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

PURPOSE 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. METHODS 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. RESULTS 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. CONCLUSIONS A new algorithm for computer simulation of breast anatomy has been proposed that improved the realism of the anthropomorphic software breast phantom.

[1]  W. Paul Segars,et al.  Computerized 3D breast phantom with enhanced high-resolution detail , 2009, Medical Imaging.

[2]  Andrew D. A. Maidment,et al.  Comparison of 3D and 2D breast density estimation from synthetic ultrasound tomography images and digital mammograms of anthropomorphic software breast phantoms , 2011, Medical Imaging.

[3]  Tatjana Jevremovic,et al.  Numerical assessment of radiation binary targeted therapy for HER-2 positive breast cancers: advanced calculations and radiation dosimetry , 2007, Physics in medicine and biology.

[4]  Tatjana Jevremovic,et al.  Radiation binary targeted therapy for HER-2 positive breast cancers: assumptions, theoretical assessment and future directions , 2006, Physics in medicine and biology.

[5]  Dragana Brzakovic,et al.  Mammogram synthesis using a three-dimensional simulation. III. Modeling and evaluation of the breast ductal network. , 2003, Medical physics.

[6]  Andrew D. A. Maidment,et al.  Digital Breast Tomosynthesis Parenchymal Texture Analysis for Breast Cancer Risk Estimation: A Preliminary Study , 2008, Digital Mammography / IWDM.

[7]  Predrag R. Bakic,et al.  Simulation of digital mammogram acquisition , 1999, Medical Imaging.

[8]  M. Rominger,et al.  Predictive value of galactographic patterns for benign and malignant neoplasms of the breast in patients with nipple discharge. , 2000, The British journal of radiology.

[9]  Tatjana Jevremovic,et al.  Monte Carlo assessment of boron neutron capture therapy for the treatment of breast cancer , 2005 .

[10]  Xavier Gérard Viennot,et al.  Combinatorial analysis of ramified patterns and computer imagery of trees , 1989, SIGGRAPH.

[11]  J. Michael O'Connor,et al.  Comparison of Two Methods to Develop Breast Models for Simulation of Breast Tomosynthesis and CT , 2008, Digital Mammography / IWDM.

[12]  Christoph Hoeschen,et al.  Evaluation of a novel method of noise reduction using computer-simulated mammograms. , 2005, Radiation protection dosimetry.

[13]  R P Velthuizen,et al.  On the statistical nature of mammograms. , 1999, Medical physics.

[14]  Andrew D. A. Maidment,et al.  Analysis of Geometric Accuracy in Digital Breast Tomosynthesis Reconstruction , 2010, Digital Mammography / IWDM.

[15]  Ann-Katherine Carton,et al.  Development of a 3D high-resolution physical anthropomorphic breast phantom , 2010, Medical Imaging.

[16]  Lei Xing,et al.  WE‐E‐204B‐01: Development of an X‐Ray/Optical Luminescence Imager for Improved X‐Ray Contrast Sensitivity , 2010 .

[17]  S Suryanarayanan,et al.  Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: application for mammography. , 2010, Medical physics.

[18]  Robert M. Nishikawa,et al.  TH‐D‐201B‐08: An Anthropomorphic Software Breast Phantom for Tomosynthesis Simulation: Power Spectrum Analysis of Phantom Reconstructions , 2010 .

[19]  Christoph Hoeschen,et al.  Testing a wavelet based noise reduction method using computer-simulated mammograms , 2005, SPIE Medical Imaging.

[20]  Andrew D. A. Maidment,et al.  Evaluation of Breast Ductal Networks Using Ramification Matrices , 2003 .

[21]  Arthur E. Burgess,et al.  Mammographic structure: data preparation and spatial statistics analysis , 1999, Medical Imaging.

[22]  Andrew D. A. Maidment,et al.  Breast dosimetry using high-resolution voxel phantoms. , 2005, Radiation protection dosimetry.

[23]  J. S. Laughlin,et al.  Absorbed radiation dose in mammography. , 1979, Radiology.

[24]  M E Read,et al.  Breast skin thickness: normal range and causes of thickening shown on film-screen mammography. , 1984, Journal of the Canadian Association of Radiologists.

[25]  Spencer Gunn,et al.  Introducing DeBRa: a detailed breast model for radiological studies. , 2009, Physics in medicine and biology.

[26]  P. C. Johns,et al.  X-ray characterisation of normal and neoplastic breast tissues. , 1987, Physics in medicine and biology.

[27]  H M Jensen,et al.  An atlas of subgross pathology of the human breast with special reference to possible precancerous lesions. , 1975, Journal of the National Cancer Institute.

[28]  Ann-Katherine Carton,et al.  Breast percent density: estimation on digital mammograms and central tomosynthesis projections. , 2009, Radiology.

[29]  Ingrid Reiser,et al.  Comparison of power spectra for tomosynthesis projections and reconstructed images. , 2009, Medical physics.

[30]  Andrew D. A. Maidment,et al.  Evaluating the Effect of Tomosynthesis Acquisition Parameters on Image Texture: A Study Based on an Anthropomorphic Breast Tissue Software Model , 2008, Digital Mammography / IWDM.

[31]  J. Wolfe.  Risk for breast cancer development determined by mammographic parenchymal pattern , 1976, Cancer.

[32]  Robert M. Nishikawa,et al.  An Anthropomorphic Software Breast Phantom for Tomosynthesis Simulation: Power Spectrum Analysis of Phantom Projections , 2010, Digital Mammography / IWDM.

[33]  Ann-Katherine Carton,et al.  Development of a physical 3D anthropomorphic breast phantom. , 2011, Medical physics.

[34]  Andrew D. A. Maidment,et al.  Classification of galactograms with ramification matrices: preliminary results. , 2003, Academic radiology.

[35]  Andrew D. A. Maidment,et al.  2D-to-3D X-Ray Breast Image Registration , 2006, WBIR.

[36]  Predrag R. Bakic,et al.  An approach to using a generalized breast model to segment digital mammograms , 1998, Proceedings. 11th IEEE Symposium on Computer-Based Medical Systems (Cat. No.98CB36237).

[37]  Andrew D. A. Maidment,et al.  Mammogram synthesis using a 3D simulation. I. Breast tissue model and image acquisition simulation. , 2002, Medical physics.

[38]  E. W. Shrigley.  Medical Physics , 1944, British medical journal.

[39]  Ann-Katherine Carton,et al.  Validation and optimization of digital breast tomosynthesis reconstruction using an anthropomorphic software breast phantom , 2010, Medical Imaging.

[40]  Helena Jernström,et al.  Of cup and bra size: Reply to a prospective study of breast size and premenopausal breast cancer incidence , 2006, International journal of cancer.

[41]  J. H. Hubbell,et al.  Tables of X-Ray Mass Attenuation Coefficients and Mass Energy-Absorption Coefficients 1 keV to 20 MeV for Elements Z = 1 to 92 and 48 Additional Substances of Dosimetric Interest , 1995 .

[42]  Ann-Katherine Carton,et al.  Simulation of tomosynthesis images based on an anthropomorphic software breast tissue phantom , 2008, SPIE Medical Imaging.

[43]  David Ingram,et al.  Simulated Mammography Using Synthetic 3D Breasts , 1998, Digital Mammography / IWDM.

[44]  Kristina Bliznakova,et al.  A novel simulation algorithm for soft tissue compression , 2007, Medical & Biological Engineering & Computing.

[45]  J S Spratt,et al.  Anatomy of the breast. , 1979, Major problems in clinical surgery.

[46]  John M Boone,et al.  Methodology for generating a 3D computerized breast phantom from empirical data. , 2009, Medical physics.

[47]  Andrew D. A. Maidment,et al.  Mammogram synthesis using a 3D simulation. II. Evaluation of synthetic mammogram texture. , 2002, Medical physics.

[48]  K Bliznakova,et al.  A three-dimensional breast software phantom for mammography simulation. , 2003, Physics in medicine and biology.

[49]  Andrew D. A. Maidment,et al.  Mammogram registration: a phantom-based evaluation of compressed Breast Thickness variation effects , 2006, IEEE Transactions on Medical Imaging.

[50]  Andrew D. A. Maidment,et al.  Registration of Mammograms and Breast Tomosynthesis Images , 2006, Digital Mammography / IWDM.

[51]  C Abbey,et al.  Statistical texture synthesis of mammographic images with super-blob lumpy backgrounds. , 1999, Optics express.

[52]  Predrag R. Bakic,et al.  Anatomic Segmentation of Mammograms Via Breast Model , 1998, Digital Mammography / IWDM.

[53]  Pierre-Edouard Sottas,et al.  Mammographic texture synthesis: second-generation clustered lumpy backgrounds using a genetic algorithm. , 2008, Optics express.

[54]  Andrew D. A. Maidment,et al.  Non-rigid Registration of Mammograms Obtained with Variable Breast Compression: A Phantom Study , 2003, WBIR.

[55]  M. Yaffe,et al.  American Cancer Society Guidelines for Breast Screening with MRI as an Adjunct to Mammography , 2007, CA: a cancer journal for clinicians.

[56]  W. Kaiser,et al.  Model-based registration of X-ray mammograms and MR images of the female breast , 2006, IEEE Transactions on Nuclear Science.

[57]  N. Erdoğan,et al.  Effect of age, breast size, menopausal and hormonal status on mammographic skin thickness , 2003, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

[58]  M. Hou,et al.  The diagnostic value of galactography in patients with nipple discharge. , 2001, Clinical imaging.

[59]  Christoph Hoeschen,et al.  A high-resolution voxel phantom of the breast for dose calculations in mammography. , 2005, Radiation protection dosimetry.

[60]  Andrew D. A. Maidment,et al.  Computer simulation of X-ray mammography using high resolution voxel phantoms , 2003 .