Photon counting detectors (PCDs) with energy discrimination capabilities have been developed for medical x-ray computed tomography (CT) and x-ray (XR) imaging. Using detection mechanisms that are completely different from the current energy integrating detectors and measuring the material information of the object to be imaged, these PCDs have the potential not only to improve the current CT and XR images, such as dose reduction, but also to open revolutionary novel applications such as molecular CT and XR imaging. The performance of PCDs is not flawless, however, and it seems extremely challenging to develop PCDs with close to ideal characteristics. In this paper, the authors offer our vision for the future of PCD-CT and PCD-XR with the review of the current status and the prediction of (1) detector technologies, (2) imaging technologies, (3) system technologies, and (4) potential clinical benefits with PCDs.

Purpose: Recently, novel CdTe photon counting x-ray detectors ͑PCXDs͒ with energy discrimination capabilities have been developed. When such detectors are operated under a high x-ray flux, however, coincident pulses distort the recorded energy spectrum. These distortions are called pulse pileup effects. It is essential to compensate for these effects on the recorded energy spectrum in order to take full advantage of spectral information PCXDs provide. Such compensation can be achieved by incorporating a pileup model into the image reconstruction process for computed tomography, that is, as a part of the forward imaging process, and iteratively estimating either the imaged object or the line integrals using, e.g., a maximum likelihood approach. The aim of this study was to develop a new analytical pulse pileup model for both peak and tail pileup effects for nonparalyzable detectors. Methods: The model takes into account the following factors: The bipolar shape of the pulse, the distribution function of time intervals between random events, and the input probability density function of photon energies. The authors used Monte Carlo simulations to evaluate the model. Results: The recorded spectra estimated by the model were in an excellent agreement with those obtained by Monte Carlo simulations for various levels of pulse pileup effects. The coefficients of variation ͑i.e., the root mean square difference divided by the mean of measurements͒ were 5.3%-10.0% for deadtime losses of 1%-50% with a polychromatic incident x-ray spectrum. Conclusions:The proposed pulse pileup model can predict recorded spectrum with relatively good accuracy.

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Purpose:Recently, photon counting x-ray detectors ͑PCXDs͒ with energy discrimination capabilities have been developed for potential use in clinical computed tomography ͑CT͒ scanners. These PCXDs have great potential to improve the quality of CT images due to the absence of electronic noise and weights applied to the counts and the additional spectral information. With high count rates encountered in clinical CT, however, coincident photons are recorded as one event with a higher or lower energy due to the finite speed of the PCXD. This phenomenon is called a "pulse pileup event" and results in both a loss of counts ͑called "deadtime losses"͒ and distortion of the recorded energy spectrum. Even though the performance of PCXDs is being improved, it is essential to develop algorithmic methods based on accurate models of the properties of detectors to compensate for these effects. To date, only one PCXD ͑model DXMCT-1, DxRay, Inc., Northridge, CA͒ has been used for clinical CT studies. The aim of that study was to evaluate the agreement between data measured by DXMCT-1 and those predicted by analytical models for the energy response, the deadtime losses, and the distorted recorded spectrum caused by pulse pileup effects. Methods: An energy calibration was performed using 99m Tc ͑140 keV͒, 57 Co ͑122 keV͒, and an x-ray beam obtained with four x-ray tube voltages ͑35, 50, 65, and 80 kVp͒. The DXMCT-1 was placed 150 mm from the x-ray focal spot; the count rates and the spectra were recorded at various tube current values from 10 to 500 A for a tube voltage of 80 kVp. Using these measurements, for each pulse height comparator we estimated three parameters describing the photon energy-pulse height curve, the detector deadtime , a coefficient k that relates the x-ray tube current I to an incident count rate a by a = k ϫ I, and the incident spectrum. The mean pulse shape of all comparators was acquired in a separate study and was used in the model to estimate the distorted recorded spectrum. The agreement between data measured by the DXMCT-1 and those predicted by the models was quantified by the coefficient of variation ͑COV͒, i.e., the root mean square difference divided by the mean of the measurement. Results: Photon energy versus pulse height curves calculated with an analytical model and those measured using the DXMCT-1 were in agreement within 0.2% in terms of the COV. The COV between the output count rates measured and those predicted by analytical models was 2.5% for deadtime losses of up to 60%. The COVs between spectra measured and those predicted by the detector model were within 3.7%-7.2% with deadtime losses of 19%-46%. Conclusions: It has been demonstrated that the performance of the DXMCT-1 agreed exceptionally well with the analytical models regarding the energy response, the count rate, and the recorded spectrum with pulse pileup effects. These models will be useful in developing methods to compensate for these effects in PCXD-based clinical CT systems.

Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the z direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi-slice CT. Two helical interpolation methods for single-slice CT, 360LI and 180LI, were used a starting points and extended to multi-slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan-beam reconstruction. Optimized sampling scan refers to a special type of multi-slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the z direction. Filter interpolation refers to a filtering process performed in the z direction using several data. The normal fan-beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four-array multi-slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single-slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination.

Purpose: The objective of the study was to demonstrate that, in x-ray computed tomography ͑CT͒, more than two types of materials can be effectively separated with the use of an energy resolved photon-counting detector and classification methodology. Specifically, this applies to the case when contrast agents that contain K-absorption edges in the energy range of interest are present in the object. This separation is enabled via the use of recently developed energy resolved photoncounting detectors with multiple thresholds, which allow simultaneous measurements of the x-ray attenuation at multiple energies. Methods: To demonstrate this capability, we performed simulations and physical experiments using a six-threshold energy resolved photon-counting detector. We imaged mouse-sized cylindrical phantoms filled with several soft-tissue-like and bone-like materials and with iodine-based and gadolinium-based contrast agents. The linear attenuation coefficients were reconstructed for each material in each energy window and were visualized as scatter plots between pairs of energy windows. For comparison, a dual-kVp CT was also simulated using the same phantom materials. In this case, the linear attenuation coefficients at the lower kVp were plotted against those at the higher kVp. Results: In both the simulations and the physical experiments, the contrast agents were easily separable from other soft-tissue-like and bone-like materials, thanks to the availability of the attenuation coefficient measurements at more than two energies provided by the energy resolved photon-counting detector. In the simulations, the amount of separation was observed to be proportional to the concentration of the contrast agents; however, this was not observed in the physical experiments due to limitations of the real detector system. We used the angle between pairs of attenuation coefficient vectors in either the 5-D space ͑for non-contrast-agent materials using energy resolved photon-counting acquisition͒ or a 2-D space ͑for contrast agents using energy resolved photon-counting acquisition and all materials using dual-kVp acquisition͒ as a measure of the degree of separation. Compared to dual-kVp techniques, an energy resolved detector provided a larger separation and the ability to separate different target materials using measurements acquired in different energy window pairs with a single x-ray exposure. Conclusions: We concluded that x-ray CT with an energy resolved photon-counting detector with more than two energy windows allows the separation of more than two types of materials, e.g., soft-tissue-like, bone-like, and one or more materials with K-edges in the energy range of interest. Separating material types using energy resolved photon-counting detectors has a number of advantages over dual-kVp CT in terms of the degree of separation and the number of materials that can be separated simultaneously.

We compare the performance of low-tube voltage with the hybrid iterative reconstruction (iDose) with standard- and low-tube voltage with the filtered backprojection (FBP) using phantoms at CT coronary angiography (CTCA). At CTCA, application of the combined low-tube voltage with iDose resulted in significant image quality improvements compared to the low-tube voltage with FBP. Image quality was the same or better despite a reduction in the radiation dose by 76% compared with standard-tube voltage with FBP.

Multislice helical computed tomography (CT) substantially reduces scanning time. However, the temporal resolution of individual images is still insufficient for imaging rapidly moving organs such as the heart and adjacent pulmonary vessels. It may, in some cases, be worse than with current single-slice helical CT. The purpose of this study is to describe a novel image reconstruction algorithm to improve temporal resolution in multislice helical CT, and to evaluate its performance against existing algorithms. The proposed image reconstruction algorithm uses helical interpolation followed by data weighting based on the acquisition time. The temporal resolution, the longitudinal (z-axis) spatial resolution, the image noise, and the in-plane image artifacts created by a moving phantom were compared with those from the basic multislice helical reconstruction (helical filter interpolation, HFI) algorithm and the basic single-slice helical reconstruction algorithm (180 degrees linear interpolation, 180LI) using computer simulations. Computer simulation results were verified with CT examinations of the heart and lung vasculature using a 0.5 second multislice scanner. The temporal resolution of HFI algorithm varies from 0.28 and 0.86 s, depending on helical pitch. The proposed method improves the resolution to a constant value of 0.29 s, independent of pitch, allowing moving objects to be imaged with reduced blurring or motion artifacts. The spatial (z) resolution was slightly worse than with the HFI algorithm; the image noise was worse than with the HFI algorithm but was comparable to axial (step-and-shoot) CT. The proposed method provided sharp images of the moving objects, portraying the anatomy accurately. The proposed algorithm for multislice helical CT allowed us to obtain CT images with high temporal resolution. It may improve the image quality of clinical cardiac, lung, and vascular CT imaging.