Evaluation of position-estimation methods applied to CZT-based photon-counting detectors for dedicated breast CT

We report on the continued development and testing of unique types of Cadmium Zinc Telluride (CZT) detectors.Using large volume (10 × 20 × 20 mm 3 ) CZT crystals, we contact variou s dual anodeŽ detector designs. Weincorporate a segmented cathode with “ve regions so that the charge on all seven contacts can be used todetermine the energy and the 3-D interaction location of detected X-ray and gamma-ray photons. We describethe status of the detector development program, emphasize strengths and weaknesses of the dierent contactcon“gurations, and discuss possible applications of Dual Anode Detectors in radiation detection applications.Keywords: CZT, X-ray Detector , Contact Geometry 1. INTRODUCTION The high average atomic number ( 50) and room temperature operation of Cadmium Zinc Telluride (CZT)detectors make them desirable for Homeland Security a pplications where high eciency of detecting nuclearartifacts is required, such as a stand o detector at a border crossing. We currently are working to developlarge-volume CZT detectors with few re adout channels by exploring novel contact designs. Such designs presentcertain advantages while avoiding the complications, limitations, and requirements of using the standard contactpatterns.The most common CZT detector designs in use today employ either pixel contacts or a coplanar grid (CPG)for the anode.

Purpose: To investigate the feasibility of using an image-based method to correct for spectral distortions from photon-counting detectors for their application in breast computed tomography (CT). Methods: The polyenergetic incident spectrum was simulated with the tungsten anode spectral model. Experiments were performed on a Cadmium-Zinc-Telluride (CZT) photon-counting detector with five energy thresholds. BR12 phantoms of various thicknesses were used for calibration. A non-linear function was selected to fit the count correlation between the simulated and the measured spectra in the calibration process. To evaluate the proposed spectral distortion correction method, both the corrected counts and the effective attenuation coefficients were compared to the simulated values for polymethyl methacrylate (PMMA) phantoms of 8.7 mm, 48.8 mm and 100.0 mm. The feasibility of applying the proposed method to quantitative material decomposition was tested using a dual-energy imaging technique with a three-material phantom that consisted of water, lipid and protein. Results: The implementation of the proposed method reduced the relative RMS error of the output counts in the five energy bins with respect to the simulated incident counts from 23.0%, 33.0% and 54.0% to 1.2%, 1.8% and 7.7% for 8.7 mm, 48.8 mm and 100.0 mm PMMA phantoms, respectively. The accuracy of the effective attenuation coefficient of PMMA estimate was also improved with the proposed spectral distortion correction. Finally, the relative RMS error of water, lipid and protein decompositions in dual- energy imaging was significantly reduced from 53.4% to 6.8% after correction was applied. Conclusions: The study demonstrated that the proposed method can effectively reduce the spectral distortions caused by various artifacts, including pulse pileup and charge sharing effects. It may be used as a generalized procedure for the spectrum distortion correction of different photon-counting detectors in clinical breast CT systems.

According to World Cancer Research Fund International, breast cancer is the 2nd common cancer type worldwide and 1st type among women. To diagnose breast cancer, mammography (MG) and digital breast tomosynthesis (DBT) are commonly preferred imaging methods. Radiotherapy is one of the treatment methods of breast cancer and in case of radiotherapy is preferred, breast computed tomography (B-CT) is taken for breast contouring which is essential for radiotherapy. Mammography (MG), digital breast tomosynthesis (DBT) and breast computed tomography (B-CT) are medical imaging techniques using ionizing radiation. During the MG, DBT and B-CT scan, the patient is exposure to ionizing radiation and determining the correct radiation dose is crucial for both correct imaging of breast and avoiding side effects of radiation to the patient. Determination of the correct dose for diagnosis is called dose optimization. For dose optimization, medical imaging devices are calibrated via phantoms. Phantom is a device that mimicking real patient tissues on radiosensitivity. Formerly, phantoms were made of water, as the human body mainly consists of water. Then, epoxy or PMMA based phantoms are used due to the water is not perfect material for mimicking human tissue. Epoxy or PMMA based phantoms are better at mimicking soft tissue and bone tissue but not enough for breast due to the breast is formed by heterogeneous distribution of glandular and adipose tissues. Heterogeneity of glandular and adipose tissues, glandular and adipose tissue percentage (%G/A), vary with race and age of women. Due to the radiation dose absorbed by glandular tissue is dependent on the glandular tissue percentage, it is essential to develop breast phantom specific to glandular and adipose tissue percentage (%G/A) for better radiation dose optimization. The aim of this study is to develop anthropomorphic breast phantoms specific to Turkish women at different age intervals. In previous study, %G/A ratios for Turkish women at different age intervals are determined and epoxy-based phantoms were produced for each age interval. Those phantoms assumed the glandular and adipose tissues are distributed homogeneously contrary to real breast. The aimed more realistic, anthropomorphic phantoms will consist of three different materials mimicking three different tissues. A FDM type 3D printer with dual nozzle is going to be used for producing glandular and adipose tissues; an SLA type 3D printer is going to be used for skin. By this way, development of phantom mimicking breast better than epoxy-based one is the goal of the study. At first step, the materials and filling ratios mimicking best each three tissues will be determined. By using PVA, TPU, ABS, PLA and PET type filaments, cubic samples will be produced with filling ratios between %50 and %100. Physical density, HU value, effective atomic number, HVL values for each sample will be determined and the filament types and filling ratios closest to real tissues will be chosen to produce phantom. Anonymous B-CT images of breast with specific %G/A ratios will be base for design of phantoms. The phantoms will have cavities for placing point detectors to measure the glandular dose during the CT scan. After all the phantoms will be produced, the phantoms will undergo CT scan and during the scan, glandular dose and tissue entrance dose will be measured via appropriate detectors. Via finding the relation between skin entrance dose and glandular dose, it is aimed to determine more accurate factors for Dance’s equation for calculation of glandular dose. This study is being supported by TÜBİTAK with project code 224S843 in the scope of 1002-A Fast Support Program.

To evaluate the performance of a prototype photon-counting detector (PCD) computed tomography (CT) system for abdominal CT in humans and to compare the results with a conventional energy-integrating detector (EID). The study was HIPAA-compliant and institutional review board-approved with informed consent. Fifteen asymptomatic volunteers (seven men; mean age, 58.2 years ± 9.8 [standard deviation]) were prospectively enrolled between September 2 and November 13, 2015. Radiation dose-matched delayed contrast agent-enhanced spiral and axial abdominal EID and PCD scans were acquired. Spiral images were scored for image quality (Wilcoxon signed-rank test) in five regions of interest by three radiologists blinded to the detector system, and the axial scans were used to assess Hounsfield unit accuracy in seven regions of interest (paired t test). Intraclass correlation coefficient (ICC) was used to assess reproducibility. PCD images were also used to calculate iodine concentration maps. Spatial resolution, noise-power spectrum, and Hounsfield unit accuracy of the systems were estimated by using a CT phantom. In both systems, scores were similar for image quality (median score, 4; P = .19), noise (median score, 3; P = .30), and artifact (median score, 1; P = .17), with good interrater agreement (image quality, noise, and artifact ICC: 0.84, 0.88, and 0.74, respectively). Hounsfield unit values, spatial resolution, and noise-power spectrum were also similar with the exception of mean Hounsfield unit value in the spinal canal, which was lower in the PCD than the EID images because of beam hardening (20 HU vs 36.5 HU; P < .001). Contrast-to-noise ratio of enhanced kidney tissue was improved with PCD iodine mapping compared with EID (5.2 ± 1.3 vs 4.0 ± 1.3; P < .001). The performance of PCD showed no statistically significant difference compared with EID when the abdomen was evaluated in a conventional scan mode. PCD provides spectral information, which may be used for material decomposition.

Characterisation of Portuguese radiotherapy departments: Organisation, occupational exposure values and diagnostic reference levels for breast and prostate computed tomography planning

X-ray computed tomography (CT) imaging plays an essential role in disease diagnosis due to its noninvasive, painless mode and superior penetration depth. However, the resolution of the soft tissue ...

This study retrospectively analyzed the mean glandular dose (MGD) to 133 breasts from 132 subjects, all women, who participated in a clinical trial evaluating dedicated breast CT in a diagnostic population. The clinical trial was conducted in adherence to a protocol approved by institutional review boards and the study participants provided written informed consent. Individual estimates of MGD to each breast from dedicated breast CT was obtained by combining x-ray beam characteristics with estimates of breast dimensions and fibroglandular fraction from volumetric breast CT images, and using normalized glandular dose coefficients. For each study participant and for the breast corresponding to that imaged with breast CT, an estimate of the MGD from diagnostic mammography (including supplemental views) was obtained from the DICOM image headers for comparison. This estimate uses normalized glandular dose coefficients corresponding to a breast with 50% fibroglandular weight fraction. The median fibroglandular weight fraction for the study cohort determined from volumetric breast CT images was 15%. Hence, the MGD from diagnostic mammography was corrected to be representative of the study cohort. Individualized estimates of MGD from breast CT ranged from 5.7 to 27.8 mGy. Corresponding to the breasts imaged with breast CT, the MGD from diagnostic mammography ranged from 2.6 to 31.6 mGy. The mean (± inter-breast SD) and the median MGD (mGy) from dedicated breast CT exam were 13.9 ± 4.6 and 12.6, respectively. For the corresponding breasts, the mean (± inter-breast SD) and the median MGD (mGy) from diagnostic mammography were 12.4 ± 6.3 and 11.1, respectively. Statistical analysis indicated that at the 0.05 level, the distributions of MGD from dedicated breast CT and diagnostic mammography were significantly different (Wilcoxon signed ranks test, p = 0.007). While the interquartile range and the range (maximum–minimum) of MGD from dedicated breast CT was lower than diagnostic mammography, the median MGD from dedicated breast CT was approximately 13.5% higher than that from diagnostic mammography. The MGD for breast CT is based on a 1.45 mm skin layer and that for diagnostic mammography is based on a 4 mm skin layer; thus, favoring a lower estimate for MGD from diagnostic mammography. The median MGD from dedicated breast CT corresponds to the median MGD from four to five diagnostic mammography views. In comparison, for the same 133 breasts, the mean and the median number of views per breast during diagnostic mammography were 4.53 and 4, respectively. Paired analysis showed that there was approximately equal likelihood of receiving lower MGD from either breast CT or diagnostic mammography. Future work will investigate methods to reduce and optimize radiation dose from dedicated breast CT.

μWe introduce a novel hybrid prototype scanner built to explore benefits of the quantum-counting technique in the context of clinical CT. The scanner is equipped with two measurement systems. One is a CdTe-based counting detector with 22cm field-of-view. Its revised ASIC architecture allows configuration of the counter thresholds of the 225m small sub-pixels in chess patterns, enabling data acquisition in four energy bins or studying high-flux scenarios with pile-up trigger. The other one is a conventional GOS-based energy-integrating detector from a clinical CT scanner. The integration of both detection technologies in one CT scanner provides two major advantages. It allows direct comparison of image quality and contrast reproduction as well as instantaneous quantification of the relative dose usage and material separation performance achievable with counting techniques. In addition, data from the conventional detector can be used as complementary information during reconstruction of the images from the counting device. In this paper we present CT images acquired with the hybrid prototype scanner, illustrate its underlying conceptual methods, and provide first experimental results quantifying clinical benefits of quantum-counting CT.

170 Background: We have conducted the prospective multicenter study to evaluate the usefulness of breast CT in delineating tumor extent and preoperatively determining the optimal surgical procedure (Sadako Akashi-Tanaka et al, Ann Surg in press). Breast CT, carried out in the supine position, was useful since breast CT correctly changed the extent of surgery in 13.1% of patients. Here, we present the in-breast tumor recurrence (IBTR) of these patients undergoing CT guided breast conserving surgery. Methods: The follow-up records of 271 women treated with local excision (complete removal of gross tumor with a margin) for breast cancer at 3 Japanese hospitals were reviewed. CT guided surgery was performed as follows; the surgeon marked the line of planned excision prior to CT on the skin, which was also recorded on the CT image. Contrast-enhanced breast CT was performed in the supine surgical position. The CT results were used to determine the extent of surgery. IBTR was defined as a recurrence in the treated breast without regional or distant metastases. Results: The median age at surgery of them was 55 years (range, 21 to 88 years). The median palpable tumor size was 1.6cm (range, 0 to 3.5 cm). Tumor histology was as follows: ductal carcinoma in situ 13, invasive ductal carcinoma 234, invasive lobular carcinoma 10, mucinous carcinoma 6, and special type 8. The median follow-up after treatment was 3.8 years (range, 3.0 to 5.3 years). The rate of IBTR was 10/271 (3.7%). The 3.8-year rate of IBTR was 4.5%. Discussion: Without prospective randomized controlled studies, it is unlikely that a definitive conclusion can be reached on whether imaging-guided diagnosis of tumor extent will reduce the rate of IBTR. However, it seems almost ethically impossible to conduct such a clinical study in Japan, because preoperative imaging-guided diagnosis of tumor extent is routinely performed prior to surgery. Conclusions: Although this was not the randomized controlled study, CT-based preoperative diagnosis of tumor extent has the potential to improve the accuracy of breast-conserving surgery. The long-term results of IBTR need to be assessed.

Improving the spatial resolution in CZT detectors using charge sharing effect and transient signal analysis: Simulation study

Although screening mammography has been shown to be effective in reducing breast cancer mortality, a new technique called breast computed tomography (CT) is being studied in the hope that breast cancer can be detected even earlier. A prototype unit has been designed, fabricated and tested at the University of California, Davis, USA, and is currently being used in a Phase II clinical trial to study the feasibility of breast CT for breast cancer detection and diagnosis. A total of 46 volunteers and patients have been imaged, and the breast CT images show impressive anatomical detail of the breast that is not appreciated in mammography. The radiation dose levels needed to produce excellent image quality are equal to two-view mammography. Further study of breast CT is needed to better understand its potential role in breast cancer screening and diagnosis.

Demonstration of multiple contrast agent imaging for the next generation color X-ray CT

Cadmium Zinc Telluride (CD1-xZnxTe has become a crucial material for x-ray and gamma ray detection due to its wide band-gap, high atomic number and high density, which offer high efficiency and sharp spectroscopic resolution at room temperature. In addition, due to being lattice matched, it can also be used as substrate for the epitaxial growth of HgCdTe that can be used for infrared detection with high resolution. Hence, increasing the single crystal yield of CdZnTe from the grown ingot gained importance for the development of such detectors. In this study, a combination of modeling and experimental approaches has been developed in order to obtain high quality CdZnTe bulk crystals with good single crystal yield. A multi-zone Vertical Gradient Freeze (VGF) furnace was used for CdZnTe growth experiments. A global temperature model of the multi-zone furnace including complete geometry was employed using CrysMAS crystal growth modeling software. The correlation studies between the model and experimental behavior of the furnace are discussed in order to create a reliable model for temperature predictions. Temperature models were also included solid-liquid interface study in order to observe the interface shape at various stages of growth which would provide valuable insight about the quality and the yield of the ingot. Growth parameters and crucible geometries were estimated by CrysMAS simulations and interchanged between experiments. Effectiveness of temperature models and simulations was supported by experimental results such as single-crystalline yield, grain evolution and crystalline quality comparison by DCRC measurements of five successful crystal growths with moderate single crystal grain sizes.

Abstract

PurposeTo develop and evaluate a new automatic classification algorithm able to identify voxels containing skin, vasculature, adipose and fibroglandular tissue in dedicated breast CT images.MethodsThe proposed algorithm combines intensity and region-based segmentation methods with energy minimizing splines and unsupervised data mining approaches for classifying and segmenting the different tissue types. Breast skin segmentation is achieved by a region growing method which uses constraints from the previously extracted skin centerline to add robustness to the model and to reduce the false positive rate. An energy minimizing active contour model is then used to classify adipose tissue voxels by including gradient flow and region-based features. Finally, blood vessels are separated from fibroglandular tissue by a k-means clustering algorithm based on automatically extracted shape-based features. To evaluate the accuracy of the algorithm, two sets of 15 different patient breast CT scans, each acquired with different breast CT systems and acquisition settings, were obtained. Three slices from each scan were manually segmented under the supervision of an experienced breast radiologist and considered the gold standard. Comparisons with manual segmentation were quantified using five similarity metrics: Dice Similarity Coefficient (DSC), sensitivity, conformity coefficient, and two Hausdorff distance measures. To evaluate the robustness to image noise, the segmentation was repeated after separately adding Gaussian noise with increasing standard deviation (in four steps, from 0.01 to 0.04) to an additional 15 slices from the first dataset. In addition, to evaluate vasculature classification, three different pre- and post-contrast injection patient breast CT images were classified and compared. Finally, DSC was also used for quantitative comparisons with previously proposed approaches for breast CT tissue classification using ten images from the first dataset.ResultsThe algorithm showed a high accuracy in classifying the different tissue types for both breast CT systems, with an average DSC of 95% and 90% for the first and second image dataset, respectively. Furthermore, it demonstrated to be robust to image noise with a robustness to image noise of 85%, 83%, 79%, and 71% for the images corrupted with the four increasing noise levels. Previous methods for breast tissues classification resulted, for the tested dataset, in an average global DSC of 87%, while our approach resulted in a global average DSC of 94.5%.ConclusionsThe proposed algorithm resulted in accurate and robust breast tissue classification, with no prior training or threshold setting. Potential applications include breast density quantification and tissue pattern characterization (both biomarkers of cancer development), simulation-based radiation dose analysis and patient data-based phantom design, which could be used for further breast imaging research.