Strain elastography with ultrasound computer tomography: a simulation study based on biomechanical models

Ultrasound computer tomography (USCT) is a promising modality for breast cancer diagnosis which images the reflectivity, sound speed and attenuation of tissue. Elastic properties of breast tissue, however, cannot directly be imaged although they have shown to be applicable as a discriminator between different tissue types. In this work we propose a novel approach combining USCT with the principles of strain elastography. Socalled USCT-SE makes use of imaging the breast in two deformation states, estimating the deformation field based on reconstructed images and thereby allows localizing and distinguishing soft and hard masses. We use a biomechanical model of the breast to realistically simulate both deformation states of the breast. The analysis of the strain is performed by estimating the deformation field from the deformed to the undeformed image by a non-rigid registration. In two experiments the non-rigid registration is applied to ground truth sound speed images and simulated SAFT images. Results of the strain analysis show that for both cases soft and hard lesions can be distinguished visually in the elastograms. This paper provides a first approach to obtain mechanical information based on external mechanical excitation of breast tissue in a USCT system

Comparison of registration strategies for USCT–MRI image fusion: preliminary results

Comparing Ultrasound Computer Tomography (USCT) to the well-known Magnetic Resonance Imaging (MRI) is an essential step in evaluating the clinical value of USCT. Yet the different conditions of the breast either embedded in water (USCT) or in air (MRI) prevent direct comparison. In this work we compare two strategies for image registration based on biomechanical modeling to automatically establish spatial correspondence: a) by applying buoyancy to the MRI, or b) by removing buoyancy from the USCT. The registration was applied to 9 datasets from 8 patients. Both registration strategies revealed similar registration accuracies (MRI to USCT: mean = 5.6 mm, median = 5.6 mm, USCT to MRI: mean = 6.6 mm, median = 5.7 mm). Image registration of USCT and MRI allows to delineate corresponding tissue structures in both modalities in the same or nearby slices. Our preliminary results indicate that both simulation strategies seem to perform similarly. Yet the newly developed deformation of the USCT volume is less computationally demanding: As the breast is subjected to buoyancy it can thereby serve as the unloaded state while for the contrary strategy we have to solve an inverse problem

Improved temperature measurement and modeling for 3D USCT II

Medical visualization plays a key role in the early diagnosis and detection of symptoms related to breast cancer. However, currently doctors must struggle to extract accurate and relevant information from the 2D models on which the medical field still relies. The problem is that 2D models lack the spatial definition necessary to extract all of the information a doctor might want. In order to address this gap, we are developing a machine capable of performing ultrasound computer tomography and reconstructing 3D images of the breasts - the KIT 3D USCT II. In order to accurately reconstruct the 3D image using ultrasound, we must first have an accurate temperature model. This is because the speed of sound varies significantly based on the temperature of the medium (in our case, water). We address this issue in three steps: so-called super-sampling, calibration, and modeling. Using these three steps, we were able to improve the accuracy of the hardware from ±1°C to just under 0.1°C

Method to Extract Frequency Dependent Material Attenuation for Improved Transducer Models

The time response of the ultrasound transducers used in our 3D ultrasound tomography device shows a slight reverberation. This may causes artifacts in the reconstructed images. Loss properties of materials used in the array fabrication have a big impact on their complex vibration behavior. Unfortunately, material parameters for accurate modeling are often not available in literature. Here, we present a method to derive loss properties of polymers and composites and how to include them in a finite element analysis (FEA). The method has three steps: First, an experiment to measure the frequency and thickness dependent sound attenuation. Second, a brute-force fit to a frequency-power law expression to obtain an analytic formulation. Third, a conversion of the sound attenuation to an equivalent structural loss factor. The last step is necessary as acoustic attenuation can not directly be implemented in structural mechanics FEA. We applied the method to derive loss properties of the filler and backing material which we use for our ultrasound transducer arrays. When including the loss factor in the simulation a reverberation is predicted, which matches the measurement well. Hence, considering loss properties allows more accurate modeling of complex vibration behavior. This aids in optimizing our ultrasound transducer array design towards better 3D ultrasound imaging

Model-Guided Manufacturing of Transducer Arrays Based on Single-Fibre Piezocomposites

For breast cancer imaging, ultrasound computer tomography (USCT) is an emerging technology. To improve the image quality of our full 3-D system, a new transducer array system (TAS) design was previously proposed. This work presents a manufacturing approach which realises this new design. To monitor the transducer quality during production, the electro-mechanical impedance (EMI) was measured initially and after each assembly step. To evaluate the measured responses, an extended Krimholtz–Leedom–Matthaei (KLM) transducer model was used. The model aids in interpreting the measured responses and presents a useful tool for evaluating parasitic electric effects and attenuation at resonance. For quality control, the phase angle at thickness resonance φt was found to be the most specific EMI property. It can be used to verify the functionality of the piezocomposites and allows reliable detection of faults in the acoustic backing. Evaluating the final response of 68 transducers showed 5% variance of the series resonance frequency. This indicates good consistency of derived ultrasound performance parameters

Object Classification and Localization with an Airborne Ultrasound Imaging System

An airborne ultrasound imaging system (ABUS) was developed at KIT for reflection tomography. The prototype system consists of sixteen ultrasonic transducers surrounding a region of interest (ROI) of defined shape with a diameter of 50 cm. The transducers have a center frequency of 200 kHz and a bandwidth of 20 kHz. The prototype aims to demonstrate possible industrial applications for object classification and localization with airborne ultrasound. This paper is a detailed version of the previous publication in IEEE Ultrasonics Symposium (IUS) 2017 [1]

Towards Subject-Specific Therapy Planning for Non-Invasive Blood Brain Barrier Opening in Mice by Focused Ultrasound

Focused ultrasound (FUS) is a promising method to open the blood brain barrier (BBB) for treatment of neurodegenerative diseases. Accurate targeting is essential for a successful BBB opening (BBBo). We aim to develop a robust therapy planning for BBBo in mice, which is challenging due to the size of the brain and the influence of the skull on the ultrasound pressure distribution. For enabling mouse individual therapy planning, a simulation tool is proposed, developed and validated. We used the k-Wave toolbox to enable 3D acoustic simulations of the commercial FUS system from Image Guided Therapy (IGT). Micro-CT scans were used to model the geometry of skulls. Simulations using a mouse skull showed an attenuation of approx. 20–24% depending on the position of penetration, which was validated by hydrophone measurements in the same range. Based on these validations we planned BBBo in m ice by placing the transducer at different positions over the mouse brain and varying the excitation amplitude. With different transducer positions, the peak pressure in the brain varied between 0.54 MPa and 0.62 MPa at 11% output level, which is expected to enable safe BBBo. Subsequently, in vivo experiments were conducted using the aforementioned simulation parameters. BBBo was confirmed by contrast enhanced T1 weighted magnetic resonance images immediately after sonication