Increased image noise and radiation dose in pediatric high pitch cardiac CTA using photon counting detector CT compared to energy integrating detector CT. 

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Gladys M. Arguello Fletes, Wei Zhou, LaDonna J Malone, Andrea I Fuentealba Cargill, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6258330/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Sep, 2025 Read the published version in Pediatric Radiology → Version 1 posted 12 You are reading this latest preprint version Abstract Background Previous studies have shown improved image quality in pediatric cardiac imaging using photon-counting detector CT (PCDCT). However, these studies did not evaluate image quality and radiation dose when utilizing the full spectral capabilities of PCDCT scanners. Objective To compare image quality and radiation dose between high pitch cardiac CT using full spectral PCDCT and dual source energy-integrating detector CT (EIDCT). Methods This retrospective, IRB-approved study analyzed high pitch cardiac CTs from January 2021 to October 2023 in pediatric patients (< 18 years). Patients were scanned using either PCDCT with full spectral technique (“QuantumPlus”) or EIDCT. Radiation doses were measured by CT dose index (CTDI) and dose-length product (DLP). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were also calculated, and image quality was assessed using a 5-point Likert scale. Statistical analysis included unpaired T-test, Shapiro-Wilk test, Mann-Whitney test, and kappa coefficients for interrater agreement. Results 200 patients were evaluated, with 100 scanned on PCDCT and 100 on EIDCT. Most patients (148/200) were ≤ 12 months of age. CNR was similar between groups for both age groups. In patients ≤ 12 months, SNR was only significantly higher at the teres muscles for EIDCT (p < 0.0001). Radiation doses were significantly higher for PCDCT across both age groups (p < 0.0001). Conclusion High pitch cardiac CT with PCDCT using spectral processing resulted in higher radiation doses and lower SNR in infants compared to EIDCT. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Photon counting detector CT (PCDCT) has demonstrated clinical benefits compared to energy-integrating detector CT (EIDCT) in adult patients and more recently in pediatric patients [ 1 – 4 ]. PCDCT directly converts x-rays into electrical signal, enabling smaller detector elements and reducing electronic noise. This results in higher spatial resolution, better signal-to-noise ratio, and the ability to sort photons by energy level. Furthermore, the ability to measure the energy of incident photons provides additional post-acquisition reconstruction options including virtual mono-energetic reconstructions, virtual non-contrast images, and iodine maps among others. The spectral capabilities of the clinically available PCDCT system offer two different types of image acquisition, each with different technical requirements and reconstruction options [ 5 ]. PCDCT uses a relatively higher tube potential to obtain the full spectrum of photon energies for multienergy applications. This mode is described by vendor as “QuantumPlus” with the full array of spectral CT capabilities including virtual monoenergetic reconstruction at energies as low as 40 keV or as high as 190 keV; virtual non-contrast images (VNC) and iodine maps. However, currently these capabilities are restricted to acquisitions acquired at 120 or 140 kV. Quantum plus imaging has been standard in PCDCT in cardiac imaging in adults (1). Exams performed at 70 or 90 kV utilize another mode referred to by the vendor as “Quantum”; in this mode spectral capability is limited to only virtual monoenergetic reconstructions at energies less than the acquired energy, thus, there is no ability to reconstruct virtual non contrast images or an iodine map. Radiation dose modulation on PCDCT is achieved by automatic tube current modulation, automatic tube potential selection, and additionally the automatic selection of an energy level (kiloelectron volt) (CARE keV; Siemens Healthineers). At time of this study, this novel measure of energy level selection, was promoted as way of decreasing the radiation dose, that one would normally expect when selecting a higher kV. A recent prior study evaluating PCDCT in a pediatric congenital heart disease population, concluded that with a similar radiation dose, PCDCT has a higher SNR and CNR when compared to EIDCT, however their study only evaluated PCDCT scans performed at 70 and 90kV [ 3 ], and therefore did not evaluate scans performed with the full spectral “QuantumPlus” technique. At the time of acquisition of these studies, there was no available data regarding pediatric cardiac studies acquired utilizing the full spectral ability of PCDCT. Thus, in this study, we aimed to compare image quality metrics and radiation dose in a large population of pediatric patients who underwent high pitch cardiac CT on a PCDCT system with advanced spectral imaging (“QuantumPlus”) to avail of the full array of PCDCT capabilities, compared with those who underwent high pitch cardiac CT on a EIDCT system. Materials and Methods In October 2022, our existing EIDCT scanner was replaced with a state of art PCDCT scanner, one of the first PCDCTs installed in a standalone pediatric center at the time. In order to compare the performance of PCDCT to EIDCT, and following institutional review board (IRB) approval, a retrospective imaging and chart review of pediatric congenital heart disease patients who underwent a high pitch single beat cardiac CT between January 2021 and October 2023 was performed. Inclusion criteria were as follows: Patients aged < 18 years, who underwent a high pitch cardiac CT on either an EIDCT or using the QuantumPlus technique on a PCDCT. Patients who required repeat studies due to inadequate contrast quality or excessive motion, or patients who had a lower kV (Quantum) technique performed on PCDCT, were excluded. Cardiac CT Techniques PCDCT High pitch cardiac CT images were acquired at 120 kV, for the purpose of utilizing “QuantumPlus” reconstruction, to allow for generation of iodine maps and virtual non contrast images. Images were acquired on a dual-source PCDCT system (NAEOTOM Alpha, Siemens Healthineers. Erlangen, Germany). Collimation was 144 x 0.40 mm, Z axis coverage was from C4 to just below the costophrenic angles in all patients, Care KeV IQ level = 25, Virtual monoenergetic images were generated at 1 mm thickness with a medium kernel for vascular images (Bv48), parameters summarized in Table 2 . For this study, the 55 KeV datasets were chosen for comparison with EIDCT, as after an initial evaluation period of multiple KeVs, our consensus opinion was that this was KeV that provided most clinical value. Clinical indications where “quantum plus” was utilized included patients with metal artifacts, concern for thrombus and concern for abnormal differential of branch pulmonary artery blood flow. EIDCT High pitch cardiac CT images were acquired on a dual-source EIDCT system (Somatom definition Flash, Siemens Healthineers. Erlangen, Germany). The tube voltage was selected using a weight-based algorithm (70 kV for 0-10kg, 80 kV 10–30, 100 kV for 30–50 kg and 120 for > 50kg. Caredose 4D was used for tube current modulation with a quality reference mAS of 150, and the weight-based kV was chosen as the reference kV. Collimation was 128 x 0.6 mm, scan direction was foot to head, Z axis coverage was from C4 to just below the costophrenic angles. Image reconstructions at 1 mm using a standard soft tissue window reconstructions were performed (I30/Bv36), parameters shown in Table 1 . Table 1 CT Technique and reconstruction parameters PCDCT EIDCT Tube voltage (kV) 120 (n = 100) 70 (n = 93); 80 (n = 5); 100 (n = 2) Collimation (mm) 144 x 0.40 128 x 0.6 Rotation time (sec) 0.25 0.28 Pitch factor 3.2 3.4 Reconstruction Slice thickness (mm) 1 1 Kernel Bv48 I30/Br36 Iterative reconstruction QIR (3) SAFIRE (3) /ADMIRE (3) Window (HU) Center 200; window 600 Center 200; window 600 The iodinated contrast injection protocol was the same on both scanners, utilizing Iopamidol (Isovue-300) at 2ml/kg (max of 100ml) with an automated injection at 1.2ml/sec or greater through right upper or lower extremity peripheral IV. Regions of interest (ROI) were placed in either the left or right ventricle depending upon anatomy of primary interest for timing the scan. Image quality analysis Quantitative and qualitative metrics of image quality were assessed. Quantitative analysis of image quality (signal to noise and contrast to noise ratios) was performed on the clinical PACS viewing workstations (Synapse 5 Radiology PACS, Fujifilm Healthcare Americas Corporation), by a pediatric radiologist, using a previously validated technique [ 3 – 6 ]. Four regions of interest (ROIs) of at least a 20 mm^2 area was placed on bilateral teres minor and paraspinal muscles to calculate signal to noise ratio (SNR). SNR should remain consistent across all structures. We selected these muscles, rather than cardiovascular structures, because they should demonstrate minimal variation across studies, regardless of age or congenital anomaly. Image SNR was calculated as the mean Hounsfield units (HU) in the ROI divided by the standard deviations (SDs) of all ROIs positioned. Image contrast to noise ratio (CNR) was calculated using the following equation CNR = Mean aorta HU– mean pulmonary artery HU/mean SD aorta HU [ 3 – 6 ]. Examples of CNR and SNR are shown in Fig. 1 . Qualitative analysis of the imaging quality of the thoracic vessels was independently performed by two cardiac imagers (18 years and 18 months of cardiac CT experience respectively). Qualitative imaging evaluation was performed using deidentified 1 mm thick axial reconstructions presented in a randomized order with the readers blinded to the type of scanner used. Visualization of selected thoracic vessels was scored using a 5-point Likert scale according to vessel clarity (1 = non-distinguishable – 5 = excellent clarity). The vessels evaluated were thoracic aorta, first and second order pulmonary artery branches, proximal internal mammary arteries, SVC or IVC, and pulmonary veins. CTDI and DLP of each exam was obtained from vendor generated dose report in PACS. Effective dose in millisieverts (mSv) was calculated based on DLP and age-related conversion factor [ 8 ]. Statistical Analysis Based on an uneven patient age distribution favoring infants and babies, two age-based subgroups were created for analysis. The first group was 12 months of age and younger and the second group older than 12 months. For each age group, patients’ ages at time of PCDCT and EIDCT scan were compared using unpaired t-test. A Shapiro-Wilk test was performed to verify the normality for radiation dose and quantitative measurements (SNR and CNR). A Mann-Whitney test was used to compare differences of non-normally distributed datasets, including subjective image quality scores, between the 2 patient groups. Interrater agreement between the two readers for qualitative image quality measures were calculated using kappa coefficients and classified (less than 0.20 poor, 0.21–0.40 fair, 0.41–0.60 moderate, 0.61–0.80 good and 0.81-1.00 very good [ 9 ]. Kappa coefficient analyses were performed in an open-source Online Kappa Calculator ( http://justusrandolph.net/kappa/ tusrandolph.net). The rest of statistical analyses were performed in on open-source package (R Project, https://www.r-project.org/ ) and p < 0.05 was considered statistically significant. Results Two hundred patients met the inclusion criteria and were included in the analysis. Detailed patient demographics are listed in Table 2 . In summary, 100 patients (50%, n = 100/200,) underwent a high pitch cardiac CT scan with advanced spectral processing (QuantumPlus) on PCDCT. These patients had a median age of 4.4 months. (range: day of life 1 to 17.5 years), with slight female preponderance (f = 53%). Similarly, 100 patients (n = 100/200 or 50%) underwent a high pitch cardiac CT on EIDCT with a median age of 3.9 months (range: day of life 1 to 17.5 years) with a male preponderance (m = 65%). Of the 200 patients that underwent cardiac CT in the study period, the predominant age group encountered in both cohorts were infants and neonates aged 12 months and below, comprising 68% of PCDCT patients (n = 68/100) and 80% of EIDCT patients: n = 80/100. Table 2 Patient demographics Demographics PCDCT (N = 100) EIDCT (N = 100) P-value Male 47 65 0.01 Female 53 35 0.01 Age Range ≤ 12 months Total 68 80 0.05 Mean ± SD 0.23 ± 0.25 0.25 ± 0.29 0.64 > 12 months Total 32 20 0.05 Mean ± SD 7.28 ± 5.29 4.35 ± 4.85 0.05 SD = standard deviation Radiation Dose Radiation doses are shown in Table 3 . The radiation dose was significantly higher (p = < 0.001) for patients in both groups scanned with the full spectral capability on PCDCT when compared to age matched patients on the EIDCT scanner. The patients of 12 months and younger scanned in PCDCT group demonstrated considerably higher radiation dose with a median CTDI of 0.23 mGy (0.21–0.27 mGy) in comparison to 0.10 (0.10–0.12) mGy in the EIDCT group; and a median DLP of 4.00 mGycm (3.26–5.17 mGycm) compared to 1.80 mGycm (1.5–2.2 mGycm ) in the EIDCT group. The patients aged greater than 12 months scanned in PCDCT had a median CTDI of 0.80 mGy (0.50–2.01 mGy) in comparison to 0.16 mGy (0.14–0.50 mGy) in the EIDCT group; and a median DLP of 23.2 mGycm (10.23–50.87 mGycm) compared to 4.2 mGycm (2.8–11.2 mGycm) in the EIDCT group. Figure 2 and Table 3 . Table 3 Radiation doses are presented with median and the range between 1st and 3rd quartile PCDCT EIDCT P-value ≤ 12 months CTDIvol (mGy) 0.23 (0.21–0.27) 0.10 (0.10–0.12) < 0.0001 DLP (mGycm) 4.00 (3.26–5.17) 1.8 (1.5–2.2) 12 months CTDIvol (mGy) 0.80 (0.50–2.01) 0.16 (0.14–0.50) < 0.0001 DLP (mGycm) 23.2 (10.23–50.87) 4.2 (2.8–11.2) 0.0001 Image Quality Analysis SNR and CNR quantitative results are shown in Table 4 with summaries below. Notably, in patients aged 12 months and younger, there was significantly decreased SNR decreased in teres muscle (p = < 0.05) on the PCDCT compared to EIDCT. Figure 3 and Table 4 . However, in patients older than 12 months, there was no significant difference in SNR on PCDCT compared to EIDCT. Regardless of patient age, there was no significant difference in CNR between EIDCT and PCDCT. Figure 4 and Table 4 . Table 4 Comparison of image quality of PCDCT versus EIDCT. Quantitative image metrics are presented with median and the range between 1st and 3rd quartile Region of Interest Metric 12 months and younger Older than 12 months Signal to Noise Ratio Right teres minor muscle PCDCT 1.86 (1.43–2.64) 2.07 (1.48–2.84) EIDCT 2.22 (1.70–2.88) 1.94 (1.61–2.64) P-value 0.017 0.89 Left teres minor muscle PCDCT 1.83 (1.46–2.31) 2.05 (1.44–2.89) EIDCT 2.23 (1.69–2.91) 1.94 (1.31–2.44) P-value 0.006 0.47 Right paraspinal muscle PCDCT 1.94 (1.43–2.36) 2.16 (1.34–3.08) EIDCT 2.07 (1.52–2.84) 1.94 (1.10–2.64) P-value 0.08 0.36 Left paraspinal muscle PCDCT 1.91 (1.41–2.40) 1.83 (1.32–2.51) EIDCT 1.90 (1.44–2.48) 2.02 (1.63–2.72) P-value 0.56 0.64 Contrast to Noise Ratio Ascending aorta PCDCT 31.61 (23.48–39.70) 30.07 (24.58–39.17) EIDCT 32.14 (22.08–52.67) 25.27 (14.92–40.05) P-value 0.39 0.17 Pulmonary artery PCDCT 30.02 (21.54–38.03) 29.29 (20.27–35.96) EIDCT 33.58 (21.08–48.76) 22.54 (17.81–45.24) P-value 0.22 0.55 In terms of subjective image quality (Figs. 5 and 6 ), both PCDCT and EIDCT demonstrated excellent clarity of the thoracic aorta, pulmonary veins, and pulmonary arteries in patients greater than 12 months (median Likert scores: 5). Both PDCT and EIDCT demonstrated good clarity of the SVC/IVC (median Likert scores: 4). The internal mammary arteries were clearer on the EIDCT compared to PCDCT, median score of 4 (good clarity) on PCDCT and median score of 5 (excellent clarity) on EIDCT and the pulmonary arteries in patients less than 12 months of age and younger were clearer on the PCDCT (a median Likert score:5) compared to EIDCT (median Likert score:4.5). Overall percent agreement for the thoracic aorta clarity Likert score was 65% for with moderate interrater agreement (95% CI [0.48,0.65]). Overall percent agreement for pulmonary artery branches was 48.5% with fair interrater agreement (95% CI k = 0.27, 0.44). Overall percent agreement for internal mammary arteries was 36.5% for with poor interrater agreement (95% CI k = 0.12, 0.29). Overall percent agreement for pulmonary veins was 45.5% with fair interrater agreement (95% CI k = 0.23, 0.41). Overall percent agreement for IVC/SVC was 29% with poor interrater agreement (94% CI k = 0.03,0.19). Examples of both groups are shown in Figs. 5 and 6 . Discussion The purpose of this study was to compare image quality and radiation dose of the full spectral capability of PCDCT with EIDCT for cardiac CT in a pediatric population. In patients 12 months of age and younger, PCDCT using the full spectral “Quantum Plus” technique showed significantly higher radiation doses with significantly lower SNR compared to EIDCT. Prior work using phantom abdominal CT models showed that universal use of a 120 kV dual source high pitch protocol on the PCDCT system [ 10 ] had a lower radiation dose than similar phantom scans on the EIDCT, however our methodology differed by using actual cardiac CT patients rather than the phantom acquistion. Other recent work on this topic includes studies by Stålhammar et al [ 4 ] and Dirrichs et al [ 3 ]. Our findings and approach differ from these prior studies as follows. The study by Dirrichs et al [ 3 ], compared their preliminary experience of using PCDCT in 30 pediatric congenital heart disease patients aged up to 3 years compared to 84 patients who underwent an EIDCT scan. In their limited patient cohort, CNR and SNR were higher in PCDCT with lower radiation dose. However, they employed a 70kV based PCDCT technique “Quantum” with the resultant limited spectral capability; therefore, they did not evaluate the full spectral PCDCT technique “Quantum Plus” used in our study. Another recently published study by Stålhammar et al [ 4 ] concluded that pediatric cardiovascular PCDCT images for congenital heart defects had high diagnostic quality with low radiation dose. In this study PCDCT scans were performed at 70kV (n = 35; age 2 days–16 years) and 90 kV (n = 35; age 2 days–17 years); also, not utilizing the full spectral capability as in our study. Additionally, scans performed at 70kV were compared to those scanned at 90 kV and there was no control group and image analyses were based on subjective rather than quantitative analyses. The QuantumPlus technique allows generation of iodine maps and virtual non contrast images. In our experience, there may be some advantages for using a QuantumPlus technique in select pediatric cardiac patients. Iodine maps can help evaluate intrastent or baffle hypodensity and occlusion as well as decrease streak artifact within vascular stents. It also offers potential in assessing relative lung perfusion qualitatively and hopefully in the future quantitatively. Additionally, virtual non-contrast reconstructions can assist in evaluating contrast-related artifacts and differentiating calcifications from contrast enhancement. While there are potential benefits from using advanced spectral capability, in our study, this was at the expense of higher radiation dose and a lower SNR in young infants. Thus, an indication-based approach to using QuantumPlus is suggested to optimize the use of these capabilities to those specific patients who would most likely benefit from them. We acknowledge that our study has several limitations. First, we are comparing CNR and SNR from very different scanning and technology parameters which introduces several significant confounders. Reconstruction kernels were different between PCDCT and EIDCT. We utilized monoenergetic 55keV reconstructions for both our qualitative and quantitative analysis on the scans performed on PCDCT. While we expect SNR to be improved by measurements using a higher keV and CNR by a lower keV reconstruction closer to the k-edge of iodine, this was not tested in this study as the images are not clinically as helpful. The difference in kernel utilizing Bv48 on PCDCT versus I30/Bv36 on EIDCT may confound evaluation of signal to noise ratio. We acknowledge that pediatric PCDCT is a novel technology, and the optimal technical parameters have not yet been established, and we suggest that more evaluation of the potential effects of the various PCDCT kernels and differing monoenergetic reconstructions on signal to noise and radiation dose be performed. It is important to mention that our EIDCT radiation doses were comparatively low with a median CTDI of 0.10mGy in the 12 months old and younger group and 0.16mGy in the older than 12 months old age group, compared to other published studies [ 11 , 12 ]. These protocols have been optimized over several years continuing to evaluate adequate image quality and dose reduction. A study by Li et al had a median CTDI of 1.2 in patients less than 4 years of age using high-pitch dual-source cardiac CT [ 11 ]. Another study by Shirota et al utilizing a 320 row CT scanner, had a median CTDI of 0.45 in newborns, 0.52 in infants less than 1 year old and 0.78 in patients less than 5 years old [ 12 ]. The existing literature, while limited, would suggest that radiation dose and image quality may be reduced if using a Quantum rather than a QuantumPlus approach, particularly in the smallest patients. Thus, future studies comparing image quality and radiation dose in PCDCT for pediatric cardiac CT at 120kV versus 90kV and 70kV is suggested. Additionally, studies are needed to evaluate the potential clinical benefits that spectral reconstructions such as optimum virtual monoenergetic reconstruction as well as iodine maps, could add to diagnostic value of pediatric cardiac CT. Conclusion In conclusion, high pitch cardiac CT on PCDCT using the advanced spectral processing mode, resulted in a higher radiation dose compared to EIDCT and in infants was associated with decreased SNR. Further work is needed to establish optimal pediatric PCDCT cardiac CT scanning parameters, but considering these findings, it is suggested that advanced spectral processing mode is best reserved for select patients who may benefit from additional reconstructions such as virtual non contrast and iodine maps. Declarations Author Contribution G.M.AF -wrote the main manuscript textZ.W - was responsible for statistics and statistics figures L.J.M Prepared with the technique and protocolA.I.FC Responsible for including and excluding the casesJ.P.W Wrote the new protocol and prepared the figuresL.P.B - Senior author wrote the main manuscript text and tablesAll authors reviewed the manuscript References Rajendran K, Petersilka M, Henning A, Shanblatt ER, Schmidt B, Flohr TG et al (2022) First Clinical Photon-counting Detector CT System: Technical Evaluation. 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Cite Share Download PDF Status: Published Journal Publication published 05 Sep, 2025 Read the published version in Pediatric Radiology → Version 1 posted Editorial decision: Revision requested 22 Apr, 2025 Reviews received at journal 09 Apr, 2025 Reviews received at journal 08 Apr, 2025 Reviews received at journal 03 Apr, 2025 Reviewers agreed at journal 28 Mar, 2025 Reviewers agreed at journal 27 Mar, 2025 Reviewers agreed at journal 25 Mar, 2025 Reviewers agreed at journal 25 Mar, 2025 Reviewers invited by journal 25 Mar, 2025 Editor assigned by journal 23 Mar, 2025 Submission checks completed at journal 23 Mar, 2025 First submitted to journal 19 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6258330","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":438068948,"identity":"2d49b2bf-e845-4b36-9afc-dd8ab92b580e","order_by":0,"name":"Gladys M. Arguello Fletes","email":"data:image/png;base64,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","orcid":"","institution":"Children's Hospital Colorado","correspondingAuthor":true,"prefix":"","firstName":"Gladys","middleName":"M. Arguello","lastName":"Fletes","suffix":""},{"id":438068949,"identity":"65e28eb2-af73-4cd5-80c9-199059d6404c","order_by":1,"name":"Wei Zhou","email":"","orcid":"","institution":"University of Colorado Denver","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhou","suffix":""},{"id":438068950,"identity":"2010d28b-feb9-4b57-80a6-393066a68202","order_by":2,"name":"LaDonna J Malone","email":"","orcid":"","institution":"Children's Hospital Colorado","correspondingAuthor":false,"prefix":"","firstName":"LaDonna","middleName":"J","lastName":"Malone","suffix":""},{"id":438068952,"identity":"00f4075c-bf35-4c4b-b15e-fa07783bfd79","order_by":3,"name":"Andrea I Fuentealba Cargill","email":"","orcid":"","institution":"Children's Hospital Colorado","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"I Fuentealba","lastName":"Cargill","suffix":""},{"id":438068953,"identity":"5fe38602-74fc-46d3-9309-4537a7af27bd","order_by":4,"name":"Jason P Weinman","email":"","orcid":"","institution":"Children's Hospital Colorado","correspondingAuthor":false,"prefix":"","firstName":"Jason","middleName":"P","lastName":"Weinman","suffix":""},{"id":438068954,"identity":"d2bf16c9-58df-4544-872d-01a114e2ad4c","order_by":5,"name":"Lorna P Browne","email":"","orcid":"","institution":"Children's Hospital Colorado","correspondingAuthor":false,"prefix":"","firstName":"Lorna","middleName":"P","lastName":"Browne","suffix":""}],"badges":[],"createdAt":"2025-03-19 06:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6258330/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6258330/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00247-025-06336-w","type":"published","date":"2025-09-05T15:57:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80050671,"identity":"4678248d-cb29-43c1-acfe-52b026b50839","added_by":"auto","created_at":"2025-04-07 10:21:45","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78344,"visible":true,"origin":"","legend":"\u003cp\u003ea. Representative axial images showing the symmetric 20 mm^2 size ROI to calculate contrast to noise ratio. b. Representative axial image showing the symmetric 12 mm size ROI to calculate signal to noise ratio.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/29cd639b3dfbaef6024e8462.jpg"},{"id":80050670,"identity":"861da6e2-ff74-4563-abc1-fd13f8940ad9","added_by":"auto","created_at":"2025-04-07 10:21:45","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36373,"visible":true,"origin":"","legend":"\u003cp\u003eBox and whisker plots show quantitative assessment of the radiation dose values of PCDCT versus EIDCT measured in CT dose index (CTDI) and dose-length product (DLP) demonstrating overall higher doses with PCDCT. The middle bars in the boxes indicate the median; the whiskers are the lower and upper quartiles.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/48548e77c1fd48031f03e553.jpg"},{"id":80051732,"identity":"9e9c7e85-46e1-4986-bcf3-9f8f59c4ddfe","added_by":"auto","created_at":"2025-04-07 10:29:45","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":67649,"visible":true,"origin":"","legend":"\u003cp\u003eBox and whisker plots show quantitative assessment of signal-to-noise ratio (SNR) values of PCDCT versus EIDCT. The middle bars in the boxes indicate the median; the whiskers are the lower and upper quartiles.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/0209fa1814b720d145cbefd4.jpg"},{"id":80051733,"identity":"8c6630b0-88e5-4ec0-a839-78e3cc9c2093","added_by":"auto","created_at":"2025-04-07 10:29:45","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":42512,"visible":true,"origin":"","legend":"\u003cp\u003eBox and whisker plots show quantitative assessment of contrast-to-noise-ratio (CNR) values of PCDCT versus EIDCT. The middle bars in the boxes indicate the median; the whiskers are the lower and upper quartiles.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/63153b085d8650aa1d05f2ca.jpg"},{"id":80050677,"identity":"388ba4dc-ee16-4220-905f-9f21f43e1ec3","added_by":"auto","created_at":"2025-04-07 10:21:45","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":64730,"visible":true,"origin":"","legend":"\u003cp\u003ea.3-month-old male with history of truncus arteriosus type 2 status post repair. Example of PCDCT with excellent clarity of both internal mammary arteries (median Likert score of 5 (arrowheads), thoracic aorta (arrow) and pulmonary arteries (double arrow). b. 9-month-old female with heterotaxy, pulmonary atresia and supracardiac total anomalous venous return. Example of PCDCT scan and intermediate clarity of the thoracic aorta (Likert score of 3) (arrow), pulmonary arteries (double arrow), and left internal mammary artery (arrowhead). c. 6-month-old male with patent ductus arteriosus. Example of EIDCT scan with excellent clarity (Likert scores of 5) of the internal mammary arteries (arrow\u003cdel\u003e \u003c/del\u003eheads), thoracic aorta (arrow) and pulmonary arteries (double arrow)\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/3308589540b6cf1d6f701b72.jpg"},{"id":80050689,"identity":"2b137272-097e-4dee-90b8-59c579213d3c","added_by":"auto","created_at":"2025-04-07 10:21:45","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":61969,"visible":true,"origin":"","legend":"\u003cp\u003ea.11-year-old male with history of heterotaxy syndrome and double outlet right ventricle with D-malposed great arteries. Example of PCDCT showing excellent clarity (Likert score of 5\u003cu\u003e)\u003c/u\u003e in the thoracic aorta (arrow), pulmonary arteries (double arrow) and right internal mammary (arrowhead). The left internal mammary artery has been previously embolized. b. 9-year-old female with history of double inlet left ventricle and scimitar syndrome. Example of EIDCT showing good clarity (Likert score of 4) of the thoracic aorta (arrow) and pulmonary arteries (double arrow). Internal mammary arteries with embolization coils\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/39b8fa12f7ac95ecc59c7bc2.jpg"},{"id":90827996,"identity":"be0c4a10-eb17-4a5c-8746-afd4ef08c236","added_by":"auto","created_at":"2025-09-08 16:04:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1048900,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6258330/v1/e5f241ea-8863-437f-bc03-c1c32ad52f5f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Increased image noise and radiation dose in pediatric high pitch cardiac CTA using photon counting detector CT compared to energy integrating detector CT. ","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePhoton counting detector CT (PCDCT) has demonstrated clinical benefits compared to energy-integrating detector CT (EIDCT) in adult patients and more recently in pediatric patients [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePCDCT directly converts x-rays into electrical signal, enabling smaller detector elements and reducing electronic noise. This results in higher spatial resolution, better signal-to-noise ratio, and the ability to sort photons by energy level. Furthermore, the ability to measure the energy of incident photons provides additional post-acquisition reconstruction options including virtual mono-energetic reconstructions, virtual non-contrast images, and iodine maps among others. The spectral capabilities of the clinically available PCDCT system offer two different types of image acquisition, each with different technical requirements and reconstruction options [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePCDCT uses a relatively higher tube potential to obtain the full spectrum of photon energies for multienergy applications. This mode is described by vendor as \u0026ldquo;QuantumPlus\u0026rdquo; with the full array of spectral CT capabilities including virtual monoenergetic reconstruction at energies as low as 40 keV or as high as 190 keV; virtual non-contrast images (VNC) and iodine maps. However, currently these capabilities are restricted to acquisitions acquired at 120 or 140 kV. Quantum plus imaging has been standard in PCDCT in cardiac imaging in adults (1). Exams performed at 70 or 90 kV utilize another mode referred to by the vendor as \u0026ldquo;Quantum\u0026rdquo;; in this mode spectral capability is limited to only virtual monoenergetic reconstructions at energies less than the acquired energy, thus, there is no ability to reconstruct virtual non contrast images or an iodine map. Radiation dose modulation on PCDCT is achieved by automatic tube current modulation, automatic tube potential selection, and additionally the automatic selection of an energy level (kiloelectron volt) (CARE keV; Siemens Healthineers). At time of this study, this novel measure of energy level selection, was promoted as way of decreasing the radiation dose, that one would normally expect when selecting a higher kV.\u003c/p\u003e \u003cp\u003eA recent prior study evaluating PCDCT in a pediatric congenital heart disease population, concluded that with a similar radiation dose, PCDCT has a higher SNR and CNR when compared to EIDCT, however their study only evaluated PCDCT scans performed at 70 and 90kV [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and therefore did not evaluate scans performed with the full spectral \u0026ldquo;QuantumPlus\u0026rdquo; technique.\u003c/p\u003e \u003cp\u003eAt the time of acquisition of these studies, there was no available data regarding pediatric cardiac studies acquired utilizing the full spectral ability of PCDCT. Thus, in this study, we aimed to compare image quality metrics and radiation dose in a large population of pediatric patients who underwent high pitch cardiac CT on a PCDCT system with advanced spectral imaging (\u0026ldquo;QuantumPlus\u0026rdquo;) to avail of the full array of PCDCT capabilities, compared with those who underwent high pitch cardiac CT on a EIDCT system.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eIn October 2022, our existing EIDCT scanner was replaced with a state of art PCDCT scanner, one of the first PCDCTs installed in a standalone pediatric center at the time. In order to compare the performance of PCDCT to EIDCT, and following institutional review board (IRB) approval, a retrospective imaging and chart review of pediatric congenital heart disease patients who underwent a high pitch single beat cardiac CT between January 2021 and October 2023 was performed. Inclusion criteria were as follows: Patients aged\u0026thinsp;\u0026lt;\u0026thinsp;18 years, who underwent a high pitch cardiac CT on either an EIDCT or using the QuantumPlus technique on a PCDCT. Patients who required repeat studies due to inadequate contrast quality or excessive motion, or patients who had a lower kV (Quantum) technique performed on PCDCT, were excluded.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCardiac CT Techniques\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003ePCDCT\u003c/h2\u003e \u003cp\u003eHigh pitch cardiac CT images were acquired at 120 kV, for the purpose of utilizing \u0026ldquo;QuantumPlus\u0026rdquo; reconstruction, to allow for generation of iodine maps and virtual non contrast images. Images were acquired on a dual-source PCDCT system (NAEOTOM Alpha, Siemens Healthineers. Erlangen, Germany). Collimation was 144 x 0.40 mm, Z axis coverage was from C4 to just below the costophrenic angles in all patients, Care KeV IQ level\u0026thinsp;=\u0026thinsp;25, Virtual monoenergetic images were generated at 1 mm thickness with a medium kernel for vascular images (Bv48), parameters summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For this study, the 55 KeV datasets were chosen for comparison with EIDCT, as after an initial evaluation period of multiple KeVs, our consensus opinion was that this was KeV that provided most clinical value. Clinical indications where \u0026ldquo;quantum plus\u0026rdquo; was utilized included patients with metal artifacts, concern for thrombus and concern for abnormal differential of branch pulmonary artery blood flow.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eEIDCT\u003c/h3\u003e\n\u003cp\u003eHigh pitch cardiac CT images were acquired on a dual-source EIDCT system (Somatom definition Flash, Siemens Healthineers. Erlangen, Germany). The tube voltage was selected using a weight-based algorithm (70 kV for 0-10kg, 80 kV 10\u0026ndash;30, 100 kV for 30\u0026ndash;50 kg and 120 for \u0026gt;\u0026thinsp;50kg. Caredose 4D was used for tube current modulation with a quality reference mAS of 150, and the weight-based kV was chosen as the reference kV. Collimation was 128 x 0.6 mm, scan direction was foot to head, Z axis coverage was from C4 to just below the costophrenic angles. Image reconstructions at 1 mm using a standard soft tissue window reconstructions were performed (I30/Bv36), parameters shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCT Technique and reconstruction parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCDCT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEIDCT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTube voltage (kV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (n\u0026thinsp;=\u0026thinsp;93); 80 (n\u0026thinsp;=\u0026thinsp;5); 100 (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollimation (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 x 0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128 x 0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRotation time (sec)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePitch factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReconstruction\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlice thickness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKernel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBv48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI30/Br36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIterative reconstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQIR (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSAFIRE (3) /ADMIRE (3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWindow (HU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCenter 200; window 600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCenter 200; window 600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe iodinated contrast injection protocol was the same on both scanners, utilizing Iopamidol (Isovue-300) at 2ml/kg (max of 100ml) with an automated injection at 1.2ml/sec or greater through right upper or lower extremity peripheral IV. Regions of interest (ROI) were placed in either the left or right ventricle depending upon anatomy of primary interest for timing the scan.\u003c/p\u003e\n\u003ch3\u003eImage quality analysis\u003c/h3\u003e\n\u003cp\u003eQuantitative and qualitative metrics of image quality were assessed.\u003c/p\u003e \u003cp\u003eQuantitative analysis of image quality (signal to noise and contrast to noise ratios) was performed on the clinical PACS viewing workstations (Synapse 5 Radiology PACS, Fujifilm Healthcare Americas Corporation), by a pediatric radiologist, using a previously validated technique [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Four regions of interest (ROIs) of at least a 20 mm^2 area was placed on bilateral teres minor and paraspinal muscles to calculate signal to noise ratio (SNR). SNR should remain consistent across all structures. We selected these muscles, rather than cardiovascular structures, because they should demonstrate minimal variation across studies, regardless of age or congenital anomaly. Image SNR was calculated as the mean Hounsfield units (HU) in the ROI divided by the standard deviations (SDs) of all ROIs positioned.\u003c/p\u003e \u003cp\u003eImage contrast to noise ratio (CNR) was calculated using the following equation CNR\u0026thinsp;=\u0026thinsp;Mean aorta HU\u0026ndash; mean pulmonary artery HU/mean SD aorta HU [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Examples of CNR and SNR are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eQualitative analysis of the imaging quality of the thoracic vessels was independently performed by two cardiac imagers (18 years and 18 months of cardiac CT experience respectively). Qualitative imaging evaluation was performed using deidentified 1 mm thick axial reconstructions presented in a randomized order with the readers blinded to the type of scanner used. Visualization of selected thoracic vessels was scored using a 5-point Likert scale according to vessel clarity (1\u0026thinsp;=\u0026thinsp;non-distinguishable \u0026ndash; 5\u0026thinsp;=\u0026thinsp;excellent clarity). The vessels evaluated were thoracic aorta, first and second order pulmonary artery branches, proximal internal mammary arteries, SVC or IVC, and pulmonary veins.\u003c/p\u003e \u003cp\u003eCTDI and DLP of each exam was obtained from vendor generated dose report in PACS. Effective dose in millisieverts (mSv) was calculated based on DLP and age-related conversion factor [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eBased on an uneven patient age distribution favoring infants and babies, two age-based subgroups were created for analysis. The first group was 12 months of age and younger and the second group older than 12 months. For each age group, patients\u0026rsquo; ages at time of PCDCT and EIDCT scan were compared using unpaired t-test. A Shapiro-Wilk test was performed to verify the normality for radiation dose and quantitative measurements (SNR and CNR).\u003c/p\u003e \u003cp\u003eA Mann-Whitney test was used to compare differences of non-normally distributed datasets, including subjective image quality scores, between the 2 patient groups. Interrater agreement between the two readers for qualitative image quality measures were calculated using kappa coefficients and classified (less than 0.20 poor, 0.21\u0026ndash;0.40 fair, 0.41\u0026ndash;0.60 moderate, 0.61\u0026ndash;0.80 good and 0.81-1.00 very good [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Kappa coefficient analyses were performed in an open-source Online Kappa Calculator (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://justusrandolph.net/kappa/\u003c/span\u003e\u003cspan address=\"http://justusrandolph.net/kappa/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e tusrandolph.net).\u003c/p\u003e \u003cp\u003eThe rest of statistical analyses were performed in on open-source package (R Project, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTwo hundred patients met the inclusion criteria and were included in the analysis. Detailed patient demographics are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In summary, 100 patients (50%, n\u0026thinsp;=\u0026thinsp;100/200,) underwent a high pitch cardiac CT scan with advanced spectral processing (QuantumPlus) on PCDCT. These patients had a median age of 4.4 months. (range: day of life 1 to 17.5 years), with slight female preponderance (f\u0026thinsp;=\u0026thinsp;53%). Similarly, 100 patients (n\u0026thinsp;=\u0026thinsp;100/200 or 50%) underwent a high pitch cardiac CT on EIDCT with a median age of 3.9 months (range: day of life 1 to 17.5 years) with a male preponderance (m\u0026thinsp;=\u0026thinsp;65%).\u003c/p\u003e \u003cp\u003eOf the 200 patients that underwent cardiac CT in the study period, the predominant age group encountered in both cohorts were infants and neonates aged 12 months and below, comprising 68% of PCDCT patients (n\u0026thinsp;=\u0026thinsp;68/100) and 80% of EIDCT patients: n\u0026thinsp;=\u0026thinsp;80/100.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePCDCT (N\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEIDCT (N\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge Range\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.28\u0026thinsp;\u0026plusmn;\u0026thinsp;5.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.35\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSD\u0026thinsp;=\u0026thinsp;standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eRadiation Dose\u003c/h3\u003e\n\u003cp\u003eRadiation doses are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The radiation dose was significantly higher (p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for patients in both groups scanned with the full spectral capability on PCDCT when compared to age matched patients on the EIDCT scanner. The patients of 12 months and younger scanned in PCDCT group demonstrated considerably higher radiation dose with a median CTDI of 0.23 mGy (0.21\u0026ndash;0.27 mGy) in comparison to 0.10 (0.10\u0026ndash;0.12) mGy in the EIDCT group; and a median DLP of 4.00 mGycm (3.26\u0026ndash;5.17 mGycm) compared to 1.80 mGycm (1.5\u0026ndash;2.2 mGycm ) in the EIDCT group.\u003c/p\u003e \u003cp\u003eThe patients aged greater than 12 months scanned in PCDCT had a median CTDI of 0.80 mGy (0.50\u0026ndash;2.01 mGy) in comparison to 0.16 mGy (0.14\u0026ndash;0.50 mGy) in the EIDCT group; and a median DLP of 23.2 mGycm (10.23\u0026ndash;50.87 mGycm) compared to 4.2 mGycm (2.8\u0026ndash;11.2 mGycm) in the EIDCT group. Figure\u0026nbsp;2 and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTable 3 Radiation doses are presented with median and the range between 1st and 3rd quartile\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCDCT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEIDCT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;12 months\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTDIvol (mGy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23 (0.21\u0026ndash;0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10 (0.10\u0026ndash;0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDLP (mGycm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.00 (3.26\u0026ndash;5.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8 (1.5\u0026ndash;2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026gt;\u0026thinsp;12 months\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTDIvol (mGy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80 (0.50\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16 (0.14\u0026ndash;0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDLP (mGycm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.2 (10.23\u0026ndash;50.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 (2.8\u0026ndash;11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eImage Quality Analysis\u003c/h3\u003e\n\u003cp\u003eSNR and CNR quantitative results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e with summaries below.\u003c/p\u003e \u003cp\u003eNotably, in patients aged 12 months and younger, there was significantly decreased SNR decreased in teres muscle (p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on the PCDCT compared to EIDCT. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. However, in patients older than 12 months, there was no significant difference in SNR on PCDCT compared to EIDCT.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegardless of patient age, there was no significant difference in CNR between EIDCT and PCDCT. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of image quality of PCDCT versus EIDCT. Quantitative image metrics are presented with median and the range between 1st and 3rd quartile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion of Interest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMetric\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 months and younger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOlder than 12 months\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSignal to Noise Ratio\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRight teres minor muscle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePCDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003cp\u003e(1.43\u0026ndash;2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003cp\u003e(1.48\u0026ndash;2.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEIDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003cp\u003e(1.70\u0026ndash;2.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003cp\u003e(1.61\u0026ndash;2.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLeft teres minor muscle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePCDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003cp\u003e(1.46\u0026ndash;2.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003cp\u003e(1.44\u0026ndash;2.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEIDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003cp\u003e(1.69\u0026ndash;2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003cp\u003e(1.31\u0026ndash;2.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRight paraspinal muscle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePCDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003cp\u003e(1.43\u0026ndash;2.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003cp\u003e(1.34\u0026ndash;3.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEIDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003cp\u003e(1.52\u0026ndash;2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003cp\u003e(1.10\u0026ndash;2.64)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLeft paraspinal muscle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePCDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003cp\u003e(1.41\u0026ndash;2.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003cp\u003e(1.32\u0026ndash;2.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEIDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003cp\u003e(1.44\u0026ndash;2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003cp\u003e(1.63\u0026ndash;2.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eContrast to Noise Ratio\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAscending aorta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePCDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.61\u003c/p\u003e \u003cp\u003e(23.48\u0026ndash;39.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003cp\u003e(24.58\u0026ndash;39.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEIDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.14\u003c/p\u003e \u003cp\u003e(22.08\u0026ndash;52.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.27\u003c/p\u003e \u003cp\u003e(14.92\u0026ndash;40.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePulmonary artery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePCDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.02\u003c/p\u003e \u003cp\u003e(21.54\u0026ndash;38.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.29\u003c/p\u003e \u003cp\u003e(20.27\u0026ndash;35.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEIDCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.58\u003c/p\u003e \u003cp\u003e(21.08\u0026ndash;48.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.54\u003c/p\u003e \u003cp\u003e(17.81\u0026ndash;45.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eP-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn terms of subjective image quality (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e), both PCDCT and EIDCT demonstrated excellent clarity of the thoracic aorta, pulmonary veins, and pulmonary arteries in patients greater than 12 months (median Likert scores: 5). Both PDCT and EIDCT demonstrated good clarity of the SVC/IVC (median Likert scores: 4). The internal mammary arteries were clearer on the EIDCT compared to PCDCT, median score of 4 (good clarity) on PCDCT and median score of 5 (excellent clarity) on EIDCT and the pulmonary arteries in patients less than 12 months of age and younger were clearer on the PCDCT (a median Likert score:5) compared to EIDCT (median Likert score:4.5).\u003c/p\u003e \u003cp\u003eOverall percent agreement for the thoracic aorta clarity Likert score was 65% for with moderate interrater agreement (95% CI [0.48,0.65]). Overall percent agreement for pulmonary artery branches was 48.5% with fair interrater agreement (95% CI k\u0026thinsp;=\u0026thinsp;0.27, 0.44). Overall percent agreement for internal mammary arteries was 36.5% for with poor interrater agreement (95% CI k\u0026thinsp;=\u0026thinsp;0.12, 0.29). Overall percent agreement for pulmonary veins was 45.5% with fair interrater agreement (95% CI k\u0026thinsp;=\u0026thinsp;0.23, 0.41). Overall percent agreement for IVC/SVC was 29% with poor interrater agreement (94% CI k\u0026thinsp;=\u0026thinsp;0.03,0.19). Examples of both groups are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe purpose of this study was to compare image quality and radiation dose of the full spectral capability of PCDCT with EIDCT for cardiac CT in a pediatric population. In patients 12 months of age and younger, PCDCT using the full spectral \u0026ldquo;Quantum Plus\u0026rdquo; technique showed significantly higher radiation doses with significantly lower SNR compared to EIDCT.\u003c/p\u003e \u003cp\u003ePrior work using phantom abdominal CT models showed that universal use of a 120 kV dual source high pitch protocol on the PCDCT system [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] had a lower radiation dose than similar phantom scans on the EIDCT, however our methodology differed by using actual cardiac CT patients rather than the phantom acquistion.\u003c/p\u003e \u003cp\u003eOther recent work on this topic includes studies by St\u0026aring;lhammar et al [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and Dirrichs et al [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Our findings and approach differ from these prior studies as follows.\u003c/p\u003e \u003cp\u003eThe study by Dirrichs et al [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], compared their preliminary experience of using PCDCT in 30 pediatric congenital heart disease patients aged up to 3 years compared to 84 patients who underwent an EIDCT scan. In their limited patient cohort, CNR and SNR were higher in PCDCT with lower radiation dose. However, they employed a 70kV based PCDCT technique \u0026ldquo;Quantum\u0026rdquo; with the resultant limited spectral capability; therefore, they did not evaluate the full spectral PCDCT technique \u0026ldquo;Quantum Plus\u0026rdquo; used in our study.\u003c/p\u003e \u003cp\u003eAnother recently published study by St\u0026aring;lhammar et al [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] concluded that pediatric cardiovascular PCDCT images for congenital heart defects had high diagnostic quality with low radiation dose. In this study PCDCT scans were performed at 70kV (n\u0026thinsp;=\u0026thinsp;35; age 2 days\u0026ndash;16 years) and 90 kV (n\u0026thinsp;=\u0026thinsp;35; age 2 days\u0026ndash;17 years); also, not utilizing the full spectral capability as in our study. Additionally, scans performed at 70kV were compared to those scanned at 90 kV and there was no control group and image analyses were based on subjective rather than quantitative analyses.\u003c/p\u003e \u003cp\u003eThe QuantumPlus technique allows generation of iodine maps and virtual non contrast images. In our experience, there may be some advantages for using a QuantumPlus technique in select pediatric cardiac patients. Iodine maps can help evaluate intrastent or baffle hypodensity and occlusion as well as decrease streak artifact within vascular stents. It also offers potential in assessing relative lung perfusion qualitatively and hopefully in the future quantitatively. Additionally, virtual non-contrast reconstructions can assist in evaluating contrast-related artifacts and differentiating calcifications from contrast enhancement.\u003c/p\u003e \u003cp\u003eWhile there are potential benefits from using advanced spectral capability, in our study, this was at the expense of higher radiation dose and a lower SNR in young infants. Thus, an indication-based approach to using QuantumPlus is suggested to optimize the use of these capabilities to those specific patients who would most likely benefit from them.\u003c/p\u003e \u003cp\u003eWe acknowledge that our study has several limitations. First, we are comparing CNR and SNR from very different scanning and technology parameters which introduces several significant confounders. Reconstruction kernels were different between PCDCT and EIDCT. We utilized monoenergetic 55keV reconstructions for both our qualitative and quantitative analysis on the scans performed on PCDCT. While we expect SNR to be improved by measurements using a higher keV and CNR by a lower keV reconstruction closer to the k-edge of iodine, this was not tested in this study as the images are not clinically as helpful. The difference in kernel utilizing Bv48 on PCDCT versus I30/Bv36 on EIDCT may confound evaluation of signal to noise ratio. We acknowledge that pediatric PCDCT is a novel technology, and the optimal technical parameters have not yet been established, and we suggest that more evaluation of the potential effects of the various PCDCT kernels and differing monoenergetic reconstructions on signal to noise and radiation dose be performed.\u003c/p\u003e \u003cp\u003eIt is important to mention that our EIDCT radiation doses were comparatively low with a median CTDI of 0.10mGy in the 12 months old and younger group and 0.16mGy in the older than 12 months old age group, compared to other published studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These protocols have been optimized over several years continuing to evaluate adequate image quality and dose reduction. A study by Li et al had a median CTDI of 1.2 in patients less than 4 years of age using high-pitch dual-source cardiac CT [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Another study by Shirota et al utilizing a 320 row CT scanner, had a median CTDI of 0.45 in newborns, 0.52 in infants less than 1 year old and 0.78 in patients less than 5 years old [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe existing literature, while limited, would suggest that radiation dose and image quality may be reduced if using a Quantum rather than a QuantumPlus approach, particularly in the smallest patients. Thus, future studies comparing image quality and radiation dose in PCDCT for pediatric cardiac CT at 120kV versus 90kV and 70kV is suggested. Additionally, studies are needed to evaluate the potential clinical benefits that spectral reconstructions such as optimum virtual monoenergetic reconstruction as well as iodine maps, could add to diagnostic value of pediatric cardiac CT.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, high pitch cardiac CT on PCDCT using the advanced spectral processing mode, resulted in a higher radiation dose compared to EIDCT and in infants was associated with decreased SNR. Further work is needed to establish optimal pediatric PCDCT cardiac CT scanning parameters, but considering these findings, it is suggested that advanced spectral processing mode is best reserved for select patients who may benefit from additional reconstructions such as virtual non contrast and iodine maps.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eG.M.AF -wrote the main manuscript textZ.W - was responsible for statistics and statistics figures L.J.M Prepared with the technique and protocolA.I.FC Responsible for including and excluding the casesJ.P.W Wrote the new protocol and prepared the figuresL.P.B - Senior author wrote the main manuscript text and tablesAll authors reviewed the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRajendran K, Petersilka M, Henning A, Shanblatt ER, Schmidt B, Flohr TG et al (2022) First Clinical Photon-counting Detector CT System: Technical Evaluation. Radiology 303(1):130\u0026ndash;138 Epub 20211214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1148/radiol.212579\u003c/span\u003e\u003cspan address=\"10.1148/radiol.212579\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMilos RI, R\u0026ouml;hrich S, Prayer F, Strassl A, Beer L, Heidinger BH et al (2023) Ultrahigh-Resolution Photon-Counting Detector CT of the Lungs: Association of Reconstruction Kernel and Slice Thickness with Image Quality. 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Radiology 307(5):e223088 Epub 20230523. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1148/radiol.223088\u003c/span\u003e\u003cspan address=\"10.1148/radiol.223088\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSt\u0026aring;lhammar F, Aurumskj\u0026ouml;ld ML, Meyer S, Wiklund M, Wingren P, Liuba P et al (2024) Photon-counting computed tomography for paediatric congenital heart defects yields images of high diagnostic quality with low radiation doses at both 70 kV and 90 kV. 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Pediatr Radiol 47(11):1463\u0026ndash;1470 Epub 20170630. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00247-017-3901-2\u003c/span\u003e\u003cspan address=\"10.1007/s00247-017-3901-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pediatric-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prad","sideBox":"Learn more about [Pediatric Radiology](http://link.springer.com/journal/247)","snPcode":"247","submissionUrl":"https://submission.nature.com/new-submission/247/3","title":"Pediatric Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6258330/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6258330/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePrevious studies have shown improved image quality in pediatric cardiac imaging using photon-counting detector CT (PCDCT). However, these studies did not evaluate image quality and radiation dose when utilizing the full spectral capabilities of PCDCT scanners.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo compare image quality and radiation dose between high pitch cardiac CT using full spectral PCDCT and dual source energy-integrating detector CT (EIDCT).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective, IRB-approved study analyzed high pitch cardiac CTs from January 2021 to October 2023 in pediatric patients (\u0026lt;\u0026thinsp;18 years). Patients were scanned using either PCDCT with full spectral technique (\u0026ldquo;QuantumPlus\u0026rdquo;) or EIDCT. Radiation doses were measured by CT dose index (CTDI) and dose-length product (DLP). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were also calculated, and image quality was assessed using a 5-point Likert scale. Statistical analysis included unpaired T-test, Shapiro-Wilk test, Mann-Whitney test, and kappa coefficients for interrater agreement.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e200 patients were evaluated, with 100 scanned on PCDCT and 100 on EIDCT. Most patients (148/200) were \u0026le;\u0026thinsp;12 months of age. CNR was similar between groups for both age groups. In patients\u0026thinsp;\u0026le;\u0026thinsp;12 months, SNR was only significantly higher at the teres muscles for EIDCT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Radiation doses were significantly higher for PCDCT across both age groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHigh pitch cardiac CT with PCDCT using spectral processing resulted in higher radiation doses and lower SNR in infants compared to EIDCT.\u003c/p\u003e","manuscriptTitle":"Increased image noise and radiation dose in pediatric high pitch cardiac CTA using photon counting detector CT compared to energy integrating detector CT. 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