Photon Counting CT: Clinical Applications and Future Developments

Hsieh, Scott S.; Leng, Shuai; Rajendran, Kishore; Tao, Shengzhen; McCollough, Cynthia H.

doi:10.1109/trpms.2020.3020212

Cited by 101 publications

(77 citation statements)

References 104 publications

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“…Photon-counting detectors not only allow for the simultaneous acquisition of multiple energy bins but also provide a variety of other benefits. Popular examples include but are not limited to a reduction in radiation and contrast media dose [32][33][34]. Hence, our experiments provide guidelines for threshold settings maximizing image quality in iodine maps, even if a dual-energy decomposition is only performed retrospectively.…”

Section: Discussionmentioning

confidence: 98%

Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

et al. 2021

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Objective To evaluate the dual-energy (DE) performance and spectral separation with respect to iodine imaging in a photon-counting CT (PCCT) and compare it to dual-source CT (DSCT) DE imaging. Methods A semi-anthropomorphic phantom extendable with fat rings equipped with iodine vials is measured in an experimental PCCT. The system comprises a PC detector with two energy bins (20 keV, T) and (T, eU) with threshold T and tube voltage U. Measurements using the PCCT are performed at all available tube voltages (80 to 140 kV) and threshold settings (50–90 keV). Further measurements are performed using a conventional energy-integrating DSCT. Spectral separation is quantified as the relative contrast media ratio R between the energy bins and low/high images. Image noise and dose-normalized contrast-to-noise ratio (CNRD) are evaluated in resulting iodine images. All results are validated in a post-mortem angiography study. Results R of the PC detector varies between 1.2 and 2.6 and increases with higher thresholds and higher tube voltage. Reference R of the EI DSCT is found as 2.20 on average overall phantoms. Maximum CNRD in iodine images is found for T = 60/65/70/70 keV for 80/100/120/140 kV. The highest CNRD of the PCCT is obtained using 140 kV and is decreasing with decreasing tube voltage. All results could be confirmed in the post-mortem angiography study. Conclusion Intrinsically acquired DE data are able to provide iodine images similar to conventional DSCT. However, PCCT thresholds should be chosen with respect to tube voltage to maximize image quality in retrospectively derived image sets. Key Points • Photon-counting CT allows for the computation of iodine images with similar quality compared to conventional dual-source dual-energy CT. • Thresholds should be chosen as a function of the tube voltage to maximize iodine contrast-to-noise ratio in derived image sets. • Image quality of retrospectively computed image sets can be maximized using optimized threshold settings.

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Section: Discussionmentioning

confidence: 98%

Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

et al. 2021

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“…Medical imaging technology plays a great role in disease diagnosis, in which computed tomography (CT) imaging is widely used in clinical medicine [ 7 ]. At present, the three-dimensional reconstruction of skull CT data is usually carried out in the research on the relationship between bony orbital changes and aging.…”

Section: Discussionmentioning

confidence: 99%

Aging of Chinese bony orbit: automatic calculation based on UNet++ and connected component analysis

et al. 2022

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Purpose Current research on the aging of bony orbit is usually done manually, which is inefficient and has a large error. In this paper, automatic segmentation of bony orbit based on deep learning and automatic calculation of the parameters of the segmented orbital contour (area and height of bony orbit) are presented. Methods The craniofacial CT scanning data of 595 Chinese were used to carry out three-dimensional reconstruction and output the craniofacial images. The orbital contour images are obtained automatically by UNet++ segmentation network, and then the bony orbital area and height were calculated automatically by connected component analysis. Results The automatic segmentation method has an Intersection of Union of 95.41% in craniofacial CT images. During the aging, the bony orbital area of males increased with age, while that of females decreased, and the area in male was larger than that in female ( P < 0.05). The distance from equal points 10 and 40–90 to the supraorbital rim was significantly larger ( P < 0.05). Except for the equal point 90, the distance from equal points to the inferior orbital rim was obviously larger ( P < 0.05). In the females, the distance from equal points 50–70 to inferior orbital rim was significantly lower ( P < 0.05). Conclusion The method proposed here can automatically and accurately study image dataset of large-scale bony orbital CT imaging. UNet++ can achieve high-precision segmentation of bony orbital contours. The bony orbital area of Chinese changes with aging, and the bony orbital height changes different between males and females, which may be caused by the different position and degree of orbital bone resorption of males and females in the process of aging.

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“…Baseline restoration would suppress dynamic noise floor fluctuations and affect the output of low-energy windows. (5) This study was conducted with a sufficiently large number of counts per reading recorded. The condition was chosen to make the CRLB analysis valid: It has been shown that if only a few counts on average per reading were recorded, the asymptotic property of maximum-likelihood would not hold and estimated results might be biased, 46 which in turn, would violate the foundation of the CRLB analysis: the existence of an unbiased estimator.…”

Section: Discussionmentioning

confidence: 99%

Assessment of multi‐energy inter‐pixel coincidence counters for photon‐counting detectors at the presence of charge sharing and pulse pileup: A simulation study

Taguchi

Iwanczyk

2021

Medical Physics

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Purpose Spectral distortion due to charge sharing (CS) and pulse pileup (PP) in photon‐counting detectors (PCDs) degrades the quality of PCD data. We recently proposed multi‐energy inter‐pixel coincidence counters (MEICC) that provided spectral cross‐talk information related to CS. When PP was absent, the normalized Cramér–Rao lower bounds (nCRLBs) of 225‐µm pixel PCDs with MEICC was comparable to those of 450‐µm pixel PCD without MEICC. The aim of this study was to assess the performance of PCDs with MEICC in the presence of both CS and PP using computer simulations. Methods An in‐house Monte Carlo program was modified to incorporate the following four temporal elements: (1) A pulse shape with a pulse duration of 20 ns, (2) delays of up to 10 ns in anode arrival times when photons were incident on pixel boundaries, (3) offsets proportional to a vertical separation between the primary and secondary charge clouds at the rate of ±4 ns per ±100 µm, and (4) a stochastic fluctuation of anode arrival times for all of the charge clouds with a standard deviation of 2 ns. We assessed the performance of five PCDs, (a)–(f), for three spectral tasks, (A)–(C): (a) The conventional PCD, (b) a PCD with MEICC, (c) a PCD with one coincidence counter (1CC), (d) a PCD with a 3 × 3 analog charge summing scheme (ACS), and (e) a PCD with a 3 × 3 digital count summing scheme (DCS); (A) conventional CT imaging with water (i.e., linear attenuation coefficient maps), (B) water–bone material decomposition, and (C) K‐edge imaging with tungsten. The tube current was changed from 1 mA to 1000 mA and the nCRLB was assessed. Results The recorded count rate curves were fitted by the non‐paralyzable detection model with the effective deadtime parameter. The best fit was achieved by 25.8 ns for the conventional PCD, 18.6 ns for MEICC and 1CC, 140.5 ns for ACS, and 209.0 ns for DCS. The nCRLBs were strongly dependent on count rates. MEICC provided the best nCRLBs for all of the imaging tasks over the count rate range investigated except for a few conditions such as K‐edge imaging at 1 mA. PP decreased the merit of MEICC over the conventional PCD in addressing CS. Nonetheless, MEICC consistently provided better nCRLBs than the conventional PCD did. The nCRLBs of MEICC were in the range of 49–58% of those of the conventional PCD for K‐edge imaging, 45–76% for water–bone material decomposition, and 81–88% for the conventional CT imaging (i.e., linear attenuation coefficient maps). ACS provided better nCRLBs than the conventional PCD did only when the effect of PP was minor (e.g., when the counting efficiency of the conventional PCD was higher than 0.95 with the tube current of up to 100 mA). Conclusion Besides a few cases, MEICC provides the best nCRLBs for all of the tasks at all of the count rates. ACS and DCS provide better nCRLBs than the conventional PCD does only when count rates are very low.

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Photon Counting CT: Clinical Applications and Future Developments

Cited by 101 publications

References 104 publications

Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system

Aging of Chinese bony orbit: automatic calculation based on UNet++ and connected component analysis

Assessment of multi‐energy inter‐pixel coincidence counters for photon‐counting detectors at the presence of charge sharing and pulse pileup: A simulation study

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