3D Breast Phantom Research Articles

Analysing Student Feedback on the Integration of 3D Printing in the Teaching of Mammography for Radiologic Technologists

The objective of this study is to assess the suitability of using printed breast models as educational tools for instructing radiographer students on positioning and compression techniques in X-ray mammography. A physical anthropomorphic breast phantom, created with a stereolithography 3D printer based on a computational breast model, served as the main tool in the teaching approach. The practical exercise, conducted in three sessions for first, second, and third-year radiographer students, involved a structured approach in front of the mammography device. A questionnaire assessed participants' opinions on the 3D breast phantom and the exercise's impact on positioning, compression, and mammography device teachings. Among the 83 students surveyed, 52 provided responses, demonstrating a success rate of 71.2% in mastering the exercise utilizing the physical breast phantom. A significant portion of students express the importance of integrating contemporary digital technologies into their academic curriculum, based on the practical experience. The instructor demonstrated thorough preparation and competence in guiding the practical session. The positive experience in this teaching approach strongly encourages future professionals to integrate these new technologies into their daily practice, especially for acquiring skills in compression techniques and breast positioning.

Cost-effective, portable, patient-dedicated three-dimensional automated breast ultrasound for point-of-care breast cancer screening

Breast cancer screening has substantially reduced mortality across screening populations. However, a clinical need persists for more accessible, cost-effective, and robust approaches for increased-risk and diverse patient populations, especially those with dense breasts where screening mammography is suboptimal. We developed and validated a cost-effective, portable, patient-dedicated three-dimensional (3D) automated breast ultrasound (ABUS) system for point-of-care breast cancer screening. The 3D ABUS system contains a wearable, rapid-prototype 3D-printed dam assembly, a compression assembly, and a computer-driven 3DUS scanner, adaptable to any commercially available US machine and transducer. Acquisition is operator-agnostic, involves a 40-second scan time, and provides multiplanar 3D visualization for whole-breast assessment. Geometric reconstruction accuracy was evaluated with a 3D grid phantom and tissue-mimicking breast phantoms, demonstrating linear measurement and volumetric reconstruction errors < 0.2 mm and < 3%, respectively. The system’s capability was demonstrated in a healthy male volunteer and two healthy female volunteers, representing diverse patient geometries and breast sizes. The system enables comfortable ultrasonic coupling and tissue stabilization, with adjustable compression to improve image quality while alleviating discomfort. Moreover, the system effectively mitigates breathing and motion, since its assembly affixes directly onto the patient. While future studies are still required to evaluate the impact on current clinical practices and workflow, the 3D ABUS system shows potential for adoption as an alternative, cost-effective, dedicated point-of-care breast cancer screening approach for increased-risk populations and limited-resource settings.

Mitigating Under-Sampling Artifacts in 3D Photoacoustic Imaging Using Res-UNet Based on Digital Breast Phantom.

In recent years, photoacoustic (PA) imaging has rapidly grown as a non-invasive screening technique for breast cancer detection using three-dimensional (3D) hemispherical arrays due to their large field of view. However, the development of breast imaging systems is hindered by a lack of patients and ground truth samples, as well as under-sampling problems caused by high costs. Most research related to solving these problems in the PA field were based on 2D transducer arrays or simple regular shape phantoms for 3D transducer arrays or images from other modalities. Therefore, we demonstrate an effective method for removing under-sampling artifacts based on deep neural network (DNN) to reconstruct high-quality PA images using numerical digital breast simulations. We constructed 3D digital breast phantoms based on human anatomical structures and physical properties, which were then subjected to 3D Monte-Carlo and K-wave acoustic simulations to mimic acoustic propagation for hemispherical transducer arrays. Finally, we applied a 3D delay-and-sum reconstruction algorithm and a Res-UNet network to achieve higher resolution on sparsely-sampled data. Our results indicate that when using a 757 nm laser with uniform intensity distribution illuminated on a numerical digital breast, the imaging depth can reach 3 cm with 0.25 mm spatial resolution. In addition, the proposed DNN can significantly enhance image quality by up to 78.4%, as measured by MS-SSIM, and reduce background artifacts by up to 19.0%, as measured by PSNR, even at an under-sampling ratio of 10%. The post-processing time for these improvements is only 0.6 s. This paper suggests a new 3D real time DNN method addressing the sparse sampling problem based on numerical digital breast simulations, this approach can also be applied to clinical data and accelerate the development of 3D photoacoustic hemispherical transducer arrays for early breast cancer diagnosis.

Technical Note: Realization and uncertainty analysis for an adjustable 3D structured breast phantom in digital breast tomosynthesis.

Projection imaging phantoms are often optimized for 2-dimensional image characteristics in homogeneous backgrounds. Therefore, evaluation of image quality in tomosynthesis (DBT) lacks accepted and establishedphantoms. We describe a 3D breast phantom with a structured, variable background. The phantom is an adaptable and advanced version of the L1 phantom by Cockmartin etal. Phantom design and its use for quality assurance measurements for DBT devices are described. Four phantoms were compared to assess theobjectivity. The container size was increased to a diameter of 24cm and a total height of 53.5 mm. Spiculated masses were replaced by five additional non-spiculated masses for higher granularity in threshold diameter resolution. These patterns are adjustable to the imaging device. The masses were printed in one session with a base layer using two-component 3D printing. New materials compared to the L1 phantom improved the attenuation difference between the lesion models and the background. Four phantoms were built and intra-human observer, inter-human observer and inter-phantom variations were determined. The latter assess the reproducibility of the phantom production. Coefficients of variance (V) were calculated for all threevariations. The difference of the attenuation coefficients between the lesion models and the background was 0.20cm-1 (with W/Al at 32kV, equivalent to 19-20keV effective energy) compared to 0.21cm-1 for 50/50 glandular/adipose breast tissue and cancerous lesions. PMMA equivalent thickness of the phantom was 47.0mm for the Siemens Mammomat Revelation. For the masses, the for the intra-observer variation was 0.248, the averaged inter-observer variation, was 0.383. for phantom variance was 0.321. For the micro-calcifications, was 0.0429, 0.0731 and 0.0759. Position, orientation and shape of the masses are reproducible and attenuation differences appropriate. The phantom presented proved to be a candidate test object for qualitycontrol.

An Innovative Concept of a 3D-Coded Aperture Imaging System Proposed for Early Breast Cancer Detection.

Coded Aperture (CA) imaging has recently been used in nuclear medicine, but still, there is no commercial SPECT imaging camera based on CA for cancer detection. The literature is rich in examples of using the CA for planar and thin 3D imaging. However, thick 3D reconstruction is still challenging for small lesion detection. This paper presents the results of mosaic modified uniformly redundant array (MURA) mask/antimask CA combined with a maximum-likelihood expectation-maximization (MLEM) algorithm. The MLEM is an iterative algorithm applied to a mosaic MURA CA mask/antimask for 3D anthropomorphic breast phantom reconstruction, slice by slice. The difference between the mask and the antimask suppresses the background noise to enhance the quality of reconstructed images. Furthermore, all reconstructed slices are stacked to form a 3D breast phantom image from single-projection data. The results of phantom reconstruction with 8 mm, 6 mm, 4 mm, and 3 mm lesions are presented. Moreover, the proposed SPECT imaging camera can reconstruct a 3D breast phantom from single-projection data of the patient’s scanning. To assess the quality of lesions in the reconstructed images, the contrast-to-background ratio (CBR), the peak signal-to-noise ratio (PSNR) and mean square error (MSE) were measured.

Circular shape MIMO antenna sensor for breast tumor detection

Abstract In this paper, a compact circular shape ultra-wide microstrip antenna is proposed for the detection of breast tumor. The proposed antenna is a two-port MIMO antenna of 1 × 2 elements. The dimensions of the proposed antenna are 34 mm × 18mm × 1.6 mm. It is designed over a lower-cost FR-4 epoxy substrate with a partial ground plane. The antenna is operated between the frequency range of 3.1–9.6 GHz. Isolation between the antenna element is less than −22 dB from 3.1 GHz to 7 GHz and −25 dB between 7 GHz and 10.6 GHz. The obtained ECC of the designed MIMO antenna is less than 0.01 and also DG is almost 10 dB in the entire UWB range. Further, the 3D breast phantom model is also simulated for analysis of the effect of SAR. Due to the variation in the electrical properties of cancerous cells and healthy cells it is possible to identify the cancerous tumor using SAR analysis. The obtained maximum Average SAR value without a tumor is 41.97 W/kg and with a cancerous tumor is 72 W/kg. Also, the variation in reflection coefficient helps to detect the tumor of the same composition but having different locations and having different sizes inside breast phantom. The principal component analysis is done to change the multi-variation in reflection coefficients data value to a single point value for better analysis.

A Realistic Breast Phantom Proposal for 3D Image Reconstruction in Digital Breast Tomosynthesis.

Objectives: Iterative (eg, simultaneous algebraic reconstruction technique [SART]) and analytical (eg, filtered back projection [FBP]) image reconstruction techniques have been suggested to provide adequate three-dimensional (3D) images of the breast for capturing microcalcifications in digital breast tomosynthesis (DBT). To decide on the reconstruction method in clinical DBT, it must first be tested in a simulation resembling the real clinical environment. The purpose of this study is to introduce a 3D realistic breast phantom for determining the reconstruction method in clinical applications. Methods: We designed a 3D realistic breast phantom with varying dimensions (643-5123) mimicking some structures of a real breast such as milk ducts, lobules, and ribs using TomoPhantom software. We generated microcalcifications, which mimic cancerous cells, with a separate MATLAB code and embedded them into the phantom for testing and benchmark studies in DBT. To validate the characterization of the phantom, we tested the distinguishability of microcalcifications by performing 3D image reconstruction methods (SART and FBP) using Laboratory of Computer Vision (LAVI) open-source reconstruction toolbox. Results: The creation times of the proposed realistic breast phantom were seconds of 2.5916, 8.4626, 57.6858, and 472.1734 for 643, 1283, 2563, and 5123, respectively. We presented reconstructed images and quantitative results of the phantom for SART (1-2-4-8 iterations) and FBP, with 11 to 23 projections. We determined qualitatively and quantitatively that SART (2-4 iter.) yields better results than FBP. For example, for 23 projections, the contrast-to-noise ratio (CNR) values of SART (2 iter.) and FBP were 2.871 and 0.497, respectively. Conclusions: We created a computationally efficient realistic breast phantom that is eligible for reconstruction and includes anatomical structures and microcalcifications, successfully. By proposing this breast phantom, we provided the opportunity to test which reconstruction methods can be used in clinical applications vary according to various parameters such as the No. of iterations and projections in DBT.

3-D Stochastic Numerical Breast Phantoms for Enabling Virtual Imaging Trials of Ultrasound Computed Tomography.

Ultrasound computed tomography (USCT) is an emerging imaging modality for breast imaging that can produce quantitative images that depict the acoustic properties of tissues. Computer-simulation studies, also known as virtual imaging trials, provide researchers with an economical and convenient route to systematically explore imaging system designs and image reconstruction methods. When simulating an imaging technology intended for clinical use, it is essential to employ realistic numerical phantoms that can facilitate the objective, or task-based, assessment of image quality (IQ). Moreover, when computing objective IQ measures, an ensemble of such phantoms should be employed, which displays the variability in anatomy and object properties that are representative of the to-be-imaged patient cohort. Such stochastic phantoms for clinically relevant applications of USCT are currently lacking. In this work, a methodology for producing realistic 3-D numerical breast phantoms for enabling clinically relevant computer-simulationstudies of USCT breast imaging is presented. By extending and adapting an existing stochastic 3-D breast phantom for use with USCT, methods for creating ensembles of numerical acoustic breast phantoms are established. These breast phantoms will possess clinically relevant variations in breast size, composition, acoustic properties, tumor locations, and tissue textures. To demonstrate the use of the phantoms in virtual USCT studies, two brief case studies are presented, which addresses the development and assessment of image reconstruction procedures. Examples of breast phantoms produced by use of the proposed methods and a collection of 52 sets of simulated USCT measurement data have been made open source for use in image reconstruction development.

Tunable blood oxygenation in the vascular anatomy of a semi-anthropomorphic photoacoustic breast phantom.

.Significance: Recovering accurate oxygenation estimations in the breast with quantitative photoacoustic tomography (QPAT) is not straightforward. Accurate light fluence models are required, but the unknown ground truth of the breast makes it difficult to validate them. Phantoms are often used for the validation, but most reported phantoms have a simple architecture. Fluence models developed in these simplistic objects are not accurate for application on the complex tissues of the breast.Aim: We present a sophisticated breast phantom platform for photoacoustic (PA) and ultrasound (US) imaging in general, and specifically for QPAT. The breast phantom is semi-anthropomorphic in distribution of optical and acoustic properties and contains wall-less channels with blood.Approach: 3D printing approaches are used to develop the solid 3D breast phantom from custom polyvinyl chloride plastisol formulations and additives for replicating the tissue optical and acoustic properties. A flow circuit was developed to flush the channels with bovine blood with a controlled oxygen saturation level. To showcase the phantom’s functionality, PA measurements were performed on the phantom with two oxygenation levels. Image reconstructions with and without fluence compensation from Monte Carlo simulations were analyzed for the accuracy of oxygen saturation estimations.Results: We present design aspects of the phantom, demonstrate how it is developed, and present its breast-like appearance in PA and US imaging. The oxygen saturations were estimated in two regions of interest with and without using the fluence models. The fluence compensation positively influenced the estimations in all cases and confirmed that highly accurate fluence models are required to minimize estimation errors.Conclusions: This phantom allows studies to be performed in PA in carefully controlled laboratory settings to validate approaches to recover both qualitative and quantitative features sought after in in-vivo studies. We believe that testing with phantoms of this complexity can streamline the transition of new PA technologies from the laboratory to studies in the clinic.

Characterization and applicability of low-density materials for making 3D physical anthropomorphic breast phantoms

Test objects or phantoms are important tools for the optimization of dose and image quality in mammography. The main quality control protocols in mammography adopt homogeneous phantoms for image quality assessment, which generate images with unrealistic uniform background and do not consider the effect of breast anatomy on image quality. Realistic three-dimensional (3D) anthropomorphic phantoms with characteristic contrast of breast tissues are required to better evaluate clinical systems in terms of their intended diagnostic tasks. This work aims to characterize low-density materials by determining their linear attenuation coefficients, μ(E), and to evaluate their suitability as breast tissue–equivalent materials for printing 3D anthropomorphic breast phantoms. Incident and transmitted mammographic X-ray spectra through different material thicknesses were measured using a CdTe detector. Attenuation curves were derived for each photon energy, and the coefficients μ(E) were calculated between 10 and 20 keV for various materials. These coefficients were compared with data for breast tissues (glandular, adipose, skin, and blood) presented in the literature. Polymethyl methacrylate (PMMA) was used as the reference material to validate the methodology used in this work. The experimental μ(E) for PMMA agreed with the results of the literature, with an average relative difference of −0.44% and average relative uncertainty of ±3.70%. Among the analysed materials, 3D printing materials TangoBlackPlus™ and VeroClear™ (Stratasys, USA) presented the best glandular equivalency, with average percentage differences relative to the theoretical coefficients, μ(E), for glandular tissue of −0.36% and +1.85%, respectively. A urethane-based polymer (water simulant) was the material with the best adipose equivalency, showing an average relative difference in μ(E) of +3.39%. None of the studied materials was suitable to provide the photon attenuation equivalent to skin or blood. TangoBlackPlus™ and VeroClear™ presented similar attenuation to the glandular tissue when compared with results from reference data of ICRP 110. These materials can be suitable for 3D printing of glandular tissue in a breast phantom, while the urethane-based polymer might be used to fill the phantom as adipose tissue–equivalent material.

Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system.

PurposeTo validate Monte Carlo (MC)‐based breast dosimetry estimations using both a homogeneous and a 3D anthropomorphic breast phantom under polyenergetic irradiation for internal breast dosimetry purposes.MethodsExperimental measurements were performed with a clinical digital mammography system (Mammomat Inspiration, Siemens Healthcare), using the x‐ray spectrum selected by the automatic exposure control and a tube current‐exposure time product of 360 mAs. A homogeneous 50% glandular breast phantom and a 3D anthropomorphic breast phantom were used to investigate the dose at different depths (range 0–4 cm with 1 cm steps) for the homogeneous case and at a depth of 2.25 cm for the anthropomorphic case. Local dose deposition was measured using thermoluminescent dosimeters (TLD), metal oxide semiconductor field‐effect transistor dosimeters (MOSFET), and GafChromic™ films. A Geant4‐based MC simulation was modified to match the clinical experimental setup. Thirty sensitive volumes (3.2 × 3.2 × 0.38 mm3) on the axial‐phantom plane were included at each depth in the simulation to characterize the internal dose variation and compare it to the experimental TLD and MOSFET measurements. The experimental 2D dose maps obtained with the GafChromic™ films were compared to the simulated 2D dose distributions.ResultsDue to the energy dependence of the dosimeters and due to x‐ray beam hardening, dosimeters based on these three technologies have to be calibrated at each depth of the phantom. As expected, the dose was found to decrease with increasing phantom depth, with the reduction being ~93% after 4 cm for the homogeneous breast phantom. The 2D dose map showed nonuniformities in the dose distribution in the axial plane of the phantom. The mean combined standard uncertainty increased with phantom depth by up to 5.3% for TLD, 6.3% for MOSFET, and 9.6% for GafChromic™ film. In the case of a heterogeneous phantom, the dosimeters are able to detect local dose gradient variations. In particular, GafChromic™ film showed local dose variations of about 46% at the boundaries of two materials.ConclusionsResults showed a good agreement between experimental measurements (with TLD and MOSFET) and MC data for both homogeneous and anthropomorphic breast phantoms. Larger discrepancies are found when comparing the GafChromic™ dose values to the MC results due to the inherent less precise nature of the former.MC validations in a heterogeneous background at the level of local dose deposition and in absolute terms play a fundamental role in the development of an accurate method to estimate radiation dose. The potential introduction of a breast dosimetry model involving a nonhomogeneous glandular/adipose tissue composition makes the validation of internal dose distributions estimates crucial.

Restoration of low-dose digital breast tomosynthesis

In breast cancer screening, the radiation dose must be kept to the minimum necessary to achieve the desired diagnostic objective, thus minimizing risks associated with cancer induction. However, decreasing the radiation dose also degrades the image quality. In this work we restore digital breast tomosynthesis (DBT) projections acquired at low radiation doses with the goal of achieving a quality comparable to that obtained from current standard full-dose imaging protocols. A multiframe denoising algorithm was applied to low-dose projections, which are filtered jointly. Furthermore, a weighted average was used to inject a varying portion of the noisy signal back into the denoised one, in order to attain a signal-to-noise ratio comparable to that of standard full-dose projections. The entire restoration framework leverages a signal-dependent noise model with quantum gain which varies both upon the projection angle and on the pixel position. A clinical DBT system and a 3D anthropomorphic breast phantom were used to validate the proposed method, both on DBT projections and slices from the 3D reconstructed volume. The framework is shown to attain the standard full-dose image quality from data acquired at 50% lower radiation dose, whereas progressive loss of relevant details compromises the image quality if the dosage is further decreased.

X-ray-induced acoustic computed tomography for 3D breast imaging: A simulation study.

The objective of this study is to demonstrate the feasibility of x-ray-induced acoustic computed tomography (XACT) for early breast un-palpable microcalcification (μCa) detection in three dimensions (3D). The proposed technique provides the true 3D imaging for breast volume which overcomes the disadvantage of the tissue superposition in mammography. A 3D breast digital phantom was rendered from two-dimensional (2D) breast CT slices. Three different tissue types, including the skin, adipose tissue, and glandular tissue, were labeled in the 3D breast phantom. μCas were manually embedded in different locations inside the breast phantom. For each tissue type, the initial pressure rise caused by the x-ray-induced acoustic (XA) effect was calculated according to its themoacoustic properties. The XA wave's propagation from the point of generation and its detection by ultrasound detector array were simulated by Matlab K-Wave toolbox. The 3D breast XACT volume with μCa was acquired without tissue superposition, and the system was characterized by μCas placed at different locations. The simulation results illustrated that the proposed breast XACT system has the ability to show the μCa cluster in 3D without any tissue superposition. Meanwhile, μCa as small as 100 μm in size can be detected with high imaging contrast, high signal to noise ratio (SNR), and high contrast to noise ratio (CNR). The dose required by the proposed XACT configuration was calculated to be 0.4 mGy for a 4.5 cm-thick compressed breast. This is one-tenth of the dose level of a typical two-view mammography for a breast with the same compression thickness. The initial exploration for the feasibility of 3D breast XACT has been conducted in this study. The system feasibility and characterization were illustrated through a 3D breast phantom and simulation works. The 3D breast XACT with the proposed system configuration has great potential to be applied as a low-dose screening and diagnostic technique for early un-palpable lesion in the breast.

Performance of leading artifact removal algorithms assessed across microwave breast imaging prototype scan configurations

Microwave imaging is a promising imaging modality for the detection of early-stage breast cancer. One of the most important signal processing components of microwave radar-based breast imaging is early-stage artifact removal. Several artifact removal algorithms have been reported in the literature. However, the neighbourhood-based skin subtraction and hybrid artifact removal algorithms have shown particularly promising results in different realistic 3D breast phantoms. For the first time in this paper, both algorithms have been evaluated and compared using the scan approaches of the most common microwave breast imaging prototype systems. The tests include 3D numerical as well as experimental breast phantoms scanned with hemispherical, cylindrical and adaptive scanning patterns. The efficacy of both algorithms has been evaluated across a range of appropriate performance metrics.

Phase-contrast Digital Breast Tomosynthesis vs phase-contrast breast CT: An image quality phantom study with synchrotron radiation

Introduction Digital Mammography is a fundamental technique in breast cancer diagnosis. DM returns a two-dimensional representation of a three-dimensional object. Therefore, tissues belonging to different planes are all projected on the same X-ray image plane. Digital Breast Tomosynthesis (DBT) and Breast Computed Tomography (BCT) are two forms of 3D X-ray breast imaging for diagnostic exam developed to overcome this limitation. Recently, it has been shown that for the generation of the radiographic contrast it is possible to exploit also the information related to the wave phase shift introduced in the propagation of X-rays in matter. Purpose To compare image quality in monochromatic DBT and BCT scans with propagation based phase contrast imaging of a 3D breast phantom. Materials and methods The CIRS Model 020 BR3D is used to evaluate the image quality in the two modalities. The standard package consists of 6 slabs of thickness of 1 cm, each slice is produced by tissue equivalent materials in an approximate 50/50 ratio by weight. The central slab of the stack contains assortments of simulated microcalcifications, fibers and masses. The experiment was conducted on the biomedical beamline ID 17 at the European Synchrotron Radiation Facility. The comparison will be made in terms of noise, contrast, CNR, SNR and spatial resolution, for simulated masses and microcalcifications. Results First measurements show slightly higher values for CNR and C for masses in CT images than in DBT images. Conclusion The image quality in DBT and BCT monochromatic images of a 3D breast phantom was evaluated.

Improvement of image performance in digital breast tomosynthesis (DBT) by incorporating a compressed-sensing (CS)-based deblurring scheme

In this work, we investigated a compressed-sensing (CS)-based deblurring scheme incorporated with the total-variation (TV) regularization penalty for image deblurring of high accuracy and adopted it into the image reconstruction in conventional digital breast tomosynthesis (DBT). We implemented the proposed algorithm and performed a systematic simulation to demonstrate its viability for improving the image performance in DBT as well as two-dimensional (2D) mammography. In the simulation, blurred noisy projection images of a 3D numerical breast phantom were generated by convolving their original (or exact) version by a designed 2D Gaussian filter kernel (standard deviation=2 in pixel unit, kernel size=11×11), followed by adding Gaussian noise (mean=0, variance=0.05), and deblurred by using the algorithm before performing the DBT reconstruction procedure. Here the projection images were taken with a half tomographic angle of θ=20° and an angle step of Δθ=2°. We investigated the image performance of the reconstructed DBT images quantitatively in terms of the modulation and the slice-sensitive profile (SSP).

TH-AB-209-12: Tissue Equivalent Phantom with Excised Human Tissue for Assessing Clinical Capabilities of Coherent Scatter Imaging Applications

Purpose: Previously we reported the development of anthropomorphic tissue-equivalent scatter phantoms of the human breast. Here we present the first results from the scatter imaging of the tissue equivalent breast phantoms for breast cancer diagnosis. Methods: A breast phantom was designed to assess the capability of coded aperture coherent x-ray scatter imaging to classify different types of breast tissue (adipose, fibroglandular, tumor). The phantom geometry was obtained from a prone breast geometry scanned on a dedicated breast CT system. The phantom was 3D printed using the segmented DICOM breast CT data. The 3D breast phantom was filled with lard (as a surrogate for adipose tissue) and scanned in different geometries alongside excised human breast tissues (obtained from lumpectomy and mastectomy procedures). The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor (i.e., momentum transfer (q) spectrum) of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: Our scatter imaging system was able to define the location and composition of the various materials and tissues within the phantom. Cancerous breast tissue was detected and classified through automated spectral matching and an 86% correlation threshold. The total scan time for the sample was approximately 10 minutes and approaches workflow times for clinical use in intra-operative or other diagnostic tasks. Conclusion: This work demonstrates the first results from an anthropomorphic tissue equivalent scatter phantom to characterize a coherent scatter imaging system. The functionality of the system shows promise in applications such as intra-operative margin detection or virtual biopsy in the diagnosis of breast cancer. Future work includes using additional patient-derived tissues (e.g., human fat), and modeling additional organs (e.g., lung).

SU‐F‐I‐14: 3D Breast Digital Phantom for XACT Imaging

Purpose:The X‐ray induced acoustic computed tomography (XACT) is a new imaging modality which combines X‐ray contrast and high ultrasonic resolution in a single modality. Using XACT in breast imaging, a 3D breast volume can be imaged by only one pulsed X‐ray radiation, which could dramatically reduce the imaging dose for patients undergoing breast cancer screening and diagnosis. A 3D digital phantom that contains both X‐ray properties and acoustic properties of different tissue types is indeed needed for developing and optimizing the XACT system. The purpose of this study is to offer a realistic breast digital phantom as a valuable tool for improving breast XACT imaging techniques and potentially leading to better diagnostic outcomes.Methods:A series of breast CT images along the coronal plane from a patient who has breast calcifications are used as the source images. A HU value based segmentation algorithm is employed to identify breast tissues in five categories, namely the skin tissue, fat tissue, glandular tissue, chest bone and calcifications. For each pixel, the dose related parameters, such as material components and density, and acoustic related parameters, such as frequency‐dependent acoustic attenuation coefficient and bandwidth, are assigned based on tissue types. Meanwhile, other parameters which are used in sound propagation, including the sound speed, thermal expansion coefficient, and heat capacity are also assigned to each tissue.Results:A series of 2D tissue type image is acquired first and the 3D digital breast phantom is obtained by using commercial 3D reconstruction software. When giving specific settings including dose depositions and ultrasound center frequency, the X‐ray induced initial pressure rise can be calculated accordingly.Conclusion:The proposed 3D breast digital phantom represents a realistic breast anatomic structure and provides a valuable tool for developing and evaluating the system performance for XACT.

An Efficient Image Reconstruction Method for Breast Cancer Detection Using an Ultra-Wideband Microwave Imaging System

ABSTRACTMicrowave breast imaging uses backscattered radar signals to identify cancerous tissue within the breast. It is a non-invasive technique and uses non-ionizing radiation; it is currently a potential alternative for classical techniques. This article presents an efficient image reconstruction method for breast cancer detection using an ultra-wideband microwave imaging system. This method consists of applying the improved version of the delay-and-sum algorithm and post-processing the resultant images. For that, we have used a numerical 3D breast phantom in CST software simulation tool (CST Inc., 2014). The breast was illuminated with ultra-wideband (UWB) pulse from a number of antenna locations, and then collected reflections were synthetically focused to create an energy map of the breast. A new algorithm is also introduced that post-processes the resulting images obtained through different configurations of acquisition point positions. This post-process allows a much clearer image to be obtained with less interference. In the constructed and post-processed image, the presence and location of single and double breast cancer tumors of 2 mm in diameter can clearly be identified.

Monte-Carlo simulation of a slot-scanning digital mammography system for tomosynthesis.

Digital breast tomosynthesis (DBT) reconstructs planar slices of the breast based on two-dimensional angular projections. Early studies and clinical trials show that DBT is an improvement over full field digital mammography (FFDM) because it provides the radiologist with better image quality and more information. This paper presents a simulation system to model the performance of a slot-scanning FFDM and DBT system. A tissue-equivalent three dimensional (3D) breast phantom was constructed, validated for slot-scanning digital mammography and used in simulating digital breast tomosynthesis. The simulation system was validated by comparing images acquired with a slot-scanning mammography machine with simulated phantom images, using the edge-test method and image quality metrics modulation transfer function (MTF), noise power spectrum (NPS) and detective quantum efficiency (DQE). Different two-dimensional (2D) projections of the 3D phantom were simulated and the phantom was reconstructed using filtered backprojection. Image quality metrics showed equivalence between simulated and real images. The simulation tool is suitable for slot-scanning FFDM and DBT and may be used for the design and comparison of mammography systems.