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Ghazi P, Youssefian S, Ghazi T. A novel hardware duo of beam modulation and shielding to reduce scatter acquisition and dose in cone-beam breast CT. Med Phys 2021; 49:169-185. [PMID: 34825715 DOI: 10.1002/mp.15374] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 11/07/2021] [Accepted: 11/12/2021] [Indexed: 12/12/2022] Open
Abstract
PURPOSE In cone-beam breast CT, scattered photons form a large portion of the acquired signal, adversely impacting image quality throughout the frequency response of the imaging system. Prior simulation studies provided proof of concept for utilization of a hardware solution to prevent scatter acquisition. Here, we report the design, implementation, and characterization of an auxiliary apparatus of fluence modulation and scatter shielding that does indeed lead to projections with a reduced level of scatter. METHODS An apparatus was designed for permanent installation within an existing cone-beam CT system. The apparatus is composed of two primary assemblies: a "Fluence Modulator" (FM) and a "Scatter Shield" (SS). The design of the assemblies enables them to operate in synchrony during image acquisition, converting the sourced x-rays into a moving narrow beam. During a projection, this narrow beam sweeps the entire fan angle coverage of the imaging system. As the two assemblies are contingent on one another, their joint implementation is described in the singular as apparatus FM-SS. The FM and the SS assemblies are each comprised a metal housing, a sensory system, and a robotic system. A controller unit handles their relative movements. A series of comparative studies were conducted to evaluate the performance of a cone-beam CT system in two "modes" of operation: with and without FM-SS installed, and to compare the results of physical implementation with those previously simulated. The dynamic range requirements of the utilized detector in the cone-beam CT imaging system were first characterized, independent of the mode of operation. We then characterized and compared the spatial resolution of the imaging system with, and without, FM-SS. A physical breast phantom, representative of an average size breast, was developed and imaged. Actual differences in signal level obtained with, versus without, FM-SS were then compared to the expected level gains based on previously reported simulations. Following these initial assessments, the scatter acquisition in each projection in both modes of operation was investigated. Finally, as an initial study of the impact of FM-SS on radiation dose in an average size breast, a series of Monte Carlo simulations were coupled with physical measurements of air kerma, with and without FM-SS. RESULTS With implementation of FM-SS, the detector's required dynamic range was reduced by a factor of 5.5. Substantial reduction in the acquisition of the scattered rays, by a factor of 5.1 was achieved. With the implementation of FM-SS, deposited dose was reduced by 27% in the studied breast. CONCLUSIONS The disclosed implementation of FM-SS, within a cone-beam breast CT system, results in reduction of scatter-components in acquired projections, reduction of dose deposit to the breast, and relaxation of requirements for the detector's dynamic range. Controlling or correcting for patient motion occurring during image acquisition remains an open problem to be solved prior to practical clinical usage of FM-SS cone-beam breast CT.
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Roser P, Birkhold A, Preuhs A, Syben C, Felsner L, Hoppe E, Strobel N, Kowarschik M, Fahrig R, Maier A. X-Ray Scatter Estimation Using Deep Splines. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2272-2283. [PMID: 33881991 DOI: 10.1109/tmi.2021.3074712] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
X-ray scatter compensation is a very desirable technique in flat-panel X-ray imaging and cone-beam computed tomography. State-of-the-art U-net based scatter removal approaches yielded promising results. However, as there are no physics' constraints applied to the output of the U-Net, it cannot be ruled out that it yields spurious results. Unfortunately, in the context of medical imaging, those may be misleading and could lead to wrong conclusions. To overcome this problem, we propose to embed B-splines as a known operator into neural networks. This inherently constrains their predictions to well-behaved and smooth functions. In a study using synthetic head and thorax data as well as real thorax phantom data, we found that our approach performed on par with U-net when comparing both algorithms based on quantitative performance metrics. However, our approach not only reduces runtime and parameter complexity, but we also found it much more robust to unseen noise levels. While the U-net responded with visible artifacts, the proposed approach preserved the X-ray signal's frequency characteristics.
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Ghazi P, Hernandez AM, Abbey C, Yang K, Boone JM. Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach. Med Phys 2019; 46:3414-3430. [PMID: 31102462 DOI: 10.1002/mp.13599] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 05/09/2019] [Accepted: 05/12/2019] [Indexed: 12/19/2022] Open
Abstract
PURPOSE The purpose of this work was twofold: (a) To provide a robust and accurate method for image segmentation of dedicated breast CT (bCT) volume data sets, and (b) to improve Hounsfield unit (HU) accuracy in bCT by means of a postprocessing method that uses the segmented images to correct for the low-frequency shading artifacts in reconstructed images. METHODS A sequential and iterative application of image segmentation and low-order polynomial fitting to bCT volume data sets was used in the interleaved correction (IC) method. Image segmentation was performed through a deep convolutional neural network (CNN) with a modified U-Net architecture. A total of 45 621 coronal bCT images from 111 patient volume data sets were segmented (using a previously published segmentation algorithm) and used for neural network training, validation, and testing. All patient data sets were selected from scans performed on four different prototype breast CT systems. The adipose voxels for each patient volume data set, segmented using the proposed CNN, were then fit to a three-dimensional low-order polynomial. The polynomial fit was subsequently used to correct for the shading artifacts introduced by scatter and beam hardening in a method termed "flat fielding." An interleaved utilization of image segmentation and flat fielding was repeated until a convergence criterion was satisfied. Mathematical and physical phantom studies were conducted to evaluate the dependence of the proposed algorithm on breast size and the distribution of fibroglandular tissue. In addition, a subset of patient scans (not used in the CNN training, testing or validation) were used to investigate the accuracy of the IC method across different scanner designs and beam qualities. RESULTS The IC method resulted in an accurate classification of different tissue types with an average Dice similarity coefficient > 95%, precision > 97%, recall > 95%, and F1-score > 96% across all tissue types. The flat fielding correction of bCT images resulted in a significant reduction in either cupping or capping artifacts in both mathematical and physical phantom studies as measured by the integral nonuniformity metric with an average reduction of 71% for cupping and 30% for capping across different phantom sizes, and the Uniformity Index with an average reduction of 53% for cupping and 34% for capping. CONCLUSION The validation studies demonstrated that the IC method improves Hounsfield Units (HU) accuracy and effectively corrects for shading artifacts caused by scatter contamination and beam hardening. The postprocessing approach described herein is relevant to the broad scope of bCT devices and does not require any modification in hardware or existing scan protocols. The trained CNN parameters and network architecture are available for interested users.
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Affiliation(s)
| | - Andrew M Hernandez
- Department of Radiology, University of California Davis, Sacramento, CA, 95817, USA
| | - Craig Abbey
- Department of Psychological & Brain Sciences, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Kai Yang
- Department of Radiology, Massachusetts General Hospital, Boston, MA, 2114, USA
| | - John M Boone
- Department of Radiology, University of California Davis, Sacramento, CA, 95817, USA
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Shah JP, Mann SD, Tornai MP. Characterization of X-ray scattering for various phantoms and clinical breast geometries using breast CT on a dedicated hybrid system. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2017; 25:373-389. [PMID: 28157120 PMCID: PMC6022823 DOI: 10.3233/xst-16202] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
OBJECTIVE The purpose of this study was to utilize a dedicated breast CT system using a 2D beam stop array to physically evaluate the scatter to primary ratios (SPRs) of different geometric phantoms and prospectively acquired clinical patient data. METHODS Including clinically unrealizable compositions of 100% glandular and 100% fat, projection images were acquired using three geometrically different phantoms filled with fluids simulating breast tissue. The beam stop array method was used for measuring scatter in projection space, and creating the scatter corrected primary images. 2D SPRs were calculated. Additionally, a new figure of merit, the 3D normalized scatter contribution (NSC) volumes were calculated. RESULTS The 2D SPR values (0.52-1.10) were primarily dependent on phantom geometry; a secondary dependence was due to their uniform density; 2D SPRs were low frequency and smoothly varying in the uniformly filled phantoms. SPRs of clinical patient data followed similar trends as phantoms, but with noticeable deviations and high frequency components due to the heterogeneous distribution of glandular tissue. The maximum measured patient 2D SPRs were all <0.6, even for the largest diameter breast. These results demonstrate modest scatter components with changing object geometries and densities; the 3D NSC volumes with higher frequency components help visualize scatter distribution throughout the reconstructed image volumes. Furthermore, the SPRs in the heterogeneous clinical breast cases were underestimated by the equivalent density, uniformly filled phantoms. CONCLUSIONS These results provide guidance on the use of uniformly distributed density and differently shaped phantoms when considering simulations. They also clearly demonstrate that results from patients can vary considerably from 2D SPRs of uniformly simulated phantoms.
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Affiliation(s)
- Jainil P. Shah
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Radiology, Duke University Medical Center, Durham, NC, USA
| | - Steve D. Mann
- Department of Radiology, Duke University Medical Center, Durham, NC, USA
- Medical Physics Graduate Program, Duke University Medical Center, Durham, NC, USA
| | - Martin P. Tornai
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Department of Radiology, Duke University Medical Center, Durham, NC, USA
- Medical Physics Graduate Program, Duke University Medical Center, Durham, NC, USA
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Dunkerley DAP, Tomkowiak MT, Slagowski JM, McCabe BP, Funk T, Speidel MA. Monte Carlo simulation of inverse geometry x-ray fluoroscopy using a modified MC-GPU framework. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2015; 9412:94120S. [PMID: 26113765 PMCID: PMC4476537 DOI: 10.1117/12.2081684] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Scanning-Beam Digital X-ray (SBDX) is a technology for low-dose fluoroscopy that employs inverse geometry x-ray beam scanning. To assist with rapid modeling of inverse geometry x-ray systems, we have developed a Monte Carlo (MC) simulation tool based on the MC-GPU framework. MC-GPU version 1.3 was modified to implement a 2D array of focal spot positions on a plane, with individually adjustable x-ray outputs, each producing a narrow x-ray beam directed toward a stationary photon-counting detector array. Geometric accuracy and blurring behavior in tomosynthesis reconstructions were evaluated from simulated images of a 3D arrangement of spheres. The artifact spread function from simulation agreed with experiment to within 1.6% (rRMSD). Detected x-ray scatter fraction was simulated for two SBDX detector geometries and compared to experiments. For the current SBDX prototype (10.6 cm wide by 5.3 cm tall detector), x-ray scatter fraction measured 2.8-6.4% (18.6-31.5 cm acrylic, 100 kV), versus 2.1-4.5% in MC simulation. Experimental trends in scatter versus detector size and phantom thickness were observed in simulation. For dose evaluation, an anthropomorphic phantom was imaged using regular and regional adaptive exposure (RAE) scanning. The reduction in kerma-area-product resulting from RAE scanning was 45% in radiochromic film measurements, versus 46% in simulation. The integral kerma calculated from TLD measurement points within the phantom was 57% lower when using RAE, versus 61% lower in simulation. This MC tool may be used to estimate tomographic blur, detected scatter, and dose distributions when developing inverse geometry x-ray systems.
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Affiliation(s)
| | | | | | - Bradley P McCabe
- Dept. of Radiation Oncology, University of Chicago, Chicago, IL, USA
| | - Tobias Funk
- Triple Ring Technologies, Inc, Newark, CA, USA
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Sechopoulos I, Bliznakova K, Qin X, Fei B, Feng SSJ. Characterization of the homogeneous tissue mixture approximation in breast imaging dosimetry. Med Phys 2012; 39:5050-9. [PMID: 22894430 DOI: 10.1118/1.4737025] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation. METHODS Twenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio-caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast CT (uncompressed breasts). For the mammography simulations the x-ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x-ray spectra were used, corresponding to the x-ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared. RESULTS For mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Test p = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution. CONCLUSIONS The normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x-ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x-ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further work is required to better characterize this overestimation and potentially develop new metrics or correction factors to better estimate the true glandular dose to breasts undergoing imaging with ionizing radiation.
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Affiliation(s)
- Ioannis Sechopoulos
- Department of Radiology and Imaging Sciences and Winship Cancer Institute, Emory University School of Medicine, 1701 Upper Gate Drive Northeast, Suite 5018, Atlanta, Georgia 30322, USA.
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Sechopoulos I. X-ray scatter correction method for dedicated breast computed tomography. Med Phys 2012; 39:2896-903. [PMID: 22559662 DOI: 10.1118/1.4711749] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
PURPOSE To improve image quality and accuracy in dedicated breast computed tomography (BCT) by removing the x-ray scatter signal included in the BCT projections. METHODS The previously characterized magnitude and distribution of x-ray scatter in BCT results in both cupping artifacts and reduction of contrast and accuracy in the reconstructions. In this study, an image processing method is proposed that estimates and subtracts the low-frequency x-ray scatter signal included in each BCT projection postacquisition and prereconstruction. The estimation of this signal is performed using simple additional hardware, one additional BCT projection acquisition with negligible radiation dose, and simple image processing software algorithms. The high frequency quantum noise due to the scatter signal is reduced using a noise filter postreconstruction. The dosimetric consequences and validity of the assumptions of this algorithm were determined using Monte Carlo simulations. The feasibility of this method was determined by imaging a breast phantom on a BCT clinical prototype and comparing the corrected reconstructions to the unprocessed reconstructions and to reconstructions obtained from fan-beam acquisitions as a reference standard. One-dimensional profiles of the reconstructions and objective image quality metrics were used to determine the impact of the algorithm. RESULTS The proposed additional acquisition results in negligible additional radiation dose to the imaged breast (∼0.4% of the standard BCT acquisition). The processed phantom reconstruction showed substantially reduced cupping artifacts, increased contrast between adipose and glandular tissue equivalents, higher voxel value accuracy, and no discernible blurring of high frequency features. CONCLUSIONS The proposed scatter correction method for dedicated breast CT is feasible and can result in highly improved image quality. Further optimization and testing, especially with patient images, is necessary to characterize its impact on clinical performance.
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Affiliation(s)
- Ioannis Sechopoulos
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA.
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Rührnschopf EP, Klingenbeck K. A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches. Med Phys 2011; 38:4296-311. [PMID: 21859031 DOI: 10.1118/1.3599033] [Citation(s) in RCA: 114] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Since scattered radiation in cone-beam volume CT implies severe degradation of CT images by quantification errors, artifacts, and noise increase, scatter suppression is one of the main issues related to image quality in CBCT imaging. The aim of this review is to structurize the variety of scatter suppression methods, to analyze the common structure, and to develop a general framework for scatter correction procedures. In general, scatter suppression combines hardware techniques of scatter rejection and software methods of scatter correction. The authors emphasize that scatter correction procedures consist of the main components scatter estimation (by measurement or mathematical modeling) and scatter compensation (deterministic or statistical methods). The framework comprises most scatter correction approaches and its validity also goes beyond transmission CT. Before the advent of cone-beam CT, a lot of papers on scatter correction approaches in x-ray radiography, mammography, emission tomography, and in Megavolt CT had been published. The opportunity to avail from research in those other fields of medical imaging has not yet been sufficiently exploited. Therefore additional references are included when ever it seems pertinent. Scatter estimation and scatter compensation are typically intertwined in iterative procedures. It makes sense to recognize iterative approaches in the light of the concept of self-consistency. The importance of incorporating scatter compensation approaches into a statistical framework for noise minimization has to be underscored. Signal and noise propagation analysis is presented. A main result is the preservation of differential-signal-to-noise-ratio (dSNR) in CT projection data by ideal scatter correction. The objective of scatter compensation methods is the restoration of quantitative accuracy and a balance between low-contrast restoration and noise reduction. In a synopsis section, the different deterministic and statistical methods are discussed with respect to their properties and applications. The current paper is focused on scatter compensation algorithms. The multitude of scatter estimation models will be dealt with in a separate paper.
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Schmidt TG. What is inverse-geometry CT? J Cardiovasc Comput Tomogr 2011; 5:145-8. [DOI: 10.1016/j.jcct.2011.04.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2011] [Accepted: 04/11/2011] [Indexed: 10/18/2022]
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Lippuner J, Elbakri IA, Cui C, Ingleby HR. Epp: A C
++ EGSnrc user code for x-ray imaging and scattering simulations. Med Phys 2011; 38:1705-8. [DOI: 10.1118/1.3555296] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
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Schmidt TG. CT energy weighting in the presence of scatter and limited energy resolution. Med Phys 2010; 37:1056-67. [PMID: 20384241 DOI: 10.1118/1.3301615] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Taly Gilat Schmidt
- Department of Biomedical Engineering, Marquette University, Milwaukee, Wisconsin 53201
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Stop Breast Cancer Now! Imagining Imaging Pathways Toward Search, Destroy, Cure, and Watchful Waiting of Premetastasis Breast Cancer. Breast Cancer 2010. [DOI: 10.1007/978-1-84996-314-5_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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