Low-contrast lesion detection in tomosynthetic breast imaging using a realistic breast phantom

Zhou, Lili; Oldan, Jorge; Fisher, Paul R.; Gindi, Gene

doi:10.1117/12.652343

Cited by 24 publications

(30 citation statements)

References 21 publications

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“…The number of angular projections has varied between 11 and 25 within a total angular span in the 30°-60°r ange. [6][7][8] While tomosynthesis optimization has also been approached in some recent studies, 5,[9][10][11][12] thus far, no framework has been developed for complete optimization of the acquisition scheme.…”

Section: Introductionmentioning

confidence: 99%

“…3 These factors also impact the obtain-able SNR as well as reconstruction artifacts inherent in tomosynthesis. 4,5 Low SNR and excessive artifacts may reduce the efficiency of tomosynthesis reading, possibly leading to lower accuracy. 6 Although critical, there has been no consensus on the acquisition parameters, such as the total dose delivered to the patient, the number of angular acquisitions, and the total angular span of those acquisitions, to achieve an optimum tomosynthesis protocol.…”

Section: Introductionmentioning

confidence: 99%

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Optimized image acquisition for breast tomosynthesis in projection and reconstruction space

Chawla

Baker

et al. 2009

Medical Physics

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Breast tomosynthesis has been an exciting new development in the field of breast imaging. While the diagnostic improvement via tomosynthesis is notable, the full potential of tomosynthesis has not yet been realized. This may be attributed to the dependency of the diagnostic quality of tomosynthesis on multiple variables, each of which needs to be optimized. Those include dose, number of angular projections, and the total angular span of those projections. In this study, the authors investigated the effects of these acquisition parameters on the overall diagnostic image quality of breast tomosynthesis in both the projection and reconstruction space. Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of each specimen were acquired at 6.2 times typical single-view clinical dose level. Images at lower dose levels were then simulated using a noise modification routine. Each projection image was supplemented with 84 simulated 3 mm 3D lesions embedded at the center of 84 nonoverlapping ROIs. The projection images were then reconstructed using a filtered backprojection algorithm at different combinations of acquisition parameters to investigate which of the many possible combinations maximizes the performance. Performance was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion detectability. The analysis was also performed without reconstruction by combining the model results from projection images using Bayesian decision fusion algorithm. The effect of acquisition parameters on projection images and reconstructed slices were then compared to derive an optimization rule for tomosynthesis. The results indicated that projection images yield comparable but higher performance than reconstructed images. Both modes, however, offered similar trends: Performance improved with an increase in the total acquisition dose level and the angular span. Using a constant dose level and angular span, the performance rolled off beyond a certain number of projections, indicating that simply increasing the number of projections in tomosynthesis may not necessarily improve its performance. The best performance for both projection images and tomosynthesis slices was obtained for 15-17 projections spanning an angular arc of ϳ45°-the maximum tested in our study, and for an acquisition dose equal to single-view mammography. The optimization framework developed in this framework is applicable to other reconstruction techniques and other multiprojection systems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimized image acquisition for breast tomosynthesis in projection and reconstruction space

Chawla

Baker

et al. 2009

Medical Physics

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“…One particular multiprojection acquisition modality, digital breast tomosynthesis, has indeed been shown to provide improved diagnostic performance as compared to the standard projection procedures. 3 However, the tomosynthesis technique is prone to reconstruction artifacts, 4,5 which might reduce the efficiency of tomosynthesis reading, even leading to higher false positive findings. 6 Therefore, there would be an advantage in using an imaging technique that could fuse information from multiple images, similar to tomosynthesis, but without the confounding effects of the reconstruction.…”

Section: Introductionmentioning

confidence: 99%

A mathematical model platform for optimizing a multiprojection breast imaging system

et al. 2008

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Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagnosis. Projection data are either reconstructed into slices as in the case of tomosynthesis or analyzed directly as in the case of multiprojection correlation imaging technique, thereby avoiding reconstruction artifacts. In this study, the authors investigated the optimum geometry of acquisitions of a multiprojection breast correlation imaging system in terms of the number of projections and their total angular span that yield maximum performance in a task that models clinical decision. Twenty-five angular projections of each breast from 82 human subjects in our breast tomosynthesis database were each supplemented with a simulated 3 mm mass. An approach based on Laguerre-Gauss channelized Hotelling observer was developed to assess the detectability of the mass in terms of receiver operating characteristic ͑ROC͒ curves. Two methodologies were developed to integrate results from individual projections into one combined ROC curve as the overall figure of merit. To optimize the acquisition geometry, different components of acquisitions were changed to investigate which one of the many possible configurations maximized the area under the combined ROC curve. Optimization was investigated under two acquisition dose conditions corresponding to a fixed total dose delivered to the patient and a variable dose condition, based on the number of projections used. In either case, the detectability was dependent on the number of projections used, the total angular span of those projections, and the acquisition dose level. In the first case, the detectability approximately followed a bell curve as a function of the number of projections with the maximum between 8 and 16 projections spanning angular arcs of about 23°−45°, respectively. In the second case, the detectability increased with the number of projections approaching an asymptote at 11-17 projections for an angular span of about 45°. These results indicate the inherent information content of the multiprojection image data reflecting the relative role of quantum and anatomical noise in multiprojection breast imaging. The optimization scheme presented here may be applied to any multiprojection imaging modalities and may be extended by including reconstruction in the case of digital breast tomosynthesis and breast computed tomography.

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“…2 A large amount of the continued research being performed to improve the clinical performance of breast imaging requires the simulation of realistic patient breast models, and this has become an entire research area in itself. [3][4][5][6][7][8][9][10] Research on breast imaging dosimetry, [11][12][13][14][15][16][17][18][19][20] lesion detectability, [21][22][23] technique optimization, 24,25 image registration, 26 image texture, 27 and x-ray scatter correction 28 has been performed using software breast models, representing both uncompressed and compressed breasts. In most studies involving a model of the compressed breast, only the cranio-caudal (CC) view has been simulated, with the breast represented as a semi-circle or semi-ellipse.…”

Section: Introductionmentioning

confidence: 99%

Objective models of compressed breast shapes undergoing mammography

Feng¹,

Patel²,

Sechopoulos³

2013

Medical Physics

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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.

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Low-contrast lesion detection in tomosynthetic breast imaging using a realistic breast phantom

Cited by 24 publications

References 21 publications

Optimized image acquisition for breast tomosynthesis in projection and reconstruction space

Optimized image acquisition for breast tomosynthesis in projection and reconstruction space

A mathematical model platform for optimizing a multiprojection breast imaging system

Objective models of compressed breast shapes undergoing mammography

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