Planar 2D x-ray mammography is generally accepted as the preferred screening technique used for breast cancer detection. Recently, digital breast tomosynthesis (DBT) has been introduced to overcome some of the inherent limitations of conventional planar imaging, and future technological enhancements are expected to result in the introduction of further innovative modalities. However, it is crucial to understand the impact of any new imaging technology or methodology on cancer detection rates and patient recall. Any such assessment conventionally requires large scale clinical trials demanding significant investment in time and resources. The concept of virtual clinical trials and virtual performance assessment may offer a viable alternative to this approach. However, virtual approaches require a collection of specialized modelling tools which can be used to emulate the image acquisition process and simulate images of a quality indistinguishable from their real clinical counterparts. In this paper, we present two image simulation chains constructed using modelling tools that can be used for the evaluation of 2D-mammography and DBT systems. We validate both approaches by comparing simulated images with real images acquired using the system being simulated. A comparison of the contrast-to-noise ratios and image blurring for real and simulated images of test objects shows good agreement ( < 9% error). This suggests that our simulation approach is a promising alternative to conventional physical performance assessment followed by large scale clinical trials.

Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection.

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Aluminium is often used as a substitute material for calcifications in phantom measurements in mammography. Additionally, calcium oxalate, hydroxyapatite and aluminium are used in simulation studies. This assumes that these materials have similar attenuation properties to calcification, and this assumption is examined in this work. Sliced mastectomy samples containing calcification were imaged at ×5 magnification using a digital specimen cabinet. Images of the individual calcifications were extracted, and the diameter and contrast of each calculated. The thicknesses of aluminium required to achieve the same contrast as each calcification when imaged under the same conditions were calculated using measurements of the contrast of aluminium foils. As hydroxyapatite and calcium oxalate are also used to simulate calcifications, the equivalent aluminium thicknesses of these materials were also calculated using tabulated attenuation coefficients. On average the equivalent aluminium thickness was 0.85 times the calcification diameter. For calcium oxalate and hydroxyapatite, the equivalent aluminium thicknesses were 1.01 and 2.19 times the thickness of these materials respectively. Aluminium and calcium oxalate are suitable substitute materials for calcifications. Hydroxyapatite is much more attenuating than the calcifications and aluminium. Using solid hydroxyapatite as a substitute for calcification of the same size would lead to excessive contrast in the mammographic image.

Purpose To investigate the relationship between image quality measurements and the clinical performance of digital mammographic systems. Methods Mammograms containing subtle malignant non-calcification lesions and simulated malignant calcification clusters were adapted to appear as if acquired by four types of detector. Observers searched for suspicious lesions and gave these a malignancy score. Analysis was undertaken using jackknife alternative free-response receiver operating characteristics weighted figure of merit (FoM). Images of a CDMAM contrast-detail phantom were adapted to appear as if acquired using the same four detectors as the clinical images. The resultant threshold gold thicknesses were compared to the FoMs using a linear regression model and an F-test was used to find if the gradient of the relationship was significantly non-zero. Results The detectors with the best image quality measurement also had the highest FoM values. The gradient of the inverse relationship between FoMs and threshold gold thickness for the 0.25mm diameter disk was significantly different from zero for calcification clusters (p=0.027), but not for non-calcification lesions (p=0.11). Systems performing just above the minimum image quality level set in the European Guidelines for Quality Assurance in Breast Cancer Screening and Diagnosis resulted in reduced cancer detection rates compared to systems performing at the achievable level. Conclusions The clinical effectiveness of mammography for the task of detecting calcification clusters was found to be linked to image quality assessment using the CDMAM phantom. The European Guidelines should be reviewed as the current minimum image quality standards may be too low.

OBJECTIVE. The objective of our study was to investigate the effect of image processing on the detection of cancers in digital mammography images. MATERIALS AND METHODS. Two hundred seventy pairs of breast images (both breasts, one view) were collected from eight systems using Hologic amorphous selenium detectors: 80 image pairs showed breasts containing subtle malignant masses; 30 image pairs, biopsy-proven benign lesions; 80 image pairs, simulated calcification clusters; and 80 image pairs, no cancer (normal). The 270 image pairs were processed with three types of image processing: standard (full enhancement), low contrast (intermediate enhancement), and pseudo-film-screen (no enhancement). Seven experienced observers inspected the images, locating and rating regions they suspected to be cancer for likelihood of malignancy. The results were analyzed using a jackknife-alternative free-response receiver operating characteristic (JAFROC) analysis. RESULTS. The detection of calcification clusters was significantly affected by the type of image processing: The JAFROC figure of merit (FOM) decreased from 0.65 with standard image processing to 0.63 with low-contrast image processing (p = 0.04) and from 0.65 with standard image processing to 0.61 with film-screen image processing (p = 0.0005). The detection of noncalcification cancers was not significantly different among the image-processing types investigated (p > 0.40). CONCLUSION. These results suggest that image processing has a significant impact on the detection of calcification clusters in digital mammography. For the three image-processing versions and the system investigated, standard image processing was optimal for the detection of calcification clusters. The effect on cancer detection should be considered when selecting the type of image processing in the future.

Objectives To compare the performance of different types of detectors in breast cancer detection. Methods A mammography image set containing subtle malignant non-calcification lesions, biopsy-proven benign lesions, simulated malignant calcification clusters and normals was acquired using amorphous-selenium (a-Se) detectors. The images were adapted to simulate four types of detectors at the same radiation dose: digital radiography (DR) detectors with a-Se and caesium iodide (CsI) convertors, and computed radiography (CR) detectors with a powder phosphor (PIP) and a needle phosphor (NIP). Seven observers marked suspicious and benign lesions. Analysis was undertaken using jackknife alternative free-response receiver operating characteristics weighted figure of merit (FoM). The cancer detection fraction (CDF) was estimated for a representative image set from screening. Results No significant differences in the FoMs between the DR detectors were measured. For calcification clusters and non-calcification lesions, both CR detectors’ FoMs were significantly lower than for DR detectors. The calcification cluster’s FoM for CR NIP was significantly better than for CR PIP. The estimated CDFs with CR PIP and CR NIP detectors were up to 15% and 22% lower respectively than for DR detectors. Conclusion Cancer detection is affected by detector type and the use of CR in mammography should be reconsidered.

Objective: To estimate the risks and benefits of breast screening in terms of number of deaths due to radiationinduced cancers and the number of lives saved owing to modern screening in the National Health Service Breast Screening Programme (NHSBSP) in England. Methods: Radiation risk model, patient dose data and data from national screening statistics were used to estimate the number of deaths due to radiation-induced breast cancers in the NHSBSP in England. Dose and dose effectiveness factors (DDREFs) equal to one and two were assumed. The breast cancer mortality reduction in the invited population due to screening and the percentage of females diagnosed with symptomatic breast cancer, who die from breast cancer, were collated from the literature. The number of lives saved owing to screening was calculated. Results: Assuming, a total of 1,770,436 females between the ages of 50-70 years were screened each year, and a breast cancer mortality reduction of 20% due to screening in the invited population, the number of screen-detected cancers were 14,872 annually, resulting in 1071 lives saved.