Detection of breast cancer with ultrasound tomography: First results with the Computed Ultrasound Risk Evaluation (CURE) prototype

Duric, Nebojsa; Littrup, Peter J.; Poulo, Lou; Babkin, Alex; Pevzner, Roman; Holsapple, Earle; Rama, Olsi; Glide, C

doi:10.1118/1.2432161

Cited by 336 publications

(281 citation statements)

References 24 publications

(24 reference statements)

Supporting

Mentioning

279

Contrasting

Unclassified

Order By: Relevance

“…(a) Schematic illustration of a ring transducer array (from [5]). (b) Interaction of an ultrasound pulse with a target leads to a scattered ultrasound field (from [17]).…”

Section: Discussionmentioning

confidence: 99%

“…CURE is capable of recording all ultrasound wavefields including reflected, transmitted, and diffracted ultrasonic signals from the breast tissue. The engineering prototype of CURE is described in [17], and the current clinical prototype is described in [5]. Fig.…”

Section: Ultrasound Breast Data Acquired Using the Cure Devicementioning

confidence: 99%

“…Compute the Akaike weights for each data point within the time window: (4) 4. Obtain the TOF value using the weighted average: (5) where t i (i = 1; . .…”

Section: Using a Weighted Average Model To Determinementioning

confidence: 99%

“…A clinical prototype of ultrasound breast-imaging system with a ring array, termed the computed ultrasound risk evaluation (CURE), has been developed at the Karmanos Cancer Institute, Wayne State University in Detroit, MI for ultrasound tomography [5] (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

“…Producing reliable cross-sectional images of sound-speed and attenuation at a resolution of 2-4 mm (see [5] for a complete analysis of phantom data).…”

mentioning

confidence: 99%

See 4 more Smart Citations

An improved automatic time-of-flight picker for medical ultrasound tomography

et al. 2009

Self Cite

View full text Add to dashboard Cite

Objective and motivation-Time-of-flight (TOF) tomography used by a clinical ultrasound tomography device can efficiently and reliably produce sound-speed images of the breast for cancer diagnosis. Accurate picking of TOFs of transmitted ultrasound signals is extremely important to ensure high-resolution and high-quality ultrasound sound-speed tomograms. Since manually picking is time-consuming for large datasets, we developed an improved automatic TOF picker based on the Akaike information criterion (AIC), as described in this paper.Methods-We make use of an approach termed multi-model inference (model averaging), based on the calculated AIC values, to improve the accuracy of TOF picks. By using multi-model inference, our picking method incorporates all the information near the TOF of ultrasound signals. Median filtering and reciprocal pair comparison are also incorporated in our AIC picker to effectively remove outliers.Results-We validate our AIC picker using synthetic ultrasound waveforms, and demonstrate that our automatic TOF picker can accurately pick TOFs in the presence of random noise with absolute amplitudes up to 80% of the maximum absolute signal amplitude. We apply the new method to 1160 in vivo breast ultrasound waveforms, and compare the picked TOFs with manual picks and amplitude threshold picks. The mean value and standard deviation between our TOF picker and manual picking are 0.4 μs and 0.29 μs, while for amplitude threshold picker the values are 1.02 μs and 0.9 μs, respectively. Tomograms for in vivo breast data with high signal-to-noise ratio (SNR) (~25 dB) and low SNR (~18 dB) clearly demonstrate that our AIC picker is much less sensitive to the SNRs of the data, compared to the amplitude threshold picker.Discussion and conclusions-The picking routine developed here is aimed at determining reliable quantitative values, necessary for adding diagnostic information to our clinical ultrasound tomography device -CURE. It has been successfully adopted into CURE, and allows us to generate such values reliably. We demonstrate that in vivo sound-speed tomograms with our TOF picks significantly improve the reconstruction accuracy and reduce image artifacts.

show abstract

“…(a) Schematic illustration of a ring transducer array (from [5]). (b) Interaction of an ultrasound pulse with a target leads to a scattered ultrasound field (from [17]).…”

Section: Discussionmentioning

confidence: 99%

Section: Ultrasound Breast Data Acquired Using the Cure Devicementioning

confidence: 99%

“…Compute the Akaike weights for each data point within the time window: (4) 4. Obtain the TOF value using the weighted average: (5) where t i (i = 1; . .…”

Section: Using a Weighted Average Model To Determinementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Producing reliable cross-sectional images of sound-speed and attenuation at a resolution of 2-4 mm (see [5] for a complete analysis of phantom data).…”

mentioning

confidence: 99%

See 3 more Smart Citations

An improved automatic time-of-flight picker for medical ultrasound tomography

et al. 2009

Self Cite

View full text Add to dashboard Cite

show abstract

Tomography across scales: Knowledge transfer from seismology to imaging breast tissue with ultrasound

Martiartu

Boehm

Hapla

et al. 2019

Preprint

View full text Add to dashboard Cite

Wave propagation is extensively used to understand the internal structure of media that are not accessible to direct observations. Seismology and medical ultrasound imaging are good examples of this. The former uses observations of seismic waves at the Earth's surface to increase our knowledge about its interior. This is crucial, for instance, to improve our understanding about the Earth's dynamics and evolution. Medical ultrasound, on the other hand, uses observations of acoustic waves, emitted and recorded at the surface of human bodies, to visualize internal body structures. This has become an essential screening tool, useful for diagnostic examination.This thesis presents an interdisciplinary work between seismology and medical ultrasound. In particular, we focus on transferring knowledge from seismic tomography to Ultrasound Computer Tomography (USCT), an emerging technology that holds great potential for early-stage breast cancer diagnosis. Here, the human breast is surrounded by transducers that collect transmitted and reflected ultrasound signals. This information is then used to obtain 3D quantitative images of acoustic tissue properties, which enable non-invasive tissue characterization and improve the specificity of standard imaging modalities. Current challenges in USCT mostly consist in providing a diagnostic tool with high accuracy (comparable to magnetic resonance imaging) and affordable computational and acquisition cost for clinical practice, the target being a maximum time of 15 minutes per patient. Despite the vastly different scale, seismic and medical ultrasound tomography share fundamental similarities that allow us to address these challenges from the stand point of the seismologist.We first introduce finite-frequency traveltime tomography to medical ultrasound. In addition to being computationally tractable for 3D imaging at high frequencies, the method has two main advantages: (1) It correctly accounts for the frequency dependence and volumetric sensitivity of traveltime measurements, which are related to off-ray-path scattering and diffraction. (2) It naturally enables out-of-plane imaging and the construction of 3D images from 2D slice-by-slice acquisition systems. Our method rests on the availability of calibration data measured in water, used to linearize the forward problem and to provide analytical expressions of cross-correlation traveltime sensitivity. We present a memoryefficient implementation suitable for arbitrarily large-scale domains, and we discuss its extension to amplitude tomography.To adapt existing acquisition systems to new imaging techniques, we then introduce optimal experimental design methods. These provide a systematic and quantitative framework i to (1) evaluate the quality of different designs in terms of uncertainties in the estimated tissue parameters and (2) optimize the configuration with respect to predefined design parameters, for example the position of transducers on the scanning device. Our first application presents a cost-effective 3D configuration o...

show abstract

Spatially tracked whole‐breast three‐dimensional ultrasound system toward point‐of‐care breast cancer screening in high‐risk women with dense breasts

et al. 2022

View full text Add to dashboard Cite

Background Mammographic screening has reduced mortality in women through the early detection of breast cancer. However, the sensitivity for breast cancer detection is significantly reduced in women with dense breasts, in addition to being an independent risk factor. Ultrasound (US) has been proven effective in detecting small, early‐stage, and invasive cancers in women with dense breasts. Purpose To develop an alternative, versatile, and cost‐effective spatially tracked three‐dimensional (3D) US system for whole‐breast imaging. This paper describes the design, development, and validation of the spatially tracked 3DUS system, including its components for spatial tracking, multi‐image registration and fusion, feasibility for whole‐breast 3DUS imaging and multi‐planar visualization in tissue‐mimicking phantoms, and a proof‐of‐concept healthy volunteer study. Methods The spatially tracked 3DUS system contains (a) a six‐axis manipulator and counterbalanced stabilizer, (b) an in‐house quick‐release 3DUS scanner, adaptable to any commercially available US system, and removable, allowing for handheld 3DUS acquisition and two‐dimensional US imaging, and (c) custom software for 3D tracking, 3DUS reconstruction, visualization, and spatial‐based multi‐image registration and fusion of 3DUS images for whole‐breast imaging. Spatial tracking of the 3D position and orientation of the system and its joints (J1–6) were evaluated in a clinically accessible workspace for bedside point‐of‐care (POC) imaging. Multi‐image registration and fusion of acquired 3DUS images were assessed with a quadrants‐based protocol in tissue‐mimicking phantoms and the target registration error (TRE) was quantified. Whole‐breast 3DUS imaging and multi‐planar visualization were evaluated with a tissue‐mimicking breast phantom. Feasibility for spatially tracked whole‐breast 3DUS imaging was assessed in a proof‐of‐concept healthy male and female volunteer study. Results Mean tracking errors were 0.87 ± 0.52, 0.70 ± 0.46, 0.53 ± 0.48, 0.34 ± 0.32, 0.43 ± 0.28, and 0.78 ± 0.54 mm for joints J1–6, respectively. Lookup table (LUT) corrections minimized the error in joints J1, J2, and J5. Compound motions exercising all joints simultaneously resulted in a mean tracking error of 1.08 ± 0.88 mm (N = 20) within the overall workspace for bedside 3DUS imaging. Multi‐image registration and fusion of two acquired 3DUS images resulted in a mean TRE of 1.28 ± 0.10 mm. Whole‐breast 3DUS imaging and multi‐planar visualization in axial, sagittal, and coronal views were demonstrated with the tissue‐mimicking breast phantom. The feasibility of the whole‐breast 3DUS approach was demonstrated in healthy male and female volunteers. In the male volunteer, the high‐resolution whole‐breast 3DUS acquisition protocol was optimized without the added complexities of curvature and tissue deformations. With small post‐acquisition corrections for motion, whole‐breast 3DUS imaging was performed on the healthy female volunteer showing relevant anatomical structures and details. Conc...

show abstract

Detection of breast cancer with ultrasound tomography: First results with the Computed Ultrasound Risk Evaluation (CURE) prototype

Cited by 336 publications

References 24 publications

An improved automatic time-of-flight picker for medical ultrasound tomography

An improved automatic time-of-flight picker for medical ultrasound tomography

Tomography across scales: Knowledge transfer from seismology to imaging breast tissue with ultrasound

Spatially tracked whole‐breast three‐dimensional ultrasound system toward point‐of‐care breast cancer screening in high‐risk women with dense breasts

Contact Info

Product

Resources

About