Ultrasound waveform tomography with the total-variation regularization could improve reconstructions of tumor margins,
but the reconstructions usually contain unwanted blocky artifacts. We develop a new ultrasound waveform tomography
method with a second-order total-generalized-variation regularization scheme to improve tomographic reconstructions
of breast tumors and remove blocky artifacts in reconstruction results. We validate our new method using numerical
phantom data and real phantom data acquired using our synthetic-aperture breast ultrasound tomography system with
two parallel transducer arrays. Compared to reconstructions of ultrasound waveform tomography with modified total-variation
regularization, our new ultrasound waveform tomography yields accurate sound-speed reconstruction results
with significantly reduced artifacts.
Proc. SPIE. 9783, Medical Imaging 2016: Physics of Medical Imaging
KEYWORDS: Breast, Breast cancer, Signal attenuation, Ultrasonography, Tomography, Data acquisition, Transducers, Mammography, Ultrasound tomography, In vivo imaging, Algorithm development, Prototyping, Design for manufacturability
Breast ultrasound tomography is an emerging imaging modality to reconstruct the sound speed, density, and ultrasound attenuation of the breast in addition to ultrasound reflection/beamforming images for breast cancer detection and characterization. We recently designed and manufactured a new synthetic-aperture breast ultrasound tomography prototype with two parallel transducer arrays consisting of a total of 768 transducer elements. The transducer arrays are translated vertically to scan the breast in a warm water tank from the chest wall/axillary region to the nipple region to acquire ultrasound transmission and reflection data for whole-breast ultrasound tomography imaging. The distance of these two ultrasound transducer arrays is adjustable for scanning breasts with different sizes. We use our breast ultrasound tomography prototype to acquire phantom and in vivo patient ultrasound data to study its feasibility for breast imaging. We apply our recently developed ultrasound imaging and tomography algorithms to ultrasound data acquired using our breast ultrasound tomography system. Our in vivo patient imaging results demonstrate that our breast ultrasound tomography can detect breast lesions shown on clinical ultrasound and mammographic images.
Ultrasound tomography has great potential to provide quantitative estimations of physical properties of breast tumors for accurate characterization of breast cancer. We design and manufacture a new synthetic-aperture breast ultrasound tomography system with two parallel transducer arrays. The distance of these two transducer arrays is adjustable for scanning breasts with different sizes. The ultrasound transducer arrays are translated vertically to scan the entire breast slice by slice and acquires ultrasound transmission and reflection data for whole-breast ultrasound imaging and tomographic reconstructions. We use the system to acquire patient data at the University of New Mexico Hospital for clinical studies. We present some preliminary imaging results of <i>in vivo </i>patient ultrasound data. Our preliminary clinical imaging results show promising of our breast ultrasound tomography system with two parallel transducer arrays for breast cancer imaging and characterization.
The sound-speed distribution of the breast can be used for characterizing breast tumors, because they typically have a higher sound speed than normal breast tissue. This is understood to be the result of remodeling of the extracellular matrix surrounding tumors. Breast sound-speed distribution can be reconstructed using ultrasound bent-ray tomography (USRT). We have recently demonstrated that USRT, using arrival times of both transmission and reflection data, significantly improves image quality. To further improve the robustness of tomographic reconstructions, we develop a USRT method using a modified total-variation (MTV) regularization scheme. Regularization is often used in solving inverse problems by introducing restrictions such as for smoothness. Tikhonov regularization is a widely used regularization scheme that tends to smooth tomographic images, but oversmoothing can obscure critical diagnostic detail such as tumor margins. Total-variation (TV) regularization is another common regularization scheme that preserves tumor margins, but at the cost of increased image noise. Our new USRT with MTV regularization is a Tikhonov-TV hybrid, reducing image noise while preserving margins. We apply our new method to ultrasound transmission data from numerical phantoms, and compare the results with those obtained using Tikhonov regularization.
Regularization is often needed in breast ultrasound waveform tomography to improve tomographic reconstructions. A global regularization parameter may lead to either over-regularization or under-regularization in different regions in the imaging domain. We develop a new ultrasound waveform tomography method with spatially-variant regularization. Our new method employs different regularization parameters in different regions of the breast so that each regularization parameter is optimal for the local region. Our numerical examples demonstrate the improvement of ultrasound waveform tomography using the spatially-variant modified total-variation regularization for sound-speed reconstructions of large and small breast tumors, particularly when their sizes are significantly different from one another.
Ultrasound transmission tomography usually generates low-resolution breast images. We improve sound-speed reconstructions using ultrasound waveform tomography with both transmission and reflection data. We validate the improvement using computer-generated synthetic-aperture ultrasound transmission and reflection data for numerical breast phantoms. Our tomography results demonstrate that using both transmission and reflection data in ultrasound waveform tomography greatly enhances the resolution and accuracy of tomographic reconstructions compared to ultrasound waveform tomography using either transmission data or reflection data alone. To verify the capability of our novel ultrasound waveform tomography, we design and manufacture a new synthetic-aperture breast ultrasound tomography system with two parallel transducer arrays for clinical studies. The distance of the two transducer arrays is adjustable for accommodating different sizes of the breast. The parallel transducer arrays also allow us to easily scan the axillary region to evaluate the status of axillary lymph nodes and detect breast cancer in the axillary region. However, synthetic-aperture ultrasound reflection data acquired by firing each transducer element sequentially are usually much weaker than transmission data, and have much lower signal-to-noise ratios than the latter. We develop a numerical virtual-point-source method to enhance ultrasound reflection data using synthetic-aperture ultrasound data acquired by firing each transducer element sequentially. Synthetic-aperture ultrasound reflection data for a breast phantom obtained using our numerical virtual-point-source method reveals many coherent ultrasound reflection waveforms that are weak or invisible in the original synthetic-aperture ultrasound data. Ultrasound waveform tomography using both transmission and reflection data together with numerical virtual-point-source method has great potential to produce high-resolution tomographic reconstructions in clinical studies of breast ultrasound tomography.
Early detection of breast cancer is the key to reducing the cancer mortality rate. With increasing computational power, waveform inversion becomes feasible for high-resolution ultrasound tomography. Because of the limited measurement geometry, ultrasound waveform tomography is usually ill-posed, which requires certain computational methodologies to stabilize waveform inversion. We develop a new ultrasound waveform tomography method using a modified total-variation regularization for detecting and characterizing small breast tumors. To solve the minimization problem, we use an alternating-minimization algorithm in which the original optimization is equivalently decomposed
into two simple subproblems. We use numerical breast-phantom data to demonstrate the improved capability of our new tomography method for accurately reconstructs the sound-speed values and shapes of small tumors.
Ultrasound could be an attractive imaging modality for detecting breast microcalcifications, but it requires significant
improvement in image resolution and quality. Recently, we have used tissue-equivalent phantoms to demonstrate that
synthetic-aperture ultrasound has the potential to detect small targets. In this paper, we study the in vivo imaging capability
of a real-time synthetic-aperture ultrasound system for detecting breast microcalcifications. This LANL's (Los Alamos
National Laboratory's) custom built synthetic-aperture ultrasound system has a maximum frame rate of 25 Hz, and is one
of the very first medical devices capable of acquiring synthetic-aperture ultrasound data and forming ultrasound images in
real time, making the synthetic-aperture ultrasound feasible for clinical applications. We recruit patients whose screening
mammograms show breast microcalcifications, and use LANL's synthetic-aperture ultrasound system to scan the regions
with microcalcifications. Our preliminary in vivo patient imaging results demonstrate that synthetic-aperture ultrasound is
a promising imaging modality for detecting breast microcalcifications.
Ultrasound waveform tomography takes wave propagation effects into account during image reconstruction,
and has the potential to produce accurate estimates of the sound speeds of small breast tumors.
However, waveform tomography is computationally time-consuming for large datasets acquired
using a synthetic-aperture ultrasound tomography system that consists of hundreds to thousands of
transducer elements. We introduce a source encoding approach to ultrasound waveform tomography
to significantly improve the computational efficiency. The method simultaneously simulates ultrasound
waveforms emitted from multiple transducer elements. To distinguish the effect of different
sources, we apply a random phase to each source. The random phase helps eliminate the unwanted
cross interferences produced by different sources. This approach greatly reduces the computational
time of ultrasound waveform tomography to one tenth of that for the original waveform tomography,
and makes it feasible for ultrasound waveform tomography in clinical applications.
Waveform tomography has the potential to quantitatively reconstruct the sound speed values of breast
tumors. It is difficult to obtain quantitative values of the sound speed of breast tumors when their
sizes are in the order of, or smaller than, the ultrasound wavelength. Because of the ill-posedness
of the full-waveform inversion, regularization techniques are usually used to improve reconstruction.
We develop an ultrasound waveform tomography method with the total-variation regularization to
improve sound-speed reconstructions of small breast tumors. Our numerical examples demonstrate
that our ultrasound waveform tomography with the total-variation regularization is a promising tool
for quantitative estimation of the sound speed of small breast tumors.