Characterization of time of flight and resolution modeling on image quality in positron emission tomography.

Time-of-flight (TOF) and resolution modeling (RM) algorithms are frequently used in clinical PET images, and inclusion of these corrections should measurably improve image quality. We quantified the effects of these correction algorithms on reconstructed images via the following metrics: recovery coefficients (RCs), contrast-to-noise ratio (CNR), noise-power spectrum (NPS), modulation transfer function (MTF), and the full width at half maximum (FWHM) of a point source. The goal of this experiment was to assess the effects of the correction algorithms when applied singly or together. Two different phantom tests were performed and analyzed by custom software. FWHM and MTF were measured using capillary tube point sources, while RCs, CNR, and NPS were measured using an image quality body phantom. Images were reconstructed with both TOF and RM, only TOF, only RM, or neither correction. The remaining reconstruction parameters used the standard clinical protocol. RM improved RCs, FWHM, and MTF, without increasing overall noise significantly. TOF improves CNR for small objects FWHM or MTF but did not decrease noise. RCs were not statistically improved by enabling these algorithms. Inclusion of both correction algorithms in image reconstruction provides an overall improvement to all metrics relative to the uncorrected image, but not by a significant margin in multiple aspects.

Theoretical comparison and optimization of cadmium telluride and gallium arsenide photon-counting detectors for contrast-enhanced spectral mammography.

Purpose: Most photon-counting detectors (PCDs) being developed use cadmium telluride (CdTe), which has nonoptimal characteristic x-ray emission with energies in the range used for breast imaging. New PCD using a gallium arsenide (GaAs) has been developed. Since GaAs has characteristic x-rays lower in energy than those of CdTe, it is hypothesized that this new PCD might be beneficial for spectral x-ray breast imaging. Approach: We performed simulations using realistic mammography x-ray spectra with both CdTe and GaAs PCDs. Five different experiments were conducted, each comparing the performance of CdTe and GaAs: (1) sensitivity of iodine quantification to charge cloud size and electronic noise, (2) effect of photon spectrum on iodine quantification, (3) effect of varying the number of energy bins, (4) a dose analysis to assess any possible dose reduction from using either detector, and (5) spectral performance of ideal CdTe and GaAs PCDs. For each study, 3 sets of 5000 noise realizations were used to calculate the Cramer-Rao lower bound (CRLB) of iodine quantification. Results: For all spectra studied, GaAs gave a lower CRLB for iodine quantification, with 10 of the 12 spectra showing a statistically significant difference ( p ≤ 0.05 ). The photon energy spectrum that optimized iodine detection for both detector materials was the 40 kVp beam with 2-mm Al filtration, which produced CRLBs of 0.282 cm 2 and 0.257 cm 2 for CdTe and GaAs, respectively, when using five energy bins. Conclusion: GaAs is a promising detector material for contrast-enhanced spectral mammography that offers better spectral performance than CdTe.

Accuracy and reproducibility of effective atomic number and electron density measurements from sequential dual energy CT.

PURPOSE: This study assesses the accuracy of effective atomic number (Zeff ) and electron density measurements acquired from dual energy CT and characterizes the response to clinically relevant variables representative of challenges in patient imaging, including: phantom size, material position within the phantom, variation over time, off-center positioning, and large cone beam angle. METHODS: The Gammex Multi-Energy CT head and body phantoms were used to measure Zeff and electron density from 35 rod inserts that mimic tissues and varying concentrations of iodine and calcium. Scans were performed on a Canon Aquilion ONE Genesis CT scanner over a period of 6 months using default dual energy protocols appropriate for each phantom size. Theoretical Zeff and electron density values were calculated using data provided by the phantom manufacturer and compared to the measurements. Sources of variance were separated and quantified to identify the influences of random photon statistics, ROI placement, and variation over time. A subset of measurements were repeated with the phantom shifted in the vertical and horizontal directions, and over all slices in the volumetric scan. RESULTS: All measurements showed strong correlation (r > 0.98) with their corresponding theoretical values; however, the system did demonstrate a bias of -0.58 atomic units in the body phantom and 0.28 atomic units in the head phantom for Zeff measurements. The mean absolute percent error (MAPE) was 6.3% for the body phantom and 3.2% for the head phantom. Electron density measurements of the body and head phantoms gave MAPE values of 4.6% and 1.0%, respectively. Zeff and electron density measurements significantly varied within the solid water background, showing a positional dependence within the phantom that dominated the total standard deviation in measurements. Zeff values dropped by 0.2 atomic units when the phantom was off-center; electron density measurements were less affected by phantom position. Along the z-axis, the accuracy drops off markedly at more than 50-60 mm from the central slice. CONCLUSION: The Canon dual energy system offers an accurate way of measuring the Zeff and electron density of clinically relevant materials. Accuracy could be improved further by calibration to remove bias, careful attention to centering within the FOV, and avoiding measurements at the edges of the cone beam.

Comparison of CT image quality between the AIDR 3D and FIRST iterative reconstruction algorithms: an assessment based on phantom measurements and clinical images.

Modern CT iterative reconstruction algorithms are transitioning from a statistical-based to model-based approach. However, increasing complexity does not ensure improved image quality for all indications, and thorough characterization of new algorithms is important to understand their potential clinical impacts. This study performs both quantitative and qualitative analyses of image quality to compare Canon's statistical-based Adaptive Iterative Dose Reduction 3D (AIDR 3D) algorithm to its model-based algorithm, Forward-projected model-based Iterative Reconstruction SoluTion(FIRST). A phantom was used to measure the task-specific modulation transfer function (MTFTask), the noise power spectrum (NPS), and the low-contrast object-specific CNR (CNRLO) for each algorithm using three dose levels and the convolution algorithm (kernel) appropriate for abdomen, lung, and brain imaging. Additionally, MTFTaskwas measured at four contrast levels, and CNRLOwas measured for two object sizes. Lastly, three radiologists participated in a preference study to compare clinical image quality for three study types: non-contrast abdomen, pulmonary embolism (PE), and lung screening. Nine questions related to the appearance of anatomical features or image quality characteristics were scored for twenty exams of each type. The behavior of both algorithms depended strongly on the kernel selected. Phantom measurements suggest that FIRST should be beneficial over AIDR 3D for abdomen imaging, but do not suggest a clear overall benefit to FIRST for lung or brain imaging; metrics suggest performance may be equivalent to or slightly favor AIDR 3D, depending on the size of the object being imaged and whether spatial resolution or low-contrast resolution is more important for the task at hand. Overall, radiologists strongly preferred AIDR 3D for lung screening, slightly preferred AIDR 3D for non-contrast abdomen, and had no preference for PE. FIRST was superior for the reduction of metal artifacts. Radiologist preference may be influenced by changes to noise texture.