Breast Anatomy Simulation Research Articles

MO-FG-209-03: Simulation of Breast Anatomy at the Cellular Scale

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: 1.Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; 2.Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; 3.Summarize the state of the science in optimized integration of modules in the simulated imaging chain; 4.Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants

MO-FG-209-01: Introduction

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: 1.Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; 2.Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; 3.Summarize the state of the science in optimized integration of modules in the simulated imaging chain; 4.Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants

MO-FG-209-00: Recent Advances in Virtual Tools for Validation of 3D/4D Breast Imaging Systems (TG234)

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: 1.Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; 2.Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; 3.Summarize the state of the science in optimized integration of modules in the simulated imaging chain; 4.Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants

MO-FG-209-02: Development of a Virtual Breast Phantom From a Multi-Modality Perspective

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: 1.Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; 2.Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; 3.Summarize the state of the science in optimized integration of modules in the simulated imaging chain; 4.Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants

MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: 1. Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; 2. Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; 3. Summarize the state of the science in optimized integration of modules in the simulated imaging chain; 4. Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants

MO-FG-209-04: DBT Applications of Feature-Adaptive Visual-Search Model Oberver

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: 1.Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; 2.Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; 3.Summarize the state of the science in optimized integration of modules in the simulated imaging chain; 4.Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants

Description and characterization of a novel method for partial volume simulation in software breast phantoms.

A modification to our previous simulation of breast anatomy is proposed to improve the quality of simulated x-ray projections images. The image quality is affected by the voxel size of the simulation. Large voxels can cause notable spatial quantization artifacts; small voxels extend the generation time and increase the memory requirements. An improvement in image quality is achievable without reducing voxel size by the simulation of partial volume averaging in which voxels containing more than one simulated tissue type are allowed. The linear x-ray attenuation coefficient of voxels is, thus, the sum of the linear attenuation coefficients weighted by the voxel subvolume occupied by each tissue type. A local planar approximation of the boundary surface is employed. In the two-material case, the partial volume in each voxel is computed by decomposition into up to four simple geometric shapes. In the three-material case, by application of the Gauss-Ostrogradsky theorem, the 3D partial volume problem is converted into one of a few simpler 2D surface area problems. We illustrate the benefits of the proposed methodology on simulated x-ray projections. An efficient encoding scheme is proposed for the type and proportion of simulated tissues in each voxel. Monte Carlo simulation was used to evaluate the quantitative error of our approximation algorithms.

MO‐A‐141‐02: Session In Memory of Fearghus O't Foghludha – Virtual Tools for Validation of X‐Ray Breast Imaging Systems

Given the large number of design parameters available to an x‐ray imaging system innovator (x‐ray spectrum, number of projection angles, angular range, dose and reconstruction algorithm, to name a few), simulation methods offer significant advantages over clinical studies for evaluation of the alternatives in terms of reproducibility, reduced radiation exposures of patients and volunteers, a known reference standard, and the capability for studying patient and disease subpopulations through appropriate choice of breast and patient model parameters. For these reasons, the emergent use of Virtual Clinical Trials for preclinical assessment of x‐ray breast imaging methods has introduced a demand to optimize protocols for simulation studies. The protocols should comprise of specifications for breast phantoms, the simulated data representation, methods for incorporating phantoms into a model for the imaging process, and appropriate statistical assessment methods applied to the resulting simulated images. This symposium explores simulation methods for evaluation of novel x‐ray breast imaging systems — the subject of recently established AAPM taskgroup TG234. The focus is on the various approaches of developing software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems along with computational models for the x‐ray image formation process. The symposium will review and discuss the state of the science of Virtual Clinical Trials for novel x‐ray breast imaging systems. Presentations will discuss real‐time simulation of breast anatomy, simulation of small‐scale tissue properties, generation of breast phantoms based upon clinical datasets, and task‐based evaluation of x‐ray breast imaging systems using software phantoms.Learning Objectives:1. Review current approaches for simulation of breast phantoms for x‐ray imaging, along with their strengths and limitations;2. Understand the validation of software phantoms using object and image statistics;3. Review methods for statistical and task‐based image quality assessment and discuss their applications in x‐ray breast imaging systems;4. Illustrate methods for performing virtual clinical trials of emerging 3D x‐ray breast imaging systems.P.R.B. is a PI on NSF grant IIS0916690 and co‐investigator on NIH R01 CA154444, NIH R21 CA155906‐01A1, and DoD HBCU PTA BC083639, and is also involved in research collaboration with Barco, Inc. and Hologic, Inc.N.K. is funded by NIH R01 CA134658 and R01 CA11243, and is involved in resaerch collaboration with Siement Medical Solution.

Optimized generation of high resolution breast anthropomorphic software phantoms

The authors present an efficient method for generating anthropomorphic software breast phantoms with high spatial resolution. Employing the same region growing principles as in their previous algorithm for breast anatomy simulation, the present method has been optimized for computational complexity to allow for fast generation of the large number of phantoms required in virtual clinical trials of breast imaging. The new breast anatomy simulation method performs a direct calculation of the Cooper's ligaments (i.e., the borders between simulated adipose compartments). The calculation corresponds to quadratic decision boundaries of a maximum a posteriori classifier. The method is multiscale due to the use of octree-based recursive partitioning of the phantom volume. The method also provides user-control of the thickness of the simulated Cooper's ligaments and skin. Using the proposed method, the authors have generated phantoms with voxel size in the range of (25-1000 μm)(3)∕voxel. The power regression of the simulation time as a function of the reciprocal voxel size yielded a log-log slope of 1.95 (compared to a slope of 4.53 of our previous region growing algorithm). A new algorithm for computer simulation of breast anatomy has been proposed that allows for fast generation of high resolution anthropomorphic software phantoms.

SU‐E‐I‐153: A Method for Fast Generation of High Resolution Software Breast Phantoms

Purpose: We have developed a new method for generating anthropomorphic software breast phantoms. The method allows for faster generation of phantoms with small voxel size, and provides better control of simulated anatomical structures. Methods: In this paper we compare the simulation time and quantization artifacts between our previous and the new method. Previously, our breast anatomy simulation was based upon a region growing algorithm. The new method preserves the concept of region growing and is optimized to allow for faster simulation. The new method includes improved thickness control of the simulated skin and Cooperˈs ligaments. For comparison, we generated phantoms simulating a 450 ml breast using both methods. The phantoms were generated with voxel sizes in the range of 25–1000 microns; we recorded the time needed for simulation. The simulation time as function of the voxel size was fitted using a power‐law regression; the regression exponents were compared between the two methods. We also performed a visual comparison of the phantoms generated with different voxel sizes. Results: For the simulated range of voxel sizes the new method yielded a regression exponent of 2.15, compared to 3.89 for the previous method. The new method is faster than the previous method for phantoms with voxels below 200 microns. Generating phantoms with small voxel size is of importance for reducing quantization artifacts in simulated images; commercial mammography systems have detector element pitch as small as 50 microns. The visual comparison of the phantoms generated at different voxel sizes confirmed the improved quality of simulation with smaller voxels, as reflected by reduced quantization artifacts. Conclusions: Our new breast anatomy simulation is substantially improved in terms of simulation time and the quality of the simulated images. This is especially important for the simulation of phantom images with various available detector resolutions.

MO-A-214-01: 3D Breast Models

Breast CT and breast tomosynthesis are being developed to overcome the principal limitation of mammography, namely the superposition of breast tissue. The normal structure of the breast can be considered a source of noise that limits the detectability of cancer and causes the appearance of patterns that mimic a cancer. It has been shown that anatomical noise is the dominant noise source in the detection of breast cancer in a mammogram. Ideally, 3D imaging should reduce this noise source so that the imaging task becomes x‐ray quantum limited. To develop and optimize these systems, a 3D breast model is essential because the limiting effects of normal breast anatomy need to be incorporated into calculations of detectability. Standard mammographic phantoms are not useful as a 3D breast model. In this symposium, 3 different approaches will be described: a full simulation of breast anatomy, developing models from imaging actual breast tissue, and a pure mathematical approach of using filtered random noise. A following discussion period will delve into advantages and disadvantages of the different approaches.

Development and characterization of an anthropomorphic breast software phantom based upon region-growing algorithm

We present a novel algorithm for computer simulation of breast anatomy for generation of anthropomorphic software breast phantoms. A realistic breast simulation is necessary for preclinical validation of volumetric imaging modalities. The anthropomorphic software breast phantom simulates the skin, regions of adipose and fibroglandular tissue, and the matrix of Cooper's ligaments and adipose compartments. The adipose compartments are simulated using a seeded region-growing algorithm; compartments are grown from a set of seed points with specific orientation and growing speed. The resulting adipose compartments vary in shape and size similar to real breasts; the adipose region has a compact coverage by adipose compartments of various sizes, while the fibroglandular region has fewer, more widely separated adipose compartments. Simulation parameters can be selected to cover the breadth of variations in breast anatomy observed clinically. When simulating breasts of the same glandularity with different numbers of adipose compartments, the average compartment volume was proportional to the phantom size and inversely proportional to the number of simulated compartments. The use of the software phantom in clinical image simulation is illustrated by synthetic digital breast tomosynthesis images of the phantom. The proposed phantom design was capable of simulating breasts of different size, glandularity, and adipose compartment distribution. The region-growing approach allowed us to simulate adipose compartments with various size and shape. Qualitatively, simulated x-ray projections of the phantoms, generated using the proposed algorithm, have a more realistic appearance compared to previous versions of the phantom. A new algorithm for computer simulation of breast anatomy has been proposed that improved the realism of the anthropomorphic software breast phantom.