RESUMO
PURPOSE: To comprehensively characterize the dosimetric properties of a clinical digital breast tomosynthesis (DBT) system for the acquisition of mammographic and tomosynthesis images. MATERIALS AND METHODS: Compressible water-oil mixture phantoms were created and imaged by using the automatic exposure control (AEC) of the Selenia Dimensions system (Hologic, Bedford, Mass) in both DBT and full-field digital mammography (FFDM) mode. Empirical measurements of the x-ray tube output were performed with a dosimeter to measure the air kerma for the range of tube current-exposure time product settings and to develop models of the automatically selected x-ray spectra. A Monte Carlo simulation of the system was developed and used in conjunction with the AEC-chosen settings and spectra models to compute and compare the mean glandular dose (MGD) resulting from both imaging modalities for breasts of varying sizes and glandular compositions. RESULTS: Acquisition of a single craniocaudal view resulted in an MGD ranging from 0.309 to 5.26 mGy in FFDM mode and from 0.657 to 3.52 mGy in DBT mode. For a breast with a compressed thickness of 5.0 cm and a 50% glandular fraction, a DBT acquisition resulted in an only 8% higher MGD than an FFDM acquisition (1.30 and 1.20 mGy, respectively). For a breast with a compressed thickness of 6.0 cm and a 14.3% glandular fraction, a DBT acquisition resulted in an 83% higher MGD than an FFDM acquisition (2.12 and 1.16 mGy, respectively). CONCLUSION: For two-dimensional-three-dimensional fusion imaging with the Selenia Dimensions system, the MGD for a 5-cm-thick 50% glandular breast is 2.50 mGy, which is less than the Mammography Quality Standards Act limit for a two-view screening mammography study.
Assuntos
Imageamento Tridimensional/métodos , Mamografia/métodos , Intensificação de Imagem Radiográfica/métodos , Neoplasias da Mama/diagnóstico por imagem , Feminino , Humanos , Método de Monte Carlo , Imagens de Fantasmas , Doses de Radiação , RadiometriaRESUMO
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.
Assuntos
Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/diagnóstico , Radiometria/métodos , Tomografia Computadorizada por Raios X/métodos , Mama/patologia , Simulação por Computador , Feminino , Humanos , Mamografia/métodos , Modelos Estatísticos , Método de Monte Carlo , Radiação Ionizante , Reprodutibilidade dos Testes , Distribuição Tecidual , Raios XRESUMO
PURPOSE: To investigate the glandular dose magnitudes and characteristics resulting from image acquisition using a dedicated breast computed tomography (BCT) clinical prototype imaging system. METHODS: The x-ray spectrum and output characteristics of a BCT clinical prototype (Koning Corporation, West Henrietta, NY) were determined using empirical measurements, breast phantoms, and an established spectrum model. The geometry of the BCT system was replicated in a Monte Carlo-based computer simulation using the GEANT4 toolkit and was validated by comparing the simulated results for exposure distribution in a standard 16 cm CT head phantom with those empirically determined using a 10 cm CT pencil ionization chamber and dosimeter. The computer simulation was further validated by replicating the results of a previous BCT dosimetry study. Upon validation, the computer simulation was modified to include breasts of varying sizes and homogeneous compositions spanning those encountered clinically, and the normalized mean glandular dose resulting from BCT was determined. Using the system's measured exposure output determined automatically for breasts of different size and density, the mean glandular dose for these breasts was computed and compared to the glandular dose resulting from mammography. Finally, additional Monte Carlo simulations were performed to study how the glandular dose values vary within the breast tissue during acquisition with both this BCT prototype and a typical craniocaudal (CC) mammographic acquisition. RESULTS: This BCT prototype uses an x-ray spectrum with a first half-value layer of 1.39 mm Al and a mean x-ray energy of 30.3 keV. The normalized mean glandular dose for breasts of varying size and composition during BCT acquisition with this system ranges from 0.278 to 0.582 mGy/mGy air kerma with the reference air kerma measured in air at the center of rotation. Using the measured exposure outputs for the tube currents automatically selected by the system for the breasts of different sizes and densities, the mean glandular dose for a BCT acquisition with this prototype system varies from 5.6 to 17.5 mGy, with the value for a breast of mean size and composition being 17.06 mGy. The glandular dose throughout the breast tissue of this mean breast varies by up to +/- 50% of the mean value. During a typical CC view mammographic acquisition of an equivalent mean breast, which typically results in a mean glandular dose of 2.0-2.5 mGy, the glandular dose throughout the breast tissue varies from approximately 15% to approximately 400% of the mean value. CONCLUSIONS: Acquisition of a BCT image with the automated tube output settings for a mean breast with the Koning Corp. clinical prototype results in mean glandular dose values approximately equivalent to three to five two-view mammographic examinations for a similar breast. For all breast sizes and compositions studied, this glandular dose ratio between acquisition with this BCT prototype and two-view mammography ranges from 1.4 to 7.2. In mammography, portions of the mean-sized breast receive a considerably higher dose than the mean value for the whole breast. However, only a small portion of a breast undergoing mammography would receive a glandular dose similar to that from BCT.
Assuntos
Carga Corporal (Radioterapia) , Mamografia/métodos , Modelos Biológicos , Radiometria/métodos , Tomografia Computadorizada por Raios X/métodos , Simulação por Computador , Feminino , Humanos , Modelos Estatísticos , Imagens de Fantasmas , Projetos Piloto , Doses de RadiaçãoRESUMO
PURPOSE: To develop a set of accurate 2D models of compressed breasts undergoing mammography or breast tomosynthesis, based on objective analysis, to accurately characterize mammograms with few linearly independent parameters, and to generate novel clinically realistic paired cranio-caudal (CC) and medio-lateral oblique (MLO) views of the breast. METHODS: We seek to improve on an existing model of compressed breasts by overcoming detector size bias, removing the nipple and non-mammary tissue, pairing the CC and MLO views from a single breast, and incorporating the pectoralis major muscle contour into the model. The outer breast shapes in 931 paired CC and MLO mammograms were automatically detected with an in-house developed segmentation algorithm. From these shapes three generic models (CC-only, MLO-only, and joint CC/MLO) with linearly independent components were constructed via principal component analysis (PCA). The ability of the models to represent mammograms not used for PCA was tested via leave-one-out cross-validation, by measuring the average distance error (ADE). RESULTS: The individual models based on six components were found to depict breast shapes with accuracy (mean ADE-CC = 0.81 mm, ADE-MLO = 1.64 mm, ADE-Pectoralis = 1.61 mm), outperforming the joint CC/MLO model (P ≤ 0.001). The joint model based on 12 principal components contains 99.5% of the total variance of the data, and can be used to generate new clinically realistic paired CC and MLO breast shapes. This is achieved by generating random sets of 12 principal components, following the Gaussian distributions of the histograms of each component, which were obtained from the component values determined from the images in the mammography database used. CONCLUSION: Our joint CC/MLO model can successfully generate paired CC and MLO view shapes of the same simulated breast, while the individual models can be used to represent with high accuracy clinical acquired mammograms with a small set of parameters. This is the first step toward objective 3D compressed breast models, useful for dosimetry and scatter correction research, among other applications.
Assuntos
Neoplasias da Mama/diagnóstico por imagem , Mamografia , Análise de Componente Principal , Algoritmos , Mama , Feminino , Humanos , Músculos PeitoraisRESUMO
PURPOSE: To develop and evaluate the impact on lesion conspicuity of a software-based x-ray scatter correction algorithm for digital breast tomosynthesis (DBT) imaging into which a precomputed library of x-ray scatter maps is incorporated. METHODS: A previously developed model of compressed breast shapes undergoing mammography based on principal component analysis (PCA) was used to assemble 540 simulated breast volumes, of different shapes and sizes, undergoing DBT. A Monte Carlo (MC) simulation was used to generate the cranio-caudal (CC) view DBT x-ray scatter maps of these volumes, which were then assembled into a library. This library was incorporated into a previously developed software-based x-ray scatter correction, and the performance of this improved algorithm was evaluated with an observer study of 40 patient cases previously classified as BI-RADS® 4 or 5, evenly divided between mass and microcalcification cases. Observers were presented with both the original images and the scatter corrected (SC) images side by side and asked to indicate their preference, on a scale from -5 to +5, in terms of lesion conspicuity and quality of diagnostic features. Scores were normalized such that a negative score indicates a preference for the original images, and a positive score indicates a preference for the SC images. RESULTS: The scatter map library removes the time-intensive MC simulation from the application of the scatter correction algorithm. While only one in four observers preferred the SC DBT images as a whole (combined mean score = 0.169 ± 0.37, p > 0.39), all observers exhibited a preference for the SC images when the lesion examined was a mass (1.06 ± 0.45, p < 0.0001). When the lesion examined consisted of microcalcification clusters, the observers exhibited a preference for the uncorrected images (-0.725 ± 0.51, p < 0.009). CONCLUSIONS: The incorporation of the x-ray scatter map library into the scatter correction algorithm improves the efficiency of the algorithm. The observer study presented here is also the first test of the scatter correction algorithm with patient images and human observers, and demonstrates its potential to improve the clinical performance of DBT.
Assuntos
Neoplasias da Mama/diagnóstico por imagem , Mamografia/métodos , Intensificação de Imagem Radiográfica/métodos , Espalhamento de Radiação , Algoritmos , Mama/patologia , Feminino , Humanos , Método de Monte Carlo , Variações Dependentes do Observador , Análise de Componente Principal , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Reprodutibilidade dos Testes , Software , Raios XRESUMO
PURPOSE: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. METHODS: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). RESULTS: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six-component model was also used to generate CC and MLO view mammogram breast shapes, using the mean PCA parameter values of these distributions and randomly generated values based on the fitted Gaussian distributions, which resemble clinically encountered breasts. A spreadsheet with the data necessary to apply this model is provided as the supplementary material. CONCLUSIONS: Our PCA models of breast shapes in both mammographic views successfully reproduce analyzed breast shapes and generate new clinically relevant shapes. This work can aid in research applications which incorporate breast shape modeling, such as x-ray scatter correction, dosimetry, and image registration.