No abstract

Average glandular dose (AGD) in digital mammography crucially depends on the estimation of breast glandularity. In this study we compared three different methods of estimating glandularities according to Wu, Dance and Volpara with respect to resulting AGDs. Exposure data from 3050 patient images, acquired with a GE Senographe Essential constituted the study population of this work. We compared AGD (1) according to Dance et al . applying custom g, c, and s factors using HVL, breast thickness, patient age and incident air kerma (IAK) from the DICOM headers; (2) according to Wu et al . as determined by the GE system; and (3) AGD derived with the Dance model with personalized c factors using glandularity determined with the Volpara (Volpara Solutions, Wellington, New Zealand) software (Volpare AGD). The ratios of the resulting AGDs were analysed versus parameters influencing dose. The highest deviation between the resulting AGDs was found in the ratio of GE AGD to Volpara AGD for breast thicknesses between 20 and 40 mm (ratio: 0.80). For thicker breasts this ratio is close to one (1 ± 0.02 for breast thicknesses >60 mm). The Dance to Volpara ratio was between 0.86 (breast thickness 20–40 mm) and 0.99 (>80 mm), and Dance/GE AGD was between 1.07 (breast thickness 20–40 mm) and 0.98 (41–60, and >80 mm). Glandularities by Volpara were generally smaller than the one calculated with the Dance method. This effect is most pronounced for small breast thickness and older ages. Taking the considerable divergences between the AGDs from different methods into account, the selection of the method should by done carefully. As the Volpara method provides an analysis of the individual breast tissue, while the Wu and the Dance methods use look up tables and custom parameter sets, the Volpara method might be more appropriate if individual ADG values are sought. For regulatory purposes and comparison with diagnostic reference values, the method to be used needs to be defined exactly and clearly be stated. However, it should be accepted that dose values calculated with standardized models, like AGD and also effective dose, are afflicted with a considerable uncertainty budgets that need to be accounted for in the interpretation of these values.

Purpose:According to the European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) image quality of digital mammography devices has to be assessed using human evaluation of the CDMAM contrast‐detail phantom. This is accomplished by the determination of threshold thicknesses of gold disks with different diameters (0.08–2 mm) and revealed to be very time consuming. Therefore a software solution based on a nonprewhitening matched filter (NPW) model was developed at the University of Nijmegen. Factors for the conversion from automatic to human readouts have been determined by Younget al. [Proc. SPIE 614206, 1–13 (2006) and Proc. SPIE 6913, 69131C1 (2008)] using a huge amount of data of both human and automatic readouts. These factors depend on the observer groups and are purely phenomenological. The authors present an alternative approach to determine the factors by using the Rose observer model.Methods:Their method uses the Rose theory which gives a relationship between threshold contrast, diameter of the object and number of incident photons. To estimate the conversion factors for the five diameters from 0.2 to 0.5 mm they exposed with five different current‐time products which resulted in 25 equations with five unknowns.Results:The theoretical conversion factors (in dependence of the diameters) amounted to be 1.61 ± 0.02 (0.2 mm diameter), 1.67 ± 0.02 (0.25 mm), 1.85 ± 0.02 (0.31 mm), 2.09 ± 0.02 (0.4 mm), and 2.28 ± 0.02 (0.5 mm). The corresponding phenomenological factors found in literature are 1.74 (0.2 mm), 1.78 (0.25 mm), 1.83 (0.31 mm), 1.88 (0.4 mm), and 1.93 (0.5 mm).Conclusions:They transferred the problem of determining the factors to a well known observer model which has been examined for many years and is also well established. This method reveals to be reproduceable and produces factors comparable to the phenomenological ones.

For FFDM, images obtained from a wet laser printer show superior objective and subjective image quality compared with a paper printer. As a consequence, the paper printer should not be used for FFDM.

In mammography screening, profound assessment of technical image quality is imperative. The European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) suggests using an alternate fixed choice contrast-detail phantom-like CDMAM. For the evaluation of technical image quality, human or automated readouts can be used. For automatic evaluation, a software (cdcom) is provided by EUREF. If the automated readout indicates unacceptable image quality, additional human readout may be performed overriding the automated readout. As the latter systematically results in higher image quality ratings, conversion factors between both methods are regularly applied. Since most image quality issues with mammography systems arise within CR systems, an assessment restricted to CR systems with data from the Austrian Reference Center in the mammography screening program has been conducted. Forty-five CR systems were evaluated. Human readouts were performed with a randomisation software to avoid bias due to learning effects. Additional automatic evaluation allowed for the computation of conversion factors between human and automatic readouts. These factors were substantially lower compared to those suggested by EUREF, namely 1.21 compared to 1.62 (EUREF UK method) and 1.42 (EUREF EU method) for 0.1 mm, and 1.40 compared to 1.83 (EUREF UK) and 1.73 (EUREF EU) for 0.25 mm structure size, respectively. Using either of these factors to adjust patient dose in order to comply with image quality requirements results in differences in the dose increase of up to 90%. This necessitates a consensus on their proper application and limits the validity of the assessment methods. Clear criteria for CR systems based on appropriate studies should be promoted.