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Park CKS, Xing S, Papernick S, Orlando N, Knull E, Toit CD, Bax JS, Gardi L, Barker K, Tessier D, Fenster A. Spatially tracked whole-breast three-dimensional ultrasound system toward point-of-care breast cancer screening in high-risk women with dense breasts. Med Phys 2022; 49:3944-3962. [PMID: 35319105 DOI: 10.1002/mp.15632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 03/16/2022] [Accepted: 03/17/2022] [Indexed: 11/06/2022] Open
Abstract
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. CONCLUSIONS Our spatially tracked 3DUS system shows potential utility as an alternative, accurate, and feasible whole-breast approach with the capability for bedside POC imaging. Future work is focused on reducing misregistration errors due to motion and tissue deformations, to develop a robust spatially tracked whole-breast 3DUS acquisition protocol, then exploring its clinical utility for screening high-risk women with dense breasts.
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Affiliation(s)
- Claire Keun Sun Park
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Shuwei Xing
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,School of Biomedical Engineering, Faculty of Engineering, Western University, London, Ontario, Canada
| | - Samuel Papernick
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Nathan Orlando
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Eric Knull
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,School of Biomedical Engineering, Faculty of Engineering, Western University, London, Ontario, Canada
| | - Carla Du Toit
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,School of Kinesiology, Faculty of Health Sciences, Western University, London, Ontario, Canada
| | - Jeffrey Scott Bax
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Lori Gardi
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Kevin Barker
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - David Tessier
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada
| | - Aaron Fenster
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.,School of Biomedical Engineering, Faculty of Engineering, Western University, London, Ontario, Canada.,Division of Imaging Sciences, Department of Medical Imaging, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
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Eisenbrey JR, Sridharan A, Machado P, Zhao H, Halldorsdottir VG, Dave JK, Liu JB, Park S, Dianis S, Wallace K, Thomenius KE, Forsberg F. Three-dimensional subharmonic ultrasound imaging in vitro and in vivo. Acad Radiol 2012; 19:732-9. [PMID: 22464198 DOI: 10.1016/j.acra.2012.02.015] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2012] [Revised: 02/08/2012] [Accepted: 02/09/2012] [Indexed: 12/27/2022]
Abstract
RATIONALE AND OBJECTIVES Although contrast-enhanced ultrasound imaging techniques such as harmonic imaging (HI) have evolved to reduce tissue signals using the nonlinear properties of the contrast agent, levels of background suppression have been mixed. Subharmonic imaging (SHI) offers near complete tissue suppression by centering the receive bandwidth at half the transmitting frequency. The aims of this study were to demonstrate the feasibility of three-dimensional (3D) SHI and to compare it to 3D HI. MATERIALS AND METHODS Three-dimensional HI and SHI were implemented on a Logiq 9 ultrasound scanner with a 4D10L probe. Four-cycle SHI was implemented to transmit at 5.8 MHz and receive at 2.9 MHz, while two-cycle HI was implemented to transmit at 5 MHz and receive at 10 MHz. The ultrasound contrast agent Definity was imaged within a flow phantom and the lower pole of two canine kidneys in both HI and SHI modes. Contrast-to-tissue ratios and rendered images were compared offline. RESULTS SHI resulted in significant improvement in contrast-to-tissue ratios relative to HI both in vitro (12.11 ± 0.52 vs 2.67 ± 0.77, P< .001) and in vivo (5.74 ± 1.92 vs 2.40 ± 0.48, P = .04). Rendered 3D subharmonic images provided better tissue suppression and a greater overall view of vessels in a flow phantom and canine renal vasculature. CONCLUSIONS The successful implementation of SHI in 3D allows imaging of vascular networks over a heterogeneous sample volume and should improve future diagnostic accuracy. Additionally, 3D SHI provides improved contrast-to-tissue ratios relative to 3D HI.
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Hansen C, Hüttebräuker N, Wilkening W, Ermert H. A method to expedite data acquisition for multiple spatial-temporal analyses of tissue perfusion by contrast-enhanced ultrasound. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2009; 56:507-519. [PMID: 19411210 DOI: 10.1109/tuffc.2009.1068] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
For semiquantitative analyses of tissue perfusion using contrast-enhanced ultrasound the acquisition and processing of time intensity curves (TIC) is required. These TICs can be computed for each pixel of an image plane, yielding parametric images of classification numbers like "blood volume" and "flow rate." The expenditure of time for data acquisition and analysis typically limits semiquantitative perfusion imaging to a single image plane in 2-D. 3-D techniques, however, provide a higher diagnostic value since more information (e.g., of an entire lesion) is obtained. Moreover, spatial compounding, being a 2-D-technique where an object is imaged from different viewing angles, is known to improve image quality by reducing artifacts and speckle noise. Both techniques, 3-D and compounding, call for optimized acquisition and processing of TICs in several image planes (3-D) or in several (overlapping) sections of the same image plane (compounding) to decrease the time needed for data acquisition. Here, an approach of interleaved imaging is presented which is applicable, among others, to contrast perfusion imaging using the replenishment method. The total acquisition time is decreased by sequentially scanning image planes twice for short time spans - first, immediately after microbubble destruction to record the initial rise of the TICs, and second, a sufficient time thereafter to assess final values of the TIC. Data from both periods are combined to fit a model function from which parameters are extracted such as perfusion rate and blood volume. This approach was evaluated by in vitro measurements on a perfusion-mimicking phantom for both, individual images such as would be used for volume reconstruction in 3-D and compound images obtained from full angle spatial compounding (FASC, 360 degrees ). An error analysis is conducted to derive the deviation of the extracted parameters of the proposed method compared with the conventional one. These deviations are entailed by a reduction in acquisition time of the proposed method, which can be adjusted by several parameters, depending on the prevailing flow. Optimization strategies are proposed to find optimal values for those settings.
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Affiliation(s)
- Christian Hansen
- Institute for High Frequency Engineering, Ruhr-University, Bochum, Germany.
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