1aBAb – Detecting liver cracks using ultrasonic shear wave imaging

Detecting liver cracks using ultrasonic shear wave imaging
Jingfei Liu – jingfei.liu@ttu.edu
Texas Tech University
2500 Broadway
Lubbock, TX 79409

Popular version of paper ‘1aBAb – An ex vivo investigation of ultrasonic shear wave imaging for detecting liver cracks
Presented Monday morning, November 29, 2021
181st ASA Meeting

Liver crack is a type of liver trauma, in which a capsular tear of different geometries occurs due to external impacts, and it is a common physical damage in traffic accidents, combating sports, and other accidents. Since liver crack is an important source of morbidity and mortality in emergency medicine, a timely and accurate detection of the crack location and geometry is highly demanded. In current emergency care, ultrasonography, although has a low accuracy, is mostly used for initial examination of liver trauma due to its immediate availability, high mobility, and nonionizing nature. After the initial screening using ultrasonography, a more accurate diagnosis is normally achieved by X-ray computer tomography (CT). Although CT can provide more details of the liver damage, it is not easy to access because patients must be transport to CT facilities, and it is even risky for the patients like newborns whose condition is unstable. To develop a diagnostic technique which both has easy access and can provide accurate diagnosis, ultrasonic shear wave imaging was proposed in this study as a better option.
In this technique, shear wave, a different type of ultrasonic wave from the ultrasonic wave (longitudinal wave) used in typical ultrasonography, is first generated at the patients’ liver, and then tracked during its propagation. Because shear wave cannot propagate in blood, there will be strong reflection or diffraction at the crack locations, which ultrasonography cannot identify (because longitudinal wave can go through blood and no strong reflection is available). Thus, the location and severeness of targeted liver crack can possibly be detected.
In this study, the feasibility and effectiveness of this method was investigated in an ex vivo scenario. A porcine liver with cracks of different geometries was tested. Shear waves were generated using acoustic radiation force impulse and recorded using ultrafast ultrasound imaging. To find the best way to display the cracks, different methods of signal processing based on time-of-flight, shear wave modulus, and accumulated shear wave path were applied to the shear wave displacement extracted. The results show that shear wave imaging is a more sensitive method than the conventional ultrasonography in detecting liver cracks.

1pBAb5 – Predicting Spontaneous Preterm Birth Risk is Improved when Quantitative Ultrasound Data are Included with Prior Clinical Data

Predicting Spontaneous Preterm Birth Risk is Improved when Quantitative Ultrasound Data are Included with Prior Clinical Data
Barbara L. McFarlin, bmcfar1@uic.edu
Yuxuan Liu
Shashi Roshan
Aiguo Han
Douglas G. Simpson
William D. O’Brien, Jr.

Popular version of paper ‘1pBAb5 – Predicting spontaneous preterm birth risk is improved when quantitative ultrasound data are included with prior clinical data
Presented Monday afternoon, November 29, 2021
181st ASA Meeting

Preterm birth (PTB) is defined as birth before 37 completed weeks’ gestation. Annually in the U.S., more than 400,000 infants are born preterm, and over 1 billion globally. Consequences of PTB for survivors are severe, can be life-long and cost society $30 billion annually, a cost that far exceeds that of any major adult diagnosis. Predicting women at risk for sPTB has been medically challenging due to 1) lack of signs and symptoms of preterm labor until intervention is too late, and 2) lack of screening tools to signal sPTB risk early enough when an intervention would likely be effective. Spontaneous preterm labor is a syndrome associated with multiple etiologies of which only a portion may be associated with cervical insufficiency; however, regardless of the reason of PTB, the cervix (the opening to the womb) must get ready for birth to allow passage of the baby.
Our Novel quantitative ultrasound (QUS) technology has been developed by our multidisciplinary investigative team (ultrasound, engineering and nurse midwifery) and shows promise of becoming a widely available and a useful method for early detection of spontaneous preterm birth. Our preliminary results of 275 pregnant women who received two ultrasounds during pregnancy, determined that QUS improved prediction of preterm birth and was an added feature to current clinical and patient risk factors. QUS technology is a feature that can readily be added to current clinical ultrasound systems, thereby reducing the time from basic science innovation translation to improve clinical care of women.
This research was supported National Institutes of Health grant R01 HD089935

1aBAb12 – Novel use of a lung ultrasound sensor for monitoring lung conditions

Novel use of a lung ultrasound sensor for monitoring lung conditions

Tanya Khokhlova – tdk7@uw.edu
Adam Maxwell – amax38@uw.edu
Gilles Thomas – gthom@uw.edu
Jeff Thiel – jt43@uw.edu
Alex Peek – apeek@uw.edu
Bryan Cunitz – bwc@uw.edu
Michael Bailey – mbailey@uw.edu
Kyle Steinbock – kyles96@uw.edu
Layla Anderson – anderla@uw.edu
Ross Kessler – kesslerr@uw.edu
Adeyinka Adedipe- adeyinka@uw.edu
University of Washington
Seattle, WA, 98195

Popular version of paper ‘1aBAb12 – Novel use of a lung ultrasound sensor for detection of lung interstitial syndrome

Presented Monday morning, November 29, 2021

181^st ASA Meeting

The need to continuously evaluate the amount of fluid in the lung is essential in patients suffering from a number of conditions, including viral pneumonia (including COVID-19) and heart failure, and patients on dialysis. Chest x-ray and CT are typically used for this purpose, but can not be done continuously due to the radiation dose, and have logistical limitations in some cases, for example when transporting unstable patients or patients with COVID-19 due to the risk of contagion. Lung ultrasound (LUS) is non-ionizing and safe, and has recently emerged as a useful triage and monitoring tool for quantification of lung water. Because lung is air-filled, it is reflective for ultrasound, and in LUS exams it is image artifacts that are being evaluated, rather than true lung images. The artifacts termed A-lines are periodic bright horizontal lines parallel to the lung surface representing multiple reflections of ultrasound pulse from the lung and indicating a normal aeration pattern. The artifacts termed B-lines are comet-like bright vertical regions originating at the lung surface and extending down. The number and distribution of B-lines are known to correlate with presence of fluid in the lung and the condition severity. However, visualization and quantification of B-lines requires training and is machine and operator dependent, whereas in select clinical scenarios continuous, automated hands-free monitoring of lung function is preferred, e.g. COVID19 infection.
In this study we were aiming to identify the detected ultrasound signal features that are associated with B-lines and to develop a miniature wearable non-imaging lung ultrasound sensor (LUSS). Individual adhesive LUSS elements could be attached to patients in specific anatomic locations similarly to EKG leads, and ultrasound signals would be collected and processed with automated algorithms continuously or on demand. First, we used an open platform ultrasound imaging system to perform standard 10-zone LUS in ten patients with confirmed pulmonary edema, and in five healthy volunteers. The ultrasound signal data corresponding to each image were collected for subsequent off-line Doppler, decorrelation and spectral analyses. The metrics we found to be associated with the B-line thickness and number were peaks of Doppler power at the pleural line and the ultrasound signal amplitude corresponding to a large depth.

Left: examples of lung ultrasound images containing A-lines and B-lines and the corresponding signals detected by the ultrasound imaging probe. Right: conceptual diagram of the use of LUSS for monitoring of lung condition and a prototype LUSS element. Adhesive LUSS elements are applied in 10 anatomic locations and automated signal processing software displays lung fluid score for each element on a 4-point scale: none (green), mild (yellow), moderate (orange) or severe (red).

Next, we built miniature LUSS elements powered by custom-built multiplexed transmit-receive circuit, and tested them in a benchtop lung model – polyurethane sponge containing variable volumes of water – side by side with LUS imaging probe previously used in patients. Wetting of the sponge produced B-lines on the ultrasound images, and the associated ultrasound signals were similar to those measured by LUSS elements. We hope to proceed with testing LUSS in human patients in the nearest future. This work was supported by NIH R01EB023910.

1aBAb9 – Extracting Human Skull Properties by Using Ultrasound and Artificial Intelligence

Extracting Human Skull Properties by Using Ultrasound and Artificial Intelligence

Churan He1– churanh2@illinois.edu
Yun Jing2 – jing.yun@psu.edu
Aiguo Han1 – han51@illinois.edu

1. Department of Electrical and Computer Engineering
The University of Illinois at Urbana Champaign
306 North Wright Street
Urbana, IL 61801

2. Graduate Program in Acoustics
Pennsylvania State University
201 Applied Science Building
University Park, PA 16802

Popular version of paper ‘1aBAb9 – Human skull profile and speed of sound estimation using pulse-echo ultrasound signals with deep learning

Presented Monday morning, November 29, 2021

181st Meeting of the Acoustical Society of America in Seattle, Washington.

Ultrasound is a tremendously valuable tool for medical imaging and therapy of the human body. When it comes to applications in the brain, however, the presence of the skull poses severe challenges to both imaging and therapy. The skulls of human adults induce significant distortions (also called phase aberrations) to the acoustic waves. The aberrations result in blurred brain images that are extremely challenging to interpret. The skull also distorts and shifts the acoustic focus, causing challenges in therapy of the brain (such as treating essential tremors and brain tumors) using high-intensity focused ultrasound.

Prior research has shown that phase aberrations can be most accurately corrected if the skull profile (i.e., thickness distribution) and speed of sound are known a priori. Various methods have been proposed to estimate the skull profile and speed of sound. The gold-standard method used in treatment planning derives the skull properties from computed-tomography (CT) images of the skull. The CT-based method, however, entails ionizing radiation, potentially causing harm to the patients.

We propose an ultrasound-based method to extract the skull properties. This method is safer because ultrasound does not cause ionizing radiation. We developed an artificial intelligence (AI) algorithm (specifically, a deep learning algorithm) that predicted the skull thickness and sound speed by using ultrasound echo signals reflected from the skull.

We tested the feasibility of our method through a simulation study (Figure 1). We performed acoustic simulations using realistic skull models built from CT scans of five ex vivo human skulls (see animation). The simulations generated a large number (=7891) of ultrasound signals from skull segments for which the thickness and sound speed were known. We used 80% of the data to train our AI algorithm and 20% for testing. We developed and tested two algorithm versions: One version took the original echo signal as the input and the other used a transformed signal (i.e., Fourier transform that displays the signal’s frequency spectrum).

Both versions of our AI algorithm achieved accurate results, while the version using the transformed signals appeared to be more accurate. Using the original signal as the input, we obtained a mean absolute error of 0.3 mm for skull thickness prediction and 31 m/s for sound speed prediction. When transformed signals were used, the error in thickness prediction was reduced to 0.2 mm (= 3% of the average skull thickness [6.3 mm]), and the error in sound speed prediction was reduced to 25 m/s (= 1% of the average sound speed [2340 m/s]). In the case of transformed signals, the correlation between predicted values and the ground truth was 0.98 for thickness and 0.81 for speed of sound (Figure 2), where a correlation value of 1 represents perfect correlation.

Collectively, our preliminary results demonstrate that the developed AI algorithm can accurately estimate skull thickness and speed of sound, providing a potentially powerful tool to correct skull phase aberration for transcranial ultrasound brain imaging and therapy.

[Animation: 3-dimensional density map of one of the skulls used in the study]

Figure 1. Schematic diagram of the simulation study

 

Figure 2. a) Scatter plot of extracted speed of sound versus ground truth; b) scatter plot of extracted thickness versus ground truth.

 

1aBAb2 – Transcranial Radiation of Guided Waves for Brain Ultrasound – Eetu Kohtanen

Transcranial Radiation of Guided Waves for Brain Ultrasound

Eetu Kohtanen – ekohtanen3@gatech.edu
Alper Erturk – alper.erturk@me.gatech.edu
Georgia Institute of Technology
771 Ferst Drive NW
Atlanta, GA 30332

Matteo Mazzotti – matteo.mazzotti@colorado.edu
Massimo Ruzzene – massimo.ruzzene@colorado.edu
University of Colorado Boulder
1111 Engineering Dr
Boulder, CO 80309

 

Popular version of paper ‘1aBAb2’

Presented Tuesday morning, June 8, 2021

180th ASA Meeting, Acoustics in Focus

 

Ultrasound imaging is a safe and familiar tool for producing medical images of soft tissues. Ultrasound can also be used to ablate tumors by focusing a large amount of acoustic energy (“focused ultrasound”) capable of destroying tumors.

The use of ultrasound in the imaging and treatment of soft tissues is well established, but ultrasound treatment for the brain poses important scientific challenges. Conventional medical ultrasound uses bulk acoustic waves that travel directly through the skull into the brain. While the center of the brain is relatively accessible in this way to treat disorders such as essential tremor, the need for transmitting waves to the brain periphery or the skull-brain interface efficiently (with reduced heating of the skull) motivates research on alternative methods.

The skull is an obstacle for bulk waves, but for guided waves it presents opportunity. Unlike bulk waves, guided (Lamb) waves propagate along structures (such as the skull), rather than through them—as the name suggests, their direction of travel is guided by structural boundaries.  If these guided waves are fast enough, they “leak” into the brain efficiently. However, there are challenges due to the complex skull geometry and bone porosity. Our research seeks a fundamental understanding of how guided waves in the skull radiate energy into the brain to pave the way for making guided waves a viable medical ultrasound tool to expand the treatment envelope.

To study the radiation of guided waves from skull bone, experiments were conducted with submersed skull segments. A transducer emits pressure waves that hit the outer side of the bone, and a hydrophone measures the pressure field on the inner side. In the following animation, the dominant guided wave radiation angle can be seen as 65 degrees. With further data processing, the experimental radiation angles (contours) are obtained with frequency. Additionally, a numerical model that considers the separate bone layers and the fluid loading is constructed to predict the radiation angles of a set of different guided wave types (solid branches). The experimental contours are always accompanied by corresponding numerical prediction, validating the model.

Experimental pressure field on the inner side of the skull bone segment and the corresponding radiation angles

With these results, we have a better understanding of guided wave radiation from the skull bone. The authors hope that these fundamental findings will eventually lead to application of guided waves for focused ultrasound in the brain.

3aBA9 – Ultrasound mediated thermal stress augments mass and drug transport in brain tumors – Costas Arvanitis

Costas Arvanitis
Georgia Institute of Technology
costas.arvanitis@gatech.edu

Popular version of paper 3aBA9 The role of U.S. thermal stress in modulating the vascular transport dynamics in the brain tumors
Presented Thursday morning, June 10, 2021
180th ASA Meeting, Acoustics in Focus

Local hyperthermia and stimuli-responsive delivery systems, such as thermosensitive liposomes, represent promising strategies to locally enhance drug delivery in brain tumors and improve treatment outcomes. However, a critical obstacle towards exploring their therapeutic potential in brain tumors is the limited ability to attain reliably and reproducibly the desired temperature in the brain.
Dr Costas Arvanitis at the Georgia Institute of Technology and Emory University, and his graduate student, Chulyong Kim, hypothesized that trans-skull focused ultrasound combined with closed-loop controlled methods can achieve this goal.

Figure 1. Graphical representation of  US mediated  thermal stress drug release and delivery from  thermosensitive drugs in brain tumors.

Almost!

Attaining controlled thermal stress through the skull is not a trivial problem, especially in mice where every new treatment is tested for safety and efficacy. For example, although at low frequencies (< 1 MHz) most of the energy is transmitted through the skull, the resulting large focal region overlaps substantially with the skull, which due to its higher absorption leads to disproportionally high skull heating. On the other hand, at higher frequencies (> 2 MHz) skull reflections and aberrations become significant, and thus limit our ability to focus the beam in the brain through the skull. Using a physically accurate mathematical modeling, the investigations revealed that an optimal frequency (≈ 1.7 MHz) does exist for applying localized thermal stress in mice brain without overheating the skull.

Based on this knowledge, the investigators built a closed-loop trans-skull magnetic resonance imaging guided focused ultrasound (MRgFUS) prototype and demonstrated that it can attain reproducible experimentation and heating of the entire tumor at the desired temperature. Next, using semi-quantitative imaging, they revealed that localized thermal stress (41.5 oC for 10 minutes) in brain tumors in rodents promotes acute changes in the cerebrovascular transport dynamics in the brain tumor microenvironment. These changes can be important, as they can increase the amount of drug that reaches the tumor.

Subsequently, by combining the abilities of this system with those of thermosensitive liposomes loaded with doxorubicin, the most common chemotherapeutic agent, they were able to achieve a marked improvement in doxorubicin accumulation and uptake in preclinical glioma tumor models. Crucially, survival studies indicated that the proposed two-pronged strategy could lead to substantial improvement in the survival.

Overall, this work, in addition to refining our understanding on the role of thermal stress in modulating the transport dynamics in the brain tumor microenvironment, allowed to establish a new paradigm for noninvasive targeted drug delivery in glioblastomas. It may, thus, create new opportunities towards attaining clinically effective drug delivery in patients with aggressive brain tumors, such as glioblastoma, that currently have limited treatment options.

Acknowledgments: This study was supported by the National Institutes of Health grants R00 EB016971.

Links: https://arvanitis.gatech.edu/