In this study, we proposed a method for detecting microcalcifications and tumor tissue using a cadmium telluride (CdTe) series linear
detector. The CdTe series detector was used as an energy resolved photon-counting (hereafter referred to as the photon-counting)
mammography detector. The CdTe series linear detector and two types of phantom were designed using a MATLAB simulation. Each
phantom consisted of mammary gland and adipose tissue. One phantom contained microcalcifications and the other contained tumor
tissue. We varied the size of these structures and the mammary gland composition. We divided the spectrum of an x-ray, which is
transmitted to each phantom, into three energy bins and calculated the corresponding linear attenuation coefficients from the numbers
of input and output photons. Subsequently, the absorption vector length that expresses the amount of absorption was calculated. When
the material composition was different between objects, for example mammary gland and microcalcifications, the absorption vector
length was also different. We compared each absorption vector length and tried to detect the microcalcifications and tumor tissue.
However, as the size of microcalcifications and tumor tissue decreased and/or the mammary gland content rate increased, there was
difficulty in distinguishing them. The microcalcifications and tumor tissue despite the reduction in size or increase in mammary gland
content rate can be distinguished by increasing the x-ray dosage. Therefore, it is necessary to find a condition under which a low
exposure dose is optimally balanced with high detection sensitivity. It is a new method to indicate the image using photon counting
technology.
Energy resolved photon-counting mammography is a new technology, which counts the number of photons that passes through an object, and presents it as a pixel value in an image of the object. Silicon semiconductor detectors are currently used in commercial mammography. However, the disadvantage of silicon is the low absorption efficiency for high X-ray energies. A cadmium telluride (CdTe) series detector has a high absorption efficiency over a wide energy range. In this study, we proposed a method to estimate the composition of the mammary gland using a CdTe series detector as a photon-counting detector. The fact that the detection rate of breast cancer in mammography is affected by mammary gland composition is now widely accepted. Assessment of composition of the mammary gland has important implications. An important advantage of our proposed technique is its ability to discriminate photons using three energy bins. We designed the CdTe series detector system using the MATLAB simulation software. The phantom contains nine regions with the ratio of glandular tissue and adipose varying in increments of 10%. The attenuation coefficient for each bin’s energy was calculated from the number of input and output photons possessed by each. The evaluation results obtained by plotting the attenuation coefficient μ in a three-dimensional (3D) scatter plot show that the plots had a regular composition order congruent with that of the mammary gland. Consequently, we believe that our proposed method can be used to estimate the composition of the mammary gland.
We propose a new mammography system using a cadmium telluride (CdTe) series photon-counting detector, having high absorption efficiency over a wide energy range. In a previous study, we showed that the use of high X-ray energy in digital mammography is useful from the viewpoint of exposure dose and image quality. In addition, the CdTe series detector can acquire X-ray spectrum information following transmission through a subject. This study focused on the tissue composition identified using spectral information obtained by a new photon-counting detector. Normal breast tissue consists entirely of adipose and glandular tissues. However, it is very difficult to find tumor tissue in the region of glandular tissue via a conventional mammogram, especially in dense breast because the attenuation coefficients of glandular tissue and tumor tissue are very close. As a fundamental examination, we considered a simulation phantom and showed the difference between normal breast tissue and tumor tissue of various thicknesses in a three-dimensional (3D) scatter plot. We were able to discriminate between both types of tissues. In addition, there was a tendency for the distribution to depend on the thickness of the tumor tissue. Thinner tumor tissues were shown to be closer in appearance to normal breast tissue. This study also demonstrated that the difference between these tissues could be made obvious by using a CdTe series detector. We believe that this differentiation is important, and therefore, expect this technology to be applied to new tumor detection systems in the future.
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