Validation of simulation of calcifications for observer studies in digital mammography

Abstract

Studies using simulated calcifications can be performed to measure the effect of different imaging factors on calcification detection in digital mammography. The simulated calcifications must be inserted into clinical images with realistic contrast and sharpness. MoCa is a program which modifies the contrast and sharpness of simulated calcification clusters extracted from images of mastectomy specimens acquired on a digital specimen cabinet at high magnification for insertion into clinical mammography images. This work determines whether the use of MoCa results in simulated calcifications with the correct contrast and sharpness. Aluminium foils (thickness 0.1-0.4 mm) and 1.60 µm thick gold discs (diameter 0.13-0.8 mm) on 0.5 mm aluminium were imaged with a range of thicknesses of polymethyl methacrylate (PMMA) using an amorphous selenium direct digital (DR) system and a powder phosphor computed radiography (CR) system (real images). Simulated images of the tests objects were also generated using MoCa. The contrast of the aluminium squares and the degradation of the contrast of the gold discs as a function of disc diameter were compared in the real and simulated images. The average ratios of the simulated-to-real aluminium contrasts over all aluminium and PMMA thicknesses were 1.03 ± 0.04 (two standard errors in the mean) and 0.99 ± 0.03 for the DR and CR systems, respectively. The ratio of the simulated-to-real degradations of contrast averaged over all disc diameters and PMMA thicknesses were 1.007 ± 0.008 and 1.002 ± 0.013 for DR and CR, respectively. The use of MoCa was accurate within the experimental errors.

The use of sequential X-ray, CT and MRI in the preoperative evaluation of breast-conserving surgery

“…The micro-calcifications are therefore, important for the early detection of breast cancer (9). The full-field digital breast cancer X-ray imaging inspection is characterized by its high definition and contrast, and can fully display the features of micro-calcifications, thus it is the golden standard for detecting micro-calcifications (10). However, radiologists can only recognize the calcifications with a diameter of >0.5 mm, and many micro-calcifications are missed.…”

Breast cancer detection rates using four different types of mammography detectors

“…The original clusters were extracted from images of mastectomy slices acquired at high magnification in a specimen cabinet. The process of extraction and insertion of calcification clusters has been validated such that the calcifications matched real malignant clusters in image quality and appearance (15, 16). The locations for the insertions were chosen to ensure that the calcifications were seen in a wide range of glandularities.…”

A model observer study using acquired mammographic images of an anthropomorphic breast phantom

“…Image quality is also important for the detection of calcifications because they are very small in size and they can occasionally be an early sign of breast cancer . Different system characteristics and different image processing software might have an effect on the detectability of calcification‐related signals . The quality of image processing is currently evaluated by humans in receiver operating curve (ROC) studies .…”

“…5 Different system characteristics and different image processing software might have an effect on the detectability of calcification-related signals. 6,7 The quality of image processing is currently evaluated by humans in receiver operating curve (ROC) studies. 8 However, these clinical studies can be time-consuming and they are not cost-effective.…”