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. Author manuscript; available in PMC: 2023 Apr 4.
Published in final edited form as: Eur Radiol. 2022 Jun 16;32(12):8579–8587. doi: 10.1007/s00330-022-08933-x

First-generation clinical dual-source photon-counting CT: ultra-low-dose quantitative spectral imaging

Leening P Liu 1,2, Nadav Shapira 1, Andrew A Chen 3,4, Russell T Shinohara 3,4, Pooyan Sahbaee 5, Mitchell Schnall 1, Harold I Litt 1, Peter B Noël 1
PMCID: PMC10071880  NIHMSID: NIHMS1881487  PMID: 35708838

Abstract

Objective

Evaluation of image characteristics at ultra-low radiation dose levels of a first-generation dual-source photon-counting computed tomography (PCCT) compared to a dual-source dual-energy CT (DECT) scanner.

Methods

A multi-energy CT phantom was imaged with and without an extension ring on both scanners over a range of radiation dose levels (CTDIvol 0.4–15.0 mGy). Scans were performed in different modes of acquisition for PCCT with 120 kVp and DECT with 70/Sn150 kVp and 100/Sn150 kVp. Various tissue inserts were used to characterize the precision and repeatability of Hounsfield units (HUs) on virtual mono-energetic images between 40 and 190 keV. Image noise was additionally investigated at an ultra-low radiation dose to illustrate PCCT’s ability to remove electronic background noise.

Results

Our results demonstrate the high precision of HU measurements for a wide range of inserts and radiation exposure levels with PCCT. We report high performance for both scanners across a wide range of radiation exposure levels, with PCCT outperforming at low exposures compared to DECT. PCCT scans at the lowest radiation exposures illustrate significant reduction in electronic background noise, with a mean percent reduction of 74% (p value ~ 10−8) compared to DECT 70/Sn150 kVp and 60% (p value ~ 10−6) compared to DECT 100/Sn150 kVp.

Conclusions

This paper reports the first experiences with a clinical dual-source PCCT. PCCT provides reliable HUs without disruption from electronic background noise for a wide range of dose values. Diagnostic benefits are not only for quantification at an ultra-low dose but also for imaging of obese patients.

Keywords: X-ray computed tomography, Radiation dosage, Diagnostic imaging

Introduction

After more than a decade of intensive research and development, photon-counting CT (PCCT) has now successfully crossed into clinical use [1]. With highly anticipated diagnostic benefits, one can foresee the replacement of current energy-integrating detectors ( EID) with energy-discriminating photon-counting technology over the next decade. Early studies conducted with prototypes [2–11] and first clinical PCCTs [12–23] have illustrated significant improvements in contrast to noise ratio (CNR), spatial resolution, structural visualization, quantitative imaging, and reductions in radiation dose. These improvements became available with the drastically different detector design that enables detection of individual x-ray photons and measurement of their energies [24–26]. Compared to conventional CT technology, PCCT allows for improvements in clinical day-to-day routine which go beyond the availability of spectral results from every scan. One of those unique features is the potential to acquire patient scans at low radiation dose levels while offering superior quantification capabilities.

In CT, Hounsfield units (HU) represent x-ray attenuation of various tissues and different endogenous and exogenous materials. When utilizing conventional CT scanners, HUs are frequently influenced by multiple factors, including acquisition parameters, vendor-specific beam shaping (polychromatic spectrum filtration), and patient habitus. Consequently, voxel values may not represent actual tissue densities, can be ambiguous, and lack ground truth. This limitation can theoretically be solved with use of dual-energy CT (DECT). However, the separation between high- and low-energy photons (spectral separation) in DECT can be suboptimal depending on patient habitus and employed dual-energy CT technology [27, 28]. Additionally, when imaging at ultra-low radiation dose levels, EIDs, utilized in conventional CTs and DECTs, are challenged by electronic background noise. The electronic noise background follows a Gaussian distribution where the mean and variance reflect the dark current and readout noise of the electronics [29, 30]. At the same time, the signal statistics for a polychromatic x-ray photon spectrum follows a compound Poisson distribution. Thus, HU measurements of voxel values remain uncertain in low-dose scenarios when utilizing dual-energy technology. On the contrary, PCCT theoretically allows removal of electronic background noise. Generally, electronic background noise influences the signal detection at the lower end of the energy spectrum, and it can therefore be removed by setting the low-energy PCCT signal threshold at around 25 keV [31].

The scope of this study is to characterize imaging capabilities at ultra-low radiation dose levels of a first-generation dual-source PCCT scanner (NAEOTOM Alpha, Siemens Healthineers) equipped with two photon-counting detectors. To illustrate improvements over the latest EID technology, all experiments were performed with a PCCT and a dual-source DECT scanner (SOMATOM Force, Siemens Healthineers). We present measurements performed with a multi-energy CT phantom to characterize the precision and repeatability of HUs for various tissue types over a range of radiation dose levels. Further, we investigate the noise behavior at an ultra-low radiation dose to illustrate PCCT’s ability to remove electronic background noise. Our results demonstrate the opportunity for quantitative imaging at ultra-low dose levels with PCCT, which may be key for improved diagnostics for many clinical applications, such as detection and characterization of lesions in oncology.

Methods

CT phantom

A phantom for CT performance evaluation (Multi-energy CT Phantom, Sun Nuclear) (Fig. 1) was imaged on two different CT systems. To evaluate the effect of patient habitus, experiments were performed with the inner phantom (20 cm diameter/small) and with the full oval-shaped phantom (30 × 40 cm/large). The phantom was equipped with interchangeable tissue-simulating inserts, which, for our experiments, included adipose, blood 70, blood 100, blood + iodine 2 mg/ml, blood + iodine 4 mg/ml, brain, calcium 50 mg/ml, iodine 2 mg/ml, iodine 5 mg/ml, and iodine 10 mg/ml. Inserts were described by elemental composition, electron density, and physical density provided by Sun Nuclear. These characteristics allowed for calculation of ground truth attenuation at any energy. See Fig. 1 for details on the corresponding position of the various inserts.

Fig. 1.

Fig. 1

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Experimental setup. A, D Photography of NAEOTOM Alpha and B, E SOMATOM Force with multi-energy CT phantom. C, F Reconstructed VMI 70 keV slice with numbered tissue-simulating inserts: 1, brain; 2, blood 100; 3, adipose; 4, iodine 2 mg/ml; 5, calcium 50 mg/ml; 6, blood + iodine 2 mg/ml; 7, iodine 10 mg/ml; 8, iodine 5 mg/ml; 9, blood 70; 10, blood + iodine 4 mg/ml

Image acquisition and reconstruction

Scans were performed on a first-generation dual-source PCCT and on a dual-source DECT. PCCT scans were performed in both single-source and dual-source modes while dual-energy scans were performed in two different modes of acquisition currently utilized in our clinical routine: 70/Sn150 kVp and 100/Sn150 kVp. The phantom, for both sizes (small/large), was placed in the isocenter of each individual scanner (Fig. 1). Data acquisition and reconstruction of the phantom was performed utilizing a standard clinical protocol (Table 1). Images were obtained, without using any exposure modulation, at multiple dose levels: CT dose index (CTDIvol) 0.4/0.6, 0.8, 1.2, 1.6, 2.0, 4.0, 6.0, 10.0, and 15.0 mGy. For some dual-energy scans, the rotation time was adjusted to match PCCT dose levels. Additionally, 0.6 mGy was the minimal available dose for the 100/Sn150 kVp acquisitions. Radiation dose (CTDIvol values) utilized in this study converts to an effective dose range between 0.26 and 13.50 mSv (k = 0.015 mSv mGy−1 cm−1) for an abdomen with a scan length of 60 cm. Each scan was repeated three times to account for the influence of statistical effects on the reconstructed results. Generated data included virtual mono-energetic images (VMI) at multiple energy levels exploiting the complete available energy range: 40, 50, 60, 70, 100, 150, and 190 keV.

Table 1.

Acquisition and reconstruction parameters

Scanner model NAEOTOM Alpha SOMATOM Force
Tube voltage 120 kVp (single-source, dual-source modes) 70/Sn150 kVp 100/Sn150 kVp
Rotation time 0.25 0.25/0.5 0.25/0.5
Spiral pitch factor 1 1 1
Collimation 144 × 0.4 mm 96 × 0.6 mm 96 × 0.6 mm
Slice thickness 3 mm 3 mm 3 mm
Iterative reconstruction QIR 32 ADMIRE 3 ADMIRE 3
Reconstruction filter Qr40 Qr40 Qr40
Reconstructed field of view 450 mm 450 mm 450 mm
Matrix size 512 × 512 512 × 512 512 × 512
Pixel spacing (in x and y) 0.88 mm 0.88 mm 0.88 mm
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Image analysis

To evaluate the stability of imaging characteristics (HU, noise) for each VMI energy level, ten consecutive central slices were selected for analysis. Regions of interest (ROI) were placed on each individual insert on a 15-mGy VMI 70 keV for each phantom size and scanner combination. These ROIs were then copied to VMIs of other energy levels and other dose levels from the corresponding phantom size and scanner combination. The mean across the three repeated scans (total of 30 slices) was subsequently calculated for each insert at each dose and VMI energy level to account for statistical effects. Analysis of the repeatability of imaging characteristics was performed by calculating mean HU differences relative to the HU obtained at a radiation dose level of 6.0 mGy. The relationship between relative differences in mean HU quantification and radiation dose was represented using a scatter plot for each insert and VMI energy level, where error bars represent a single standard deviation of the means (in each direction).

Further analysis of the effect of dose on spectral image characteristics was performed by evaluating root mean square errors (RMSE) across all radiation dose levels. For each insert and each VMI energy level, RMSE was calculated relative to the mean HU value across all dose levels, while the coefficient of variation was calculated as the ratio of the standard deviation to the mean CT number, i.e., attenuation quantifications relative to air (CT # = HU + 1000). Average coefficients of variation across the different material inserts were plotted against VMI energy levels to demonstrate differences in variation between VMI energy levels, phantom size, and scanner combinations.

To evaluate noise in all configurations, additional reconstructions of VMI 70 keV were acquired without iterative reconstruction (QIR and ADMIRE off for PCCT and DECT acquisitions, respectively). Noise was computed by averaging standard deviations of ROIs from three repeated scans (30 slices) for each individual insert and radiation dose combination. Values were represented in a scatter plot, with error bars corresponding to a single standard deviation (in each direction) between slices. Characterization of the noise was achieved by utilizing the inverse square relationship between radiation dose and image noise. This relationship corresponds with Poisson noise; deviation from this relationship at lower doses indicates the presence of non-negligible system noise, such as electronic noise. Noise corresponding to scans between 1.2 and 15 mGy was linearly fit against the inverse square of their corresponding CTDIvol values. RMSE values for each insert were calculated to emphasize differences between the predicted noise values (linear fit) and measured noise at lower dose levels (0.4/0.6 and 0.8 mGy). Values were visualized for each material insert in a scatter plot. The Shapiro-Wilk test was used to examine normality for percent reduction in non-Poisson noise, calculated as 100% minus the ratio between single-source or dual-source PCCT and 70/Sn150 kVp or 100/Sn150 kVp pair (p value of 0.10, 0.12, 0.47, and 0.33 for single-source PCCT relative to 70/Sn150 kVp, single-source PCCT relative to 100/Sn150 kVp, dual-source PCCT relative to 70/Sn150 kVp, and dual-source PCCT relative to 100/Sn150 kVp, respectively). As data did not show evidence of non-normality, four separate one-sample t tests were utilized to examine the significance of percent reduction in non-Poisson noise of single-source PCCT relative to 70/Sn150 kVp pair, single-source PCCT relative to 100/Sn150 kVp pair, dual-source PCCT relative to 70/Sn150 kVp pair, and dual-source PCCT relative to 100/Sn150 kVp pair. A p value less than 0.05 denoted significance.

Results

Results from the dose-dependent quantitative HU precision at 70 keV relative to the mean at CTDIvol of 6.0 mGy are summarized in Fig. 2. Each panel illustrates the results for the individual inserts with magnified regions for the low-dose regime (CTDIvol 0.4 to 5 mGy). Overall, we obtained a good agreement between the different spectral CT technologies (PCCT vs. DECT) with consistent results when comparing individual inserts. At lower dose values, considerable deviations of relative HUs can be detected for the larger patient size when imaged with DECT. Independent of patient habitus, PCCT and DECT performed similarly at higher radiation exposures, as differences due to phantom sizes became smaller with high values of CTDIvol.

Fig. 2.

Fig. 2

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Comparison of relative HU at VMI 70 keV versus CT dose index (CTDIvol) for individual insert and phantom sizes between PCCT and DECT. Note that the HU differences are relative to the 6.0 mGy scan. Enlarged low-dose sections visualize regions with the largest variations between scanners

Figure 3A presents the RMSE calculated relative to the mean across all radiation dose levels for VMI 70 keV data. For this evaluation, it can be concluded that comparable results are observed across scanner platforms for each individual insert. For the larger patient size, single-source and dual-source PCCT provided reduced average RMSE (0.96 ± 0.31 and 2.01 ± 0.96 HU, respectively) for VMI 70 keV across inserts compared to DECT with either 70/Sn150 kVp (20.32 ± 11.32 HU) or 100/Sn150 kVp (4.58 ± 1.87 HU). Coefficients of variation for each VMI energy level and scanner platform were calculated and are summarized for each insert in Table S1 (large patient size) and S2 (small patient size). Compared to earlier results where we focused on 70 keV data, in Fig. 3B, one can observe the average coefficient of variation for individual VMI energy levels. The previously observed trend that PCCT outpaces DECT for larger patient sizes can also be observed along the whole spectrum of VMIs.

Fig. 3.

Fig. 3

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Comprehensive overview of dose-dependent spectral HU quantification for PCCT and DECT. RMSE over all radiation exposure levels and VMIs versus individual inserts (A). Average coefficient of variation including all dose levels and inserts versus different VMIs (40 to 190 keV) (B). PCCT performance is marginally influenced by patient size when comparing to DECT

Image noise was evaluated as the standard deviation within an ROI for each of the material inserts. Figure 4 presents noise dependence on radiation dose level, phantom size, spectral technology, and acquisition type at VMI 70 keV. At high and medium radiation dose levels, comparable noise levels were observed for all spectral technologies and acquisition types per each phantom size. For the large phantom size, a transition occurs at lower radiation dose levels where the PCCT technology outperforms the dual-energy technology (both kVp pairs). To further analyze this transition, we analyzed the 70 keV noise dependence as a function of the inverse square root of the radiation dose, as shown in Fig. 5. At medium and high radiation dose levels where Poisson noise dominates and linear dependence is expected, linear fits to noise at these dose levels (higher than or equal to 1 mGy) demonstrated strong positive correlation for all four technologies (single-source PCCT, dual-source PCCT, 70/Sn150 kVp pair, 100/Sn150 kVp pair) with R2 values of 0.9564, 0.9882, 0.9976, and 0.9907, respectively. Thus, deviations from the expected linear correlation at low radiation doses indicated the non-negligible influence of electronic noise. Figure 5B presents RMSE values of noise assessments for low radiation dose levels (0.4 and 0.8 mGy for PCCT and the 70/Sn150 kVp pair, 0.6 and 0.8 mGy for the 100/Sn150 kVp pair) for all material inserts. For every insert, RMSE values of noise for PCCT were reduced in comparison to that for 70/Sn150 kVp and 100/Sn150 kVp pairs. We observed a significant reduction in non-Poisson, i.e., electronic, noise for the single-source PCCT scans, with mean percent noise reduction of 73% (p value 8.04 × 10−9) compared to the 70/Sn150 kVp pair acquisitions and 58% (p value 5.59 × 10−7) compared to the 100/Sn150 kVp pair acquisitions. More reduction was observed for dual-source PCCT scans, with mean percent noise reduction of 89% (p value 5.45 × 10−13) compared to the 70/Sn150 kVp pair acquisitions and 82% (p value 1.60 × 10−10) compared to the 100/Sn150 kVp pair acquisitions.

Fig. 4.

Fig. 4

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Comparison of noise levels at VMI 70 keV versus CTDIvol for individual insert and phantom sizes between PCCT and DECT. While comparable noise levels were observed for all scanners at high and medium radiation dose levels, at lower radiation dose levels, PCCT outperforms the dual-energy technology for the larger patient size

Fig. 5.

Fig. 5

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Analysis of noise dependance on radiation dose using linear fits and deviations from expected behavior from Poisson (quantum) distributed events. A Example of the noise dependence on the radiation dose of a single material insert (adipose) and linear fits using all CTDIvol ≥ 1 mGy data points (white area). Noise from low CTDIvol (< 1 mGy) data points (orange area) was not included in the linear fits. B Deviations from linear fits of the two lowest dose levels for different material inserts under different spectral acquisition modes. PCCT exhibits the lowest deviations, implying a small contribution of non-Poisson, e.g., electronic, noise sources

Discussion

This paper reports the first experience with a clinical dual-source PCCT scanner on spectral HU quantification and noise behavior at ultra-low dose levels. The presented results illustrate unique features which become available with clinical PCCT: (i) high precision of HU measurements for a wide range of inserts and radiation exposure levels and (ii) reduced influence of electronic background noise at ultra-low-dose acquisitions. We report high performance for both scanners along a wide range of radiation exposure levels with PCCT outperforming the latest-generation DECT at low exposures. Our data demonstrate that PCCT offers diagnostic benefits not only for quantification at ultra-low dose but also for imaging of morbidly obese patients. PCCT’s potential to reduce artifacts, such as rings, when imaging large patients has been previously demonstrated with a prototype scanner [32]. With the arrival of PCCT in the clinical arena, more accurate characterization of tissues and enhanced perfusion imaging at reduced radiation dose levels become routinely available.

The advent of PCCT has allowed for improved visualization and quantification on low-dose acquisitions. With the continued mission to reduce radiation dose to patients, particularly those who receive repeated scans, low-dose acquisitions are advantageous but have previously been marred by image quality concerns. However, Gutjahr et al reported, with a PCCT prototype, on noise and CNR behavior for clinically relevant dose levels and found similar noise behavior with improved CNR compared to EID acquisitions, enabling better delineation between structures [8]. Moreover, Leng et al demonstrated that high accuracy for iodine quantification (RMSE of 0.5 mg/ml) and accurate CT numbers in VMIs (percentage error of 8.9%) can be achieved in a range of CTDIvol between 9.1 and 42.9 mGy [10]. Several groups have also demonstrated the capabilities of low-dose PCCT for thoracic applications that were previously not feasible [9, 33–35].

In addition to characterizing low-dose imaging over the last decade, several investigators have reported on quantitative imaging potentials of PCCT, including improvements in existing capabilities of spectral CT and newer developments. Both of these avenues have included concerns about quantitative consistency, particularly around patient habitus effects and radiation dose. Existing spectral results, such as iodine density maps and VMIs, have illustrated accuracy with PCCT [10], and high-spatial-resolution imaging, particularly for thoracic imaging, can be achieved in a clinically accepted dose range [9, 33–35]. Furthermore, patient habitus–related effects, such as beam hardening, can be eliminated with PCCT, which allowed significantly improved HU accuracy [4]. With respect to new developments, K-edge imaging with PCCT can non-invasively determine the biodistribution of gold nanoparticles with high correlation to optical emission spectrometry [36]. These and several other contributions used prototype systems and played a significant role in the clinical translation by illustrating significant improvements of PCCT compared to CT equipped with EIDs. Our current work demonstrates that these potential advantages from a first-generation clinical PCCT may be applied to diagnostic imaging with confidence in quantification even with ultra-low-dose imaging and obese patients.

The present study has limitations. Due to the vast increase in parameter space with PCCT, we only present an initial overview of ultra-low-dose capabilities (all data is available upon request). Future studies will be necessary to evaluate additional parameters such as iterative reconstruction level, contrast agent concentrations, and effect of high-spatial-resolution modes (spectral mode with high resolution unavailable with current system configuration) on quantitative PCCT spectral result performance. Concerning contrast agents, we have not evaluated the quantitative performance concerning K-edge agents, such as nanoparticles [37]. The ability to detect and quantitatively measure K-edge agents is essential to distinguish between two contrast agents, which is required for dual-contrast protocols [2, 38–44]. Our experiments were only performed with a geometric image quality phantom which lacks textures seen in clinical CT acquisitions. Ultimately, findings will be confirmed in the clinical routine, but as an intermediate step, we plan to utilize patient-based phantoms [45]. Finally, our study only includes the comparison to one DECT scanner. Other generations or implementation of DECT or conventional EID CT may provide different performance in the utilized radiation dose range for quantitative stability and noise. For example, in respect to noise, the different DECT technologies (dual-layer, rapid kVp switching, dual source) demonstrated specific noise characteristics with increases in VMI energy levels [46]. However, regardless of the DECT implementation, electronic noise still plagues images at low dose levels, marring quantification and image quality.

Conclusion

In conclusion, the present study reports on experimental evaluations of a first-generation dual-source PCCT scanner with a focus on quantitative imaging at ultra-low radiation dose levels. Compared to conventional CT and DECT, PCCT provides reliable HUs without disruption from electronic background noise for a wide range of dose values and patient sizes. With its high quantitative stability and low electronic noise, PCCT is an excellent tool for quantitative imaging in clinical practice.

Supplementary Material

supplement

Key Points.

  • PCCT scanners provide precise and reliable Hounsfield units at ultra-low dose levels.

  • The influence of electronic background noise can be removed at ultra-low-dose acquisitions with PCCT.

  • Both spectral platforms have high performance along a wide range of radiation exposure levels, with PCCT outperforming at low radiation exposures.

Acknowledgements

We acknowledge support through the National Institutes of Health (R01EB030494).

Funding

This study has received funding from the National Institutes of Health (R01EB030494).

Abbreviations

CNR

Contrast to noise ratio

DECT

Dual-energy CT

EID

Energy-integrating detectors

HU

Hounsfield units

PCCT

Photon-counting computed tomography

RMSE

Root mean square error

ROI

Region of interest

Footnotes

Conflict of interest The authors of this manuscript declare relationships with the following companies: Siemens Healthineers. Harold I. Litt, Peter B. Noël, and Mitch Schnall have a research agreement with Siemens Healthineers. Pooyan Sahbaee is an employee of Siemens Healthineers.

Guarantor The scientific guarantor of this publication is Dr. Peter B. Noël.

Statistics and biometry No complex statistical methods were necessary for this paper.

Informed consent Written informed consent was not required for this study because it did not involve human subjects.

Ethical approval Institutional Review Board approval was not required because this study only included phantoms.

Methodology

• Experimental

• performed at one institution

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00330-022-08933-x.

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