaging platform to automate detection of cancerous tissue in the prostate.  Results of the study were very encouraging and showed a promising ability of the methods to distinguish cancerous from non-cancerous prostate tissue.

A database of 12,000 fine-resolution, micro-ultrasound images and correlated biopsy histology has been developed.  The new algorithm for automated detection continues to evolve and is applied to this growing data set.

Future clinical application of the algorithms implemented in the ExactVu would involve scanning a patient with indications of prostate cancer (e.g., as a result of a transrectal palpation or a high level of prostate-specific antigen in the blood) to identify regions of the gland that are sufficiently suspicious for cancer to warrant a biopsy.  As the scan proceeds, the algorithm continuously analyzes the ultrasound signals and automatically indicates to the examining urologist any regions that have a significant risk of being cancerous.  The urologist evaluates the indicated region and makes a clinical judgement on whether the region in fact warrants a biopsy.

The results of this study show an encouraging ability of ultrasound-signal processing and the machine-learning algorithm together with the novel micro-ultrasound instrumentation to depict regions of the prostate that are cancerous with high reliability.  The study demonstrates a promising potential of the algorithms and micro-ultrasound to improve targeting of biopsies, to increase cancer-detection rates, to avoid unnecessary biopsies and associated risks, to support focal therapy more effectively, and consequently to achieve better patient outcomes.

[i] American Cancer Association: https://cancerstatisticscenter.cancer.org/?_ga=2.177940773.1025752599.1511161127-1043893878.1511161127#!/

[ii] Ghai S, et al: Assessing Cancer Risk on Novel 29 MHz Micro-Ultrasound Images of the Prostate: Creation of the Micro-Ultrasound Protocol for Prostate Risk Identification. J. Urol. 2016; 196: 562–569.

2aBAa7 – Stimulating the brain with ultrasound: treatment planning

Joseph Blackmore – joseph.blackmore@wadham.ox.ac.uk
Robin Cleveland – robin.cleveland@eng.ox.ac.uk
Institute of Biomedical Engineering, University of Oxford, Roosevelt Drive, Oxford, OX3 7DQ, United Kingdom

Michele Veldsman – michele.veldsman@ndcn.ox.ac.uk
Christopher Butler – chris.butler@ndcn.ox.ac.uk
Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, United Kingdom

Popular version of paper 2aBAa7
Presented Monday morning, June 26, 2017
173rd ASA Meeting, Boston

Many disorders of the brain, such as OCD and essential tremor, can be treated by stimulating or disrupting specific locations in the brain. This can be done by placing an electrode directly at the site needing disruption with a procedure known as deep brain stimulation, but it is an invasive procedure that involves drilling a hole in the skull and inserting a wire through the brain tissue.

Non-invasive alternatives do exist in which electrodes or magnets are placed on the scalp, avoiding the need for surgery. However, these methods can only be used to treat brain regions quite close to the skull and have limited spatial specificity.

Recently, low-intensity focused ultrasound has also been shown to stimulate localized regions of the brain, creating, for example, the sensation of seeing stars in your eyes (known as phosphenes) [1], when targeted to a region of the brain associated with vision. However, steering and focusing an ultrasound beam to the correct location within the brain remains a challenge due to the presence of the skull.

Skull bone, with its varying thickness, curvature, and structure, strongly distorts and attenuates ultrasound waves and can shift the focal point away from the intended target. Consequently, in current human trials, as many of 50 percent of ultrasound stimulation attempts did not elicit a response [1,2].

One solution to more robust focusing is to use ultrasound transducers with hundreds, or even thousands of elements, each of which is individually tuned to account for variations in skull properties so that all waves focus to the intended target location with the brain. However, this equipment is very complex and expensive which, in this early stage of research into ultrasound-induced neuromodulation, has limited progress.

Here, we performed a numerical study to assess whether single-element transducers — which are relatively inexpensive — could be used in combination with numerical modelling to achieve sufficient targeting in the brain. This would provide a solution that can be used as a research tool to further understand the mechanisms behind ultrasound-induced neuromodulation.

Figure 1 – Propagation of sound waves from the brain target out to a spherical receiver outside the skull. The received signals are then optimized to determine the best position for an ultrasound source to deliver sound back through the skull. The locations for different optimization methods are depicted by the colored dots.

The method works by importing a three-dimensional CT image into a computer and placing a virtual acoustic source at the desired target location. A super-computer then calculates how the sound travels from the target, through brain tissue and the skull bone, onto a sphere outside the head, depicted in Figure 1.

From the predicted signals, it is possible to determine the best position of an ultrasound source which can send sound back through the skull to the target location. We employed different strategies for choosing the source location (the dots in Figure 1), and for the optimal strategy predict that a single element transducer can localize sound to a region about 36 millimeters long and 4 millimeters in diameter at depths up to 45 millimeters into brain tissue, which is depicted in Figure 2.

brain

Figure 2 – Focusing the sound waves to a region deep within the brain from a curved single-element transducer. The red cross indicates the intended target. The blue contours represent the acoustic intensity relative to the intensity at the target. -3dB corresponds to 50% of the intensity at the target, -6dB is 25% and -12dB is 12.5%.

[1] Lee, Wonhye, et al. “Transcranial focused ultrasound stimulation of human primary visual cortex.” Scientific Reports 6 (2016).
[2] Lee, Wonhye, et al. “Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex.” Scientific Reports 5 (2015): 8743.