Anatomical noise in contrast-enhanced digital mammography. Part II. Dual-energy imaging

Hill, Melissa L.; Mainprize, James G.; Carton, Ann-Katherine; Saab-Puong, Sylvie; Iordache, Răzvan; Muller, Serge; Jong, Roberta A.; Dromain, Clarisse; Yaffe, Martin J.

doi:10.1118/1.4812681

Cited by 26 publications

(63 citation statements)

References 54 publications

(124 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 3 shows the alpha and beta values calculated for real and simulated images. The beta value of real images used in this study (β≈3) is consistent with previously published work (Burgess 1999, Cockmartin et al 2013, Hill et al 2013. The average beta values of simulated images closely match those of real images for both 2D (<7% difference) and DBT (<4% difference).…”

Section: Real Images Synthetic Images P-value 2dsupporting

confidence: 89%

“…The anatomical structures seen in mammograms are known to be described by a power-law spectrum (Burgess 1999, Cockmartin et al 2013, Hill et al 2013, of the form shown in equation (3), where β is the power-law exponent which reflects breast tissue complexity; α is the power spectrum magnitude in units of area; and f is the spatial frequency.…”

Section: Power Spectrum Analysismentioning

confidence: 99%

“…Power spectrum analysis was performed on unprocessed 2D and reconstructed DBT planes of the breast models and real images following published methods (Cockmartin et al 2013, Hill et al 2013. The ROI size was set to 25mm 2 with an overlap of 1.25mm in both horizontal and vertical directions.…”

Section: Power Spectrum Analysismentioning

confidence: 99%

“…Thus power-law parameters were estimated by applying a linear fit to the log transformed data in the frequency range of 0.2-0.7mm -1 . The power spectra for DBT images were calculated in the same manner as the 2D images except the image pixels were not normalised since they are independent of the dose applied (Cockmartin et al 2013, Hill et al 2013.…”

Section: Power Spectrum Analysismentioning

confidence: 99%

See 3 more Smart Citations

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

et al. 2017

View full text Add to dashboard Cite

A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from digital breast tomosynthesis (DBT) clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper's ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were .51±.06 and .54±.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72±.01, 2.75±.01) and (2.77±.03, 2.82±.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average β values (2D, DBT) of (3.10±.17, 3.21±.11) and (3.01±.32, 3.19±.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30mm x 30mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers. Page 1 of 16AUTHOR SUBMITTED MANUSCRIPT -PMB-104914. R2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 KeywordsVirtual clinical trials, breast model, breast phantom, synthetic breast, image simulation, 2D-mammography, digital breast tomosynthesis.

show abstract

Section: Real Images Synthetic Images P-value 2dsupporting

confidence: 89%

Section: Power Spectrum Analysismentioning

confidence: 99%

Section: Power Spectrum Analysismentioning

confidence: 99%

Section: Power Spectrum Analysismentioning

confidence: 99%

See 2 more Smart Citations

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

et al. 2017

View full text Add to dashboard Cite

show abstract

“…To characterize breast texture, radial power-law spectrum coefficients, β, estimated in LE, HE and DE recombined phantom images were compared to previously reported β values from clinical LE, HE and DE recombined CC and MLO images acquired with a prototype SenoBright® application 15 .…”

Section: Power-law Analysismentioning

confidence: 99%

Assessment of mass detection performance in contrast enhanced digital mammography

Carton¹,

Carvalho²,

et al. 2015

Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment

Self Cite

View full text Add to dashboard Cite

We address the detectability of contrast-agent enhancing masses for contrast-agent enhanced spectral mammography (CESM), a dual-energy technique providing functional projection images of breast tissue perfusion and vascularity using simulated CESM images. First, the realism of simulated CESM images from anthropomorphic breast software phantoms generated with a software x-ray imaging platform was validated. Breast texture was characterized by power-law coefficients calculated in data sets of real clinical and simulated images. We also performed a 2-alternative forced choice (2-AFC) psychophysical experiment whereby simulated and real images were presented side-by-side to an experienced radiologist to test if real images could be distinguished from the simulated images. It was found that texture in our simulated CESM images has a fairly realistic appearance. Next, the relative performance of human readers and previously developed mathematical observers was assessed for the detection of iodine-enhancing mass lesions containing different contrast agent concentrations. A four alternative-forced-choice (4 AFC) task was designed; the task for the model and human observer was to detect which one of the four simulated DE recombined images contained an iodineenhancing mass. Our results showed that the NPW and NPWE models largely outperform human performance. After introduction of an internal noise component, both observers approached human performance. The CHO observer performs slightly worse than the average human observer. There is still work to be done in improving model observers as predictors of human-observer performance. Larger trials could also improve our test statistics. We hope that in the future, this framework of software breast phantoms, virtual image acquisition and processing, and mathematical observers can be beneficial to optimize CESM imaging techniques.

show abstract

Optimization of contrast‐enhanced breast imaging: Analysis using a cascaded linear system model

Scaduto

Zhao

2017

Medical Physics

View full text Add to dashboard Cite

show abstract

Anatomical noise in contrast-enhanced digital mammography. Part II. Dual-energy imaging

Cited by 26 publications

References 54 publications

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

Assessment of mass detection performance in contrast enhanced digital mammography

Optimization of contrast‐enhanced breast imaging: Analysis using a cascaded linear system model

Contact Info

Product

Resources

About