The use of mammography equipment attached to a digital breast tomosynthesis (DBT) system is widespread in Japan. Tomosynthesis exposes the breast to X-rays continuously (or in pulses) at different angles in a single scan, yielding multiple projection images. Arbitrary multi-slice images can be reconstructed from the projection images after scanning. However, DBT increases the exposure dose compared to mammography. Therefore, it is necessary to rapidly establish performance evaluation procedures and quality control procedures for DBT. In this study, we conduct quality control measurements on DBT systems sold in Japan by five different companies and examine feasible common items. The purpose of the study was to establish a quality control method for DBT systems in Japan. The measurements were performed based on the EUREF breast tomosynthesis quality control protocol version 1.03. In this study, we attempted to measure 18 items in DBT systems. We examined whether the 18 items could be measured using each system; however, this was not an evaluation of equipment performance based on the measured values. There were some quality control items that were difficult to complete due to the specifications of a DBT system, such as equipment that required pressure during DBT operation, problems due to the shape of the bucky, and equipment that did not have stationary mode. There were also problems related to the availability of measurement data, such as with equipment that could not retrieve projection data and reconstructed data. This study clarified points to be considered for establishing common quality control items. In the future, we will carefully refer to the recently published IEC 61223-3-6, consider international harmonization, and establish DBT guidelines customized for the Japanese market.
Recently we have reported indirect X-ray photon-counting imaging using CMOS photon detectors (CPD) and have shown its high spatial resolution with MTF of over 0.7 at 10LP/mm [1]. However, at that time its energy resolution potential and the quantum efficiency were totally unknown. Thus, there was a question about whether it can detect relatively low energy X-ray photons, for example around 20keV used for mammography, with sufficient quantum efficiency while eliminating counting errors.
In this study we exposed the CPD test devices to near single energy X-ray photons of 19.5keV adopting a clinical mammography equipment and additional Mo filters, and measured output intensity distributions. We also fitted our intensity distribution model to the results estimating signal yield per keV and parameters for signal variation.
We tested with 2 types of Hamamatsu Photonics CsI(Tl) scintillators. A CPD with J6675-01 scintillator plate has a signal distribution of 76% FWHM, still showing sufficient capability of photon counting with a little loss of actual signals. The signal yield is about 3.6 e-/keV. In the meanwhile, a CPD with J6675 has a superior distribution of 49% FWHM with signal yield of 7.1 e-/keV.
In both types, the dominant factor of the variation is not shot noise or sensor noise but something that is proportional to the signal intensity. This variation factor is possibly attributed to random noise of scintillation intensity, which is about 28% rms in J6675-01 and 17% rms in J6675.
Mammary gland density is used as one of the measures in managing the risk of breast cancer. It can be divided into four categories. In addition, mammography is used for population-based breast cancer screening in Japan. However, mass and calcification are assumed to be hidden in the shadow of the mammary gland as displayed by the mammogram when patients showing heterogeneously dense or extremely dense in the mammary gland density category are scanned with mammography. Therefore, it is necessary to recommend an examination suitable for each category of mammary gland density. In one example, a doctor recommends ultrasonography in addition to mammography for patients with dense breasts. However, mammary gland density is distinguished visually using subjective judgment. Against such a background, we have worked on an automatic classification of mammary gland densities using a deep learning technique. Moreover, we investigated the effect of image resolution on the classification results in the automatic classification of mammary gland density with deep learning. The resolution was varied from 1/100 (474 × 354) to 1/3600 (79 × 59) using 1106 cases of resolution 4740 × 3540 (pixels) obtained with Fuji Computed Radiography (FCR) by Fujifilm Co. Ltd. As a result, the accuracy of automatic classification of mammary gland density exceeded 90% up to a resolution of 1/400 (237 × 177), and was 89% even at the lowest resolution of 1/3600 (79 × 59).
The purpose of this work is to develop a new pattern recognition method using the higher-order autocorrelation features (HOAFs), and to apply this to our microcalcification detection system on mammographic images. Microcalcification is a typical sign of breast cancer and tends to show up as very subtle shadows. We developed a triple-ring filter for detecting microcalcifications, and the prototype detection system is nearly complete. However, our prototype system does not allow for the detection of three types of microcalcifications, two of which are amorphous and linear microcalcifications and the third is obscured microcalcifications which is often confused with the background or circumference that have almost the same density. We targeted the amorphous type of microcalcification, which has a low contrast and easily goes undetected. The various features of microcalcifications and false-positive (FP) shadows were extracted and trained using the multi-regression analysis, and unknown images were recognized as a result of this training. As a result, amorphous microcalcifications were successfully detected with no increase in the number of FPs compared with our existing detection method.
A method for measuring the characteristic curves generated by the mammography imaging systems has not yet
been well established due to poor quality control over X-ray exposure in the range of kV values, which is lower than the
conventional quality. In this paper, we proposed a bootstrap method using a “stepwedge” designed for characteristic
curve measurement in mammography. A ten-step stepwedge containing calcium phosphate, with each step having a
different density of material, was employed. In our experiment, the tube voltage and mA values were changed in the
range of 25 to 32 kV at increments of 1 kV and in the range of 20 to 100 mAs at increments of 20 mAs, respectively.
The results of the curve measurements indicated that our method might be useful to both screen-film mammography and
computed radiography (CR), although additional experiments to evaluate the accuracy and precision of the acquired
data are required.
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