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X-ray scatter correction in breast tomosynthesis with a precomputed scatter map library.

ABSTRACT: 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.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.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).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.

SUBMITTER: Feng SS

PROVIDER: S-EPMC3978288 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

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Project description:To develop a software-based scatter correction method for digital breast tomosynthesis (DBT) imaging and investigate its impact on the image quality of tomosynthesis reconstructions of both phantoms and patients.A Monte Carlo (MC) simulation of x-ray scatter, with geometry matching that of the cranio-caudal (CC) view of a DBT clinical prototype, was developed using the Geant4 toolkit and used to generate maps of the scatter-to-primary ratio (SPR) of a number of homogeneous standard-shaped breasts of varying sizes. Dimension-matched SPR maps were then deformed and registered to DBT acquisition projections, allowing for the estimation of the primary x-ray signal acquired by the imaging system. Noise filtering of the estimated projections was then performed to reduce the impact of the quantum noise of the x-ray scatter. Three dimensional (3D) reconstruction was then performed using the maximum likelihood-expectation maximization (MLEM) method. This process was tested on acquisitions of a heterogeneous 50∕50 adipose∕glandular tomosynthesis phantom with embedded masses, fibers, and microcalcifications and on acquisitions of patients. The image quality of the reconstructions of the scatter-corrected and uncorrected projections was analyzed by studying the signal-difference-to-noise ratio (SDNR), the integral of the signal in each mass lesion (integrated mass signal, IMS), and the modulation transfer function (MTF).The reconstructions of the scatter-corrected projections demonstrated superior image quality. The SDNR of masses embedded in a 5 cm thick tomosynthesis phantom improved 60%-66%, while the SDNR of the smallest mass in an 8 cm thick phantom improved by 59% (p < 0.01). The IMS of the masses in the 5 cm thick phantom also improved by 15%-29%, while the IMS of the masses in the 8 cm thick phantom improved by 26%-62% (p < 0.01). Some embedded microcalcifications in the tomosynthesis phantoms were visible only in the scatter-corrected reconstructions. The visibility of the findings in two patient images was also improved by the application of the scatter correction algorithm. The MTF of the images did not change after application of the scatter correction algorithm, indicating that spatial resolution was not adversely affected.Our software-based scatter correction algorithm exhibits great potential in improving the image quality of DBT acquisitions of both phantoms and patients. The proposed algorithm does not require a time-consuming MC simulation for each specific case to be corrected, making it applicable in the clinical realm.

Project description:To improve image quality and accuracy in dedicated breast computed tomography (BCT) by removing the x-ray scatter signal included in the BCT projections.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.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.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.

Project description:To analyze the frequency domain characteristics of the signal in mammography images and breast tomosynthesis projections with patient tissue texture due to detected scattered x-rays.Acquisitions of x-ray projection images of 19 different patient breasts were simulated using previously acquired volumetric patient images. Acquisition of these images was performed with a dedicated breast CT prototype system, and the images were classified into voxels representing skin, adipose, and glandular tissue with a previously validated automated algorithm. The classified three dimensional images then underwent simulated mechanical compression representing that which is performed during acquisition of mammography and breast tomosynthesis images. The acquisition of projection images of each patient breast was simulated using Monte Carlo methods with each simulation resulting in two images: one of the primary (non-scattered) signal and one of the scatter signal. To analyze the scatter signal for both mammography and breast tomosynthesis, two projections images of each patient breast were simulated, one with the x-ray source positioned at 0° (mammography and central tomosynthesis projection) and at 30° (wide tomosynthesis projection). The noise power spectra (NPS) for both the scatter signal alone and the total signal (primary + scatter) for all images were obtained and the combined results of all patients analyzed. The total NPS was fit to the expected power-law relationship NPS(f) = k/f β and the results were compared with those previously published on the power spectrum characteristics of mammographic texture. The scatter signal alone was analyzed qualitatively and a power-law fit was also performed.The mammography and tomosynthesis projections of three patient breasts were too small to analyze, so a total of 16 patient breasts were analyzed. The values of β for the total signal of the 0° projections agreed well with previously published results. As expected, the scatter power spectrum reflected a fast drop-off with increasing spatial frequency, with a reduction of four orders of magnitude by 0.1 lp/mm. The β values for the scatter signal were 6.14 and 6.39 for the 0° and 30° projections, respectively.Although the low-frequency characteristics of scatter in mammography and breast tomosynthesis were known, a quantitative analysis of the frequency domain characteristics of this signal was needed in order to optimize previously proposed software-based x-ray scatter reduction algorithms for these imaging modalities.

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X-ray scatter correction in breast tomosynthesis with a precomputed scatter map library.

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