Photon-Counting CT Angiography vs. Energy-Integrating CT Angiography for Intracranial Vascular Implant Imaging

Photon-Counting CT Angiography vs. Energy-Integrating CT Angiography for Intracranial Vascular Implant Imaging | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Photon-Counting CT Angiography vs. Energy-Integrating CT Angiography for Intracranial Vascular Implant Imaging Daniel Rosok, Sebastian Zensen, Marcel Opitz, Denise Bos, Maximilian Schüssler, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7695127/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Photon-counting detector (PCD) CT angiography (CTA) is an emerging technology that improves spatial resolution and reduces artifacts, potentially enhancing imaging of intracranial implants. No in vivo intra-individual comparisons with energy-integrating detector (EID) CTA in patients with intracranial vascular implants have been reported. The purpose was to fill that gap by directly comparing PCD-CTA and EID-CTA. Methods In this retrospective single-center observational study, all patients with intracranial vascular implants scanned with PCD-CT from April 2023 to March 2024 were included after ethics approval. Intra-individual comparisons were performed using dual-source EID-CT from the same manufacturer. Image quality was evaluated subjectively with a 5-point Likert scale (1 = lowest, 5 = highest) and objectively via signal-to-noise ratios (SNR). Wilcoxon signed-rank tests were used for statistical analysis. Results Among 693 PCD-CT scans, 52 patients (7.5%) had intracranial vascular implants; 10 underwent both PCD-CTA and EID-CTA (median age 56.5 years, IQR 53.8–61; 90% female). PCD-CTA with iterative metal artifact reduction (MAR) demonstrated fewer artifacts and higher diagnostic value than EID-CTA (median Likert scores 4.5 and 5 vs. 3 and 3; p = 0.004). Objective image quality was superior with PCD-CTA compared to EID-CTA with MAR (SNR 34.4 vs. 17.1; p = 0.005) but not significantly different without MAR (27.8 vs. 9.9; p = 0.203). Conclusions PCD-CTA with MAR offers superior image quality and artifact reduction in patients with intracranial vascular implants, highlighting its potential as a non-invasive alternative for follow-up imaging. Larger studies are warranted to validate these findings. Energy-integrating CT angiography Intracranial vascular implants Neurovascular imaging Photon-counting CT angiography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Photon-counting detector (PCD) CT represents a paradigm shift in medical imaging by enabling high-resolution imaging through the counting of individual X-ray photons and measurement of photon energy [ 1 – 3 ]. Compared to energy-integrating detectors (EID) used in conventional CT scanners, PCD-CT directly converts photons into electronic signals within a semiconductor substrate, eliminating the intermediate step of converting photons into visible light with a scintillator, as required by EID-CT. This technology can offer superior image quality by the lowering of electronic noise and beam-hardening artifacts [ 1 , 4 – 6 ], particularly useful in the imaging of intracranial arteries and metal implants. Intracranial neurovascular implants—such as clips, coils, and intrasaccular devices—are used for aneurysm therapy and other cerebrovascular conditions. Following neuroradiological and neurosurgical interventions, imaging is essential to assess treatment efficacy and detect potential complications. Digital subtraction angiography (DSA) remains the gold standard for imaging intracranial vessels due to its high diagnostic accuracy and its insusceptibility to metal artifacts [ 7 , 8 ]. However, as an invasive procedure, it carries a small risk of periprocedural complications [ 9 ]. Non-invasive alternatives such as EID CT angiography (CTA) and MR angiography (MRA) are widely used, but both have limitations—CTA is affected by beam hardening artifacts, while MRA offers lower spatial resolution [ 10 – 12 ]. The integration of the new PCD-CTA might offer the potential to improve image quality and diagnostic accuracy in patients with intracranial vascular implants. PCD-CTA for imaging intracranial vascular implants has been previously explored in vitro and compared to flat panel CTA in a phantom-study [ 13 ] and to digital subtraction angiography in vivo [ 14 – 16 ]. To the best of our knowledge, no systematic evaluation has yet compared PCD-CTA with conventional CTA for intracranial vascular devices intra-individual in vivo. The objective of this study was to analyze the image quality, diagnostic value and radiation dose of PCD-CTA in patients with intracranial implants compared to EID-CTA. Material and Methods Composition of the study cohort This retrospective, single-center, observational cohort study was approved by the local ethics committee of our institution and adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational studies [17, 18]. The initial study sample included all patients who underwent cranial CT imaging using the PCD-CT system “NAEOTOM Alpha” (Siemens Healthineers, Erlangen, Germany) between April 2023 and March 2024. Patients were recruited consecutively. From this cohort, only patients with intracranial vascular implants who had undergone both dual-source PCD-CTA and dual-source EID-CTA on comparable state-of-the-art systems were included to enable intra-individual comparison under similar conditions. The comparator EID-CT system was the dual-source 256-slice (2 x 128) “SOMATOM Definition Flash” (Siemens Healthineers, Erlangen, Germany). These patients underwent follow-up examinations after endovascular or neurosurgical treatment at our university hospital. The primary outcome of the study was image quality, assessed both subjectively via a 5-point Likert scale for artifacts and diagnostic value, and objectively via signal-to-noise ratios (SNR). Image acquisition parameters Standardized protocols were applied for both PCD-CTA and EID-CTA examinations. The cerebral vasculature was scanned from the skull base to the vertex without gantry tilt. CTA was performed after intravenous injection of 70 ml iodinated contrast medium (Ultravist-300, iopromide; Bayer Healthcare, Berlin, Germany) at 4 ml/s. Contrast enhancement of the common carotid artery was monitored, and scanning commenced five seconds after reaching the predefined attenuation threshold. Key acquisition and reconstruction parameters are summarized in table 1. Table 1 Image acquisition and reconstruction parameters Parameter Photon-counting CT angiography Energy-integrating CT angiography Acquisition parameters Tube voltage (kVp) 140 80 (A-tube)/ Sn140 (B-tube) Tube current (image quality level/ reference mAs) With modulation and vendor-specific image quality level of 145 With modulation and 222 mAs as reference for tube A and 111 mAs for tube B Rotation time (s/ rotation) 0.25 0.33 Collimation (mm) 0.4 0.6 Pitch 0.8 0.5 Reconstruction parameters Reconstruction type iterative iterative Matrix size/ pixel no. 512 x 512 512 x 512 Kernel Q40f Bv40 Slice thickness 1mm 1mm Qualitative evaluation One board-certified neuroradiologist (CD, 13 years of experience) and one radiology resident (DR, 4 years of experience) independently evaluated the image quality of the CTA with iterative metal artifact reduction (MAR) using a Likert scale. First, the readers were blinded to image type and patient identity and reviewed all images independently in a random order. Secondly, the results were compared and, in the event of discrepant scores, a joint discussion of the findings was held, resulting in consensus. The areas directly adjacent to the intracranial vascular devices were rated regarding the quantity of artifacts and the diagnostic value of the examination (with options: 5 = very mild artifacts, excellent diagnostic value, 4 = mild artifacts, completely acceptable diagnostic value, 3 = moderate artifacts, mostly acceptable diagnostic value, 2 = strong artifacts, suboptimal diagnostic value, 1 = very strong artifacts, unacceptable diagnostic value). Quantitative evaluation SNR were used for quantitative analysis of CTA. SNR were defined as the mean attenuation values in Hounsfield units (HU) divided by their standard deviation (SD) from each region of interest (ROl). The ROIs were placed directly adjacent to the neurovascular implant in the artery of diagnostic interest. Average ROI sizes of approximately 10 mm² were selected based on the respective vessel dimensions and placed within the contrast-enhanced arterial lumen. The same representative vessel areas with identical ROI sizes were chosen for PCD-CTA and EID-CTA scans. Analyses were carried out separately on the original and the automatically post-processed images with MAR. Radiation dose analysis The radiation exposure parameters volume-weighted computed tomography dose index (CTDIvol) and dose-length product (DLP) were extracted from Digital Imaging and Communications in Medicine protocols. Statistical analysis Data analysis was conducted using SPSS Version 27.0 (IBM Corp, Armonk, NY, USA; RRID:SCR_016479). Normality of distributions was assessed using the Shapiro-Wilk test. As the variables were not normally distributed, non-parametric data are reported as medians with interquartile ranges (IQR), and categorical variables are presented as frequencies and percentages. Intra-individual comparisons of patients who underwent both PCD-CTA and EID-CTA were performed using the Wilcoxon signed-rank test to assess differences in Likert scores, SNR, and radiation dose parameters. A two-sided p < 0.05 was considered statistically significant. Figures were created using GraphPad Prism Version 5.0 (GraphPad Software, La Jolla, CA, USA; RRID:SCR_002798). Results Composition of the study cohort During the study period, 693 PCD-CT examinations of the head and intracranial vasculature were performed, identifying 52 patients (7.5 %, 52/693) with intracranial vascular implants (42 females, 80.8 %; median age 59.3 years, IQR 14.8, range 20.8–83.9). Multiple PCD-CTs were performed in 9 patients (17.3 %, 9/52). Intracranial aneurysms were the most common indication for implants, affecting mainly the middle cerebral artery (42.3 %, 22/52), anterior communicating artery (34.6 %, 18/52), internal carotid artery (17.3 %, 9/52), posterior inferior cerebellar artery (7.7 %, 4/52), and basilar artery tip (3.8 %, 2/52). Single cases involved the pericallosal and posterior communicating arteries (1.9 %, 1/52 each), with other indications including arteriovenous malformations (2 cases) and a dural arteriovenous fistula (1 case). Table 2 summarizes the distribution of intracranial vascular implant types among the 52 patients identified with neurovascular devices during the study period. Table 2 Distribution of intracranial vascular implant types Intracranial vascular implant Number of patients (% of 52 patients) Clip 26 (50.0 %) Coil 16 (30.8 %) Coil + clip 2 (3.8 %) Flow diverter 2 (3.8 %) Stent 1 (1.9 %) Web-device 1 (1.9 %) Coil + stent 1 (1.9 %) Flow diverter + coil 1 (1.9 %) Flow diverter + clip 1 (1.9 %) Coil + stent + clip 1 (1.9 %) For image quality comparison between PCD-CTA and EID-CTA, patients were excluded in sequential steps. Four patients with CTA but without a comparable EID-CT were excluded (7.7 %, 4/52). Non-contrast CTs (73.1 %, 38/52) were also excluded, as the study focused on CTA and images with and without MAR were not consistently available. Only patients with complete PCD-CTA and EID-CTA datasets, including images with and without MAR, were included, yielding a final cohort of 10 patients (19.2 %, 10/52). The final cohort comprised 90% females (9/10) and a median age of 56.5 years (IQR 7.2, range 38–72). In this subgroup, implants comprised clips (60%, 6/10), flow diverters with coils (20%, 2/10), a clip with coil (10%, 1/10), and a combination of coil, clip, and stent (10%, 1/10). Only CTA examinations were further analyzed. Figure 1 illustrates the case assignment algorithm and exclusion process. Three sequential exclusion steps were applied to derive the final study cohort. Qualitative evaluation All patients showed significantly fewer artifacts and higher diagnostic value for PCD-CTA compared to EID-CTA. For artifacts, PCD-CTA had a median Likert score of 4.5 (IQR 4–5) compared to 3 (IQR 2.8–3) for EID-CTA ( p < 0.004). For diagnostic value, PCD-CTA had a median Likert score of 5 (IQR 4–5) compared to 3 (IQR 3–3.75) for EID-CTA ( p < 0.004). Figure 2 illustrates the differences in image quality between PCD-CTA and EID-CTA with respect to artifact prevalence and overall diagnostic value. Quantitative evaluation For signal, PCD-CTA had a median HU of 385.5 (IQR 272.8–474.8) with MAR and 431 (IQR 321–500) without MAR, whereas EID-CTA had a median of 211.5 (IQR 170.5–301.5) with MAR and 146 (IQR 136.3–188.3) without MAR. Signal was significantly higher for PCD-CTA compared to EID-CTA ( p = 0.005 for both MAR and no MAR). For noise, PCD-CTA had a median SD of 10.5 (IQR 5.5–17.3) with MAR and 26 (IQR 18.8–53.8) without MAR, compared to 9 (IQR 6–24.3) with MAR and 14.5 (IQR 11.0–31.8) without MAR in EID-CTA. Noise was not significantly different with MAR ( p = 0.312) but was higher for PCD-CTA without MAR compared to EID-CTA ( p = 0.041). For SNR, PCD-CTA achieved a median of 34.4 (IQR 17.7–80.6) with MAR and 17.1 (IQR 7.2–25.5) without MAR, while EID-CTA showed a median of 27.8 (IQR 7.1–40.2) with MAR and 9.9 (IQR 5.0–16.1) without MAR. SNR was significantly higher for PCD-CTA compared to EID-CTA with MAR ( p = 0.005), but not significantly different without MAR ( p = 0.203). Figure 3 shows the image quality differences of PCD-CTA and EID-CTA assessed by signal, noise and SNR. Figures 4 and 5 illustrate the superior vessel delineation in PCD-CTA compared to EID-CTA and the valuable effect of MAR in PCD-CTA of neurovascular implants. Radiation dose analysis Radiation exposure was significantly lower with PCD-CTA compared to EID-CTA. Median CTDIvol was 6.1 mGy (IQR 6.1–6.2) versus 13.8 mGy (IQR 12.9–14.6) for EID-CTA, corresponding to a 55.8 % reduction ( p = 0.008). Median DLP was 109 mGy·cm (IQR, 106–117) versus 214 mGy·cm (IQR, 203–231), representing a 49.1 % reduction ( p = 0.011). Discussion This study demonstrates that PCD-CTA of intracranial implants provides superior qualitative and quantitative image quality compared to conventional EID-CTA. The higher diagnostic value of PCD-CTA was attributed to subjectively improved vascular contrast with sharper margins and objectively higher SNR with the application of MAR. This could clinically enhance visualization of vessels adjacent to the neurovascular implant (Figures 4 and 5), improve non-invasive assessment of vessel patency, and aid in the exclusion of aneurysmal remnants or reperfusion. Moreover, PCD-CTA was associated with significantly lower radiation exposure than EID-CTA, with a 56% reduction in median CTDIvol and a 49% reduction in median DLP. This reduction represents a major clinical advantage, particularly for patients requiring repeated follow-up imaging of intracranial implants, as it minimizes cumulative radiation exposure while maintaining superior image quality. To assess the effect of MAR on image quality, PCD-CTA and EID-CTA were analyzed with and without MAR. Improved image quality was observed for PCD-CTA only when MAR was applied, highlighting the critical role of artifact reduction [19]. Sharper vessel delineation in PCD-CTA likely reflects the superior spatial resolution of photon-counting detectors [1]. Signal measured in vessels adjacent to intracranial implants was significantly higher in PCD-CTA than in EID-CTA, both with and without MAR, likely due to PCDs’ ability to capture more photons and suppress electronic noise [1]. PCD-CTA without MAR exhibited higher noise levels than EID-CTA, possibly because inclusion of low-energy photons increases beam-hardening artifacts [1, 20], which are pronounced around intracranial implants. Thus, MAR in PCD-CTA is particularly important for denoising and correcting beam-hardening artifacts. Intracranial aneurysms were the most common indication for intracranial devices in our cohort, with clips being the most frequent implant type. The cohort showed a female predominance, which may reflect the higher prevalence of intracranial aneurysms in women [21]. The median age was 56 years, consistent with the typical peak age for aneurysm presentation [21]. Symons et al. were among the first to highlight the potential of PCD-CTA for intracranial imaging [22]. Using a prototype PCD-CT—where one EID subsystem of a dual-source CT was replaced by a PCD—they demonstrated benefits in artifact reduction, with both PCD-CT and EID-CT acquisitions performed sequentially after a single iodine contrast injection [22]. Our in vivo findings align with Schmitt et al., who showed in an experimental PCD-CT model that applying MAR enhances visualization of neurovascular coils by reducing beam-hardening artifacts [23]. We could confirm that PCD-CTA produces higher noise than EID-CTA without MAR, and in the absence of MAR, both modalities yielded relatively high noise levels, affecting SNR. Similar improvements in small-vessel imaging were reported by Si-Mohamed et al. in coronary stents, with PCD-CTA showing superior image quality and higher intraluminal HU signal than EID-CTA, without significantly different noise [24]. De Beukelaer et al., in comparison with DSA, demonstrated that ultra-high-resolution PCD-CTA effectively assesses in-stent stenosis and aneurysm remnants in intracranial implants [15, 16], supporting its potential as a non-invasive alternative for postinterventional follow-up. Their reported DLP values were consistent with our dose measurements [16]. However, they observed no MAR benefit within their PCD-CTA dataset. This discrepancy may be attributable to differences in technical parameters and the position and composition of the intracranial implants. In contrast, our comparison between PCD-CTA and EID-CTA showed that MAR reduced signal intensity but decreased noise proportionally more, improving SNR. Halo artifacts were observed around larger implants, occasionally obscuring adjacent vessels, but were markedly less extensive than artifacts without MAR. For smaller implants, artifact severity was generally low. Overall, MAR reduced the spatial extent of artifacts and improved diagnostic confidence, especially for coil-treated aneurysms. In addition, sharp reconstruction kernels combined with optimized tube voltage settings in PCD-CTA may further enhance image quality [14, 25-27]. An important clinical consideration is whether the enhanced image quality provided by PCD-CTA leads to improved patient outcomes. Increased resolution may facilitate earlier detection of small residual or recurrent aneurysms. Further research is needed to determine whether these imaging advances affect treatment planning, follow-up intervals, or long-term outcomes. Given the limited availability of PCD-CT scanners, establishing the comparability of examinations across systems with different detector technologies is essential. Our study has limitations, including its retrospective design, small sample size and number of readers, and single-center setting with specific CT systems, which may limit the generalizability of the findings. Despite the use of CT systems from the same manufacturer and standardized protocols, small differences in technical parameters could have influenced image quality and its evaluation. Nevertheless, the intra-individual comparison design strengthens the reliability of the findings and provides valuable clinical insights into the application of PCD-CTA for imaging intracranial vascular implants. Conclusion Photon counting CTA combined with an iterative metal artifact reduction algorithm, offers improved image quality and radiation dose reduction compared to conventional CTA in patients with intracranial vascular implants. The improved image quality is particularly evident in patients with large implants. Our findings support the clinical integration of PCD-CTA as a non-invasive, high-resolution, dose-reduced imaging modality for neurovascular follow-up. Further multicenter studies with larger cohorts and a focused evaluation of its impact on patient management are warranted. Declarations Funding No funding was received for conducting this study. Competing interests The authors have no competing interests to declare that are relevant to the content of this article. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki and received ethical approval from the local Ethics Committee. Consent to participate This retrospective study was conducted using data obtained during routine clinical care. As confirmed by the local Ethics Committee of the Medical Faculty of the University of Duisburg-Essen, the requirement to obtain informed consent was waived. Availability of data The data are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Authors' contributions D.R. and C.D. conceptualized the study, acquired and analyzed the data, and drafted the original manuscript. All authors critically reviewed previous versions and approved the final manuscript. References Willemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D. Photon-counting CT: Technical Principles and Clinical Prospects. Radiology. 2018;289(2):293-312.https://doi.org/10.1148/radiol.2018172656 Esquivel A, Ferrero A, Mileto A, Baffour F, Horst K, Rajiah PS, et al. Photon-Counting Detector CT: Key Points Radiologists Should Know. 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Diagnostics. 2022;12(6):1306.https://doi.org/10.3390/diagnostics12061306 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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Rosok","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIie3QsWrCQBzH8Z8EOh3emiC0r/CXg4LY0ldJCcTlbJ0km50yCa7nW/gICTdksc16q3To4hDoIrRDL1WnctXR4b7ccIR8+N8d4PNdYkW7Jr/bAA3i4/fgBKH9Xx11LsGRBOwc0q1ey6IhPHOutbjPU3Bebd4nGF67SLR+iktFGCxVmiTjXCJSUgiFkXARKiRpRiAyTOhxns1Whl31GPTji4vUW9LfLanXQg/yDA919fFlycxJjJ2ClhRSJB17MEJ8a99Bxw6ByGypnFNIkb1Lf/6WIjRS9BiN+q4p3VqKZpfdUfti4W6agC+qzSfLhjeuKYfCPwc+AXw+n8/3bz8AnlJDYpzGMgAAAABJRU5ErkJggg==","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Rosok","suffix":""},{"id":531506729,"identity":"832ee149-2bad-40e2-9baa-bf33f124c95c","order_by":1,"name":"Sebastian Zensen","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Zensen","suffix":""},{"id":531506730,"identity":"c408c3ea-d593-4ad1-b76d-b8e9698b1549","order_by":2,"name":"Marcel Opitz","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Marcel","middleName":"","lastName":"Opitz","suffix":""},{"id":531506731,"identity":"706d6d28-0226-49c4-8cc8-08e555119d63","order_by":3,"name":"Denise Bos","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Denise","middleName":"","lastName":"Bos","suffix":""},{"id":531506737,"identity":"e7aaffa3-d8ba-4d8d-a597-7d73635d22f1","order_by":4,"name":"Maximilian Schüssler","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Maximilian","middleName":"","lastName":"Schüssler","suffix":""},{"id":531506738,"identity":"1cd80900-4a9f-4760-ab22-f33d4a1d659d","order_by":5,"name":"Yan Li","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Li","suffix":""},{"id":531506740,"identity":"f1c3418d-c788-41f7-a6fa-a5163d874f53","order_by":6,"name":"Hanna Styczen","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Hanna","middleName":"","lastName":"Styczen","suffix":""},{"id":531506741,"identity":"7eb46d80-514a-41c6-812d-17d43426ae90","order_by":7,"name":"Philipp Dammann","email":"","orcid":"","institution":"Department of Neurosurgery, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Philipp","middleName":"","lastName":"Dammann","suffix":""},{"id":531506742,"identity":"18b0c263-12e8-4e07-bd9f-495faa9a403a","order_by":8,"name":"Ramazan Jabbarli","email":"","orcid":"","institution":"Department of Neurosurgery, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Ramazan","middleName":"","lastName":"Jabbarli","suffix":""},{"id":531506743,"identity":"cfde5026-01ed-4ec3-bec4-fecab37eb821","order_by":9,"name":"Martin Köhrmann","email":"","orcid":"","institution":"Department of Neurology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Köhrmann","suffix":""},{"id":531506744,"identity":"0e8253a4-fefe-4310-9d9c-dafe5c8bbbd6","order_by":10,"name":"Jordi Kühne Escola","email":"","orcid":"","institution":"Department of Neurology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Jordi","middleName":"Kühne","lastName":"Escola","suffix":""},{"id":531506746,"identity":"96d43c10-73c5-488e-9ee0-c1eb30c932b1","order_by":11,"name":"Michael Forsting","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Forsting","suffix":""},{"id":531506750,"identity":"db11553e-f446-43c1-adcc-b6903cd9cc67","order_by":12,"name":"Cornelius Deuschl","email":"","orcid":"","institution":"Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen","correspondingAuthor":false,"prefix":"","firstName":"Cornelius","middleName":"","lastName":"Deuschl","suffix":""}],"badges":[],"createdAt":"2025-09-23 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1","display":"","copyAsset":false,"role":"figure","size":141561,"visible":true,"origin":"","legend":"\u003cp\u003eCase assignment algorithm\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7695127/v1/6e2718ea9270be4410e634c2.jpeg"},{"id":94046563,"identity":"eb580529-b45f-4cd3-b921-e8f1a6fadde4","added_by":"auto","created_at":"2025-10-21 23:07:28","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":128134,"visible":true,"origin":"","legend":"\u003cp\u003eResults of the qualitative image quality assessment\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7695127/v1/ecde1b3ff5e6c478f2246583.jpeg"},{"id":94047553,"identity":"33057836-77ce-4d03-af7c-b299e3761ac7","added_by":"auto","created_at":"2025-10-21 23:15:28","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":169892,"visible":true,"origin":"","legend":"\u003cp\u003eResults of the quantitative image quality analysis\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7695127/v1/e51641a6300025e76565261a.jpeg"},{"id":94046568,"identity":"40120c4c-ecbb-4482-ae71-57b092f77d52","added_by":"auto","created_at":"2025-10-21 23:07:28","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":207137,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Photon-Counting (a) and Energy-Integrating Detector (b) CT Angiography with Metal Artifact Reduction\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7695127/v1/07c566def92386c0d0edbdec.jpeg"},{"id":94046579,"identity":"2f12789a-1cd4-4410-ae83-9dc8fffbd759","added_by":"auto","created_at":"2025-10-21 23:07:28","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":556334,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Photon-Counting Detector CT Angiography without Metal Artifact Reduction (a) and with Metal Artifact Reduction (b)\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7695127/v1/bd99b0bf47b2739454f78f96.jpeg"},{"id":94048320,"identity":"a0b50376-4181-4de9-ba22-d938b1dad5d8","added_by":"auto","created_at":"2025-10-21 23:23:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1734238,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7695127/v1/43678d39-72c0-4bd7-9421-12012387b793.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Photon-Counting CT Angiography vs. Energy-Integrating CT Angiography for Intracranial Vascular Implant Imaging","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePhoton-counting detector (PCD) CT represents a paradigm shift in medical imaging by enabling high-resolution imaging through the counting of individual X-ray photons and measurement of photon energy [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Compared to energy-integrating detectors (EID) used in conventional CT scanners, PCD-CT directly converts photons into electronic signals within a semiconductor substrate, eliminating the intermediate step of converting photons into visible light with a scintillator, as required by EID-CT.\u003c/p\u003e\u003cp\u003eThis technology can offer superior image quality by the lowering of electronic noise and beam-hardening artifacts [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], particularly useful in the imaging of intracranial arteries and metal implants.\u003c/p\u003e\u003cp\u003eIntracranial neurovascular implants\u0026mdash;such as clips, coils, and intrasaccular devices\u0026mdash;are used for aneurysm therapy and other cerebrovascular conditions. Following neuroradiological and neurosurgical interventions, imaging is essential to assess treatment efficacy and detect potential complications. Digital subtraction angiography (DSA) remains the gold standard for imaging intracranial vessels due to its high diagnostic accuracy and its insusceptibility to metal artifacts [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, as an invasive procedure, it carries a small risk of periprocedural complications [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Non-invasive alternatives such as EID CT angiography (CTA) and MR angiography (MRA) are widely used, but both have limitations\u0026mdash;CTA is affected by beam hardening artifacts, while MRA offers lower spatial resolution [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The integration of the new PCD-CTA might offer the potential to improve image quality and diagnostic accuracy in patients with intracranial vascular implants. PCD-CTA for imaging intracranial vascular implants has been previously explored in vitro and compared to flat panel CTA in a phantom-study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and to digital subtraction angiography in vivo [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, no systematic evaluation has yet compared PCD-CTA with conventional CTA for intracranial vascular devices intra-individual in vivo. The objective of this study was to analyze the image quality, diagnostic value and radiation dose of PCD-CTA in patients with intracranial implants compared to EID-CTA.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eComposition of the study cohort\u003c/p\u003e\n\u003cp\u003eThis retrospective, single-center, observational cohort study was approved by the local ethics committee of our institution and adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational studies [17, 18]. The initial study sample included all patients who underwent cranial CT imaging using the PCD-CT system \u0026ldquo;NAEOTOM Alpha\u0026rdquo; (Siemens Healthineers, Erlangen, Germany) between April 2023 and March 2024. Patients were recruited consecutively. From this cohort, only patients with intracranial vascular implants who had undergone both dual-source PCD-CTA and dual-source EID-CTA on comparable state-of-the-art systems were included to enable intra-individual comparison under similar conditions. The comparator EID-CT system was the dual-source 256-slice (2 x 128) \u0026ldquo;SOMATOM Definition Flash\u0026rdquo; (Siemens Healthineers, Erlangen, Germany). These patients underwent follow-up examinations after endovascular or neurosurgical treatment at our university hospital. The primary outcome of the study was image quality, assessed both subjectively via a 5-point Likert scale for artifacts and diagnostic value, and objectively via signal-to-noise ratios (SNR).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eImage acquisition parameters\u003c/p\u003e\n\u003cp\u003eStandardized protocols were applied for both PCD-CTA and EID-CTA examinations. The cerebral vasculature was scanned from the skull base to the vertex without gantry tilt. CTA was performed after intravenous injection of 70 ml iodinated contrast medium (Ultravist-300, iopromide; Bayer Healthcare, Berlin, Germany) at 4 ml/s. Contrast enhancement of the common carotid artery was monitored, and scanning commenced five seconds after reaching the predefined attenuation threshold. Key acquisition and reconstruction parameters are summarized in table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eImage acquisition and reconstruction parameters\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhoton-counting CT angiography\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnergy-integrating CT angiography\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcquisition parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eTube voltage (kVp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e80 (A-tube)/ Sn140 (B-tube)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eTube current (image quality level/ reference mAs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003eWith modulation and vendor-specific image quality level of 145\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003eWith modulation and 222 mAs as reference for tube A and 111 mAs for tube B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eRotation time (s/ rotation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eCollimation (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e0.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003ePitch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e0.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e0.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReconstruction parameters\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eReconstruction type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003eiterative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003eiterative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eMatrix size/ pixel no.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e512 x 512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e512 x 512\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eKernel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003eQ40f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003eBv40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.2781%;\"\u003e\n \u003cp\u003eSlice thickness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.4503%;\"\u003e\n \u003cp\u003e1mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 34.2715%;\"\u003e\n \u003cp\u003e1mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eQualitative evaluation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne board-certified neuroradiologist (CD, 13 years of experience) and one radiology resident (DR, 4 years of experience) independently evaluated the image quality of the CTA with iterative metal artifact reduction (MAR) using a Likert scale. First, the readers were blinded to image type and patient identity and reviewed all images independently in a random order. Secondly, the results were compared and, in the event of discrepant scores, a joint discussion of the findings was held, resulting in consensus. The areas directly adjacent to the intracranial vascular devices were rated regarding the quantity of artifacts and the diagnostic value of the examination (with options: 5 = very mild artifacts, excellent diagnostic value, 4 = mild artifacts, completely acceptable diagnostic value, 3 = moderate artifacts, mostly acceptable diagnostic value, 2 = strong artifacts, suboptimal diagnostic value, 1 = very strong artifacts, unacceptable diagnostic value).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQuantitative evaluation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSNR were used for quantitative analysis of CTA. SNR were defined as the mean attenuation values in Hounsfield units (HU) divided by their standard deviation (SD) from each region of interest (ROl). The ROIs were placed directly adjacent to the neurovascular implant in the artery of diagnostic interest. Average ROI sizes of approximately 10 mm\u0026sup2; were selected based on the respective vessel dimensions and placed within the contrast-enhanced arterial lumen. The same representative vessel areas with identical ROI sizes were chosen for PCD-CTA and EID-CTA scans. Analyses were carried out separately on the original and the automatically post-processed images with MAR.\u003c/p\u003e\n\u003cp\u003eRadiation dose analysis\u003c/p\u003e\n\u003cp\u003eThe radiation exposure parameters volume-weighted computed tomography dose index (CTDIvol) and dose-length product (DLP) were extracted from Digital Imaging and Communications in Medicine protocols.\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eData analysis was conducted using SPSS Version 27.0 (IBM Corp, Armonk, NY, USA; RRID:SCR_016479). Normality of distributions was assessed using the Shapiro-Wilk test. As the variables were not normally distributed, non-parametric data are reported as medians with interquartile ranges (IQR), and categorical variables are presented as frequencies and percentages. Intra-individual comparisons of patients who underwent both PCD-CTA and EID-CTA were performed using the Wilcoxon signed-rank test to assess differences in Likert scores, SNR, and radiation dose parameters. A two-sided \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 was considered statistically significant. Figures were created using GraphPad Prism Version 5.0 (GraphPad Software, La Jolla, CA, USA; RRID:SCR_002798).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eComposition of the study cohort\u003c/p\u003e\n\u003cp\u003eDuring the study period, 693 PCD-CT examinations of the head and intracranial vasculature were performed, identifying 52 patients (7.5 %, 52/693) with intracranial vascular implants (42 females, 80.8 %; median age 59.3 years, IQR 14.8, range 20.8\u0026ndash;83.9). Multiple PCD-CTs were performed in 9 patients (17.3 %, 9/52). Intracranial aneurysms were the most common indication for implants, affecting mainly the middle cerebral artery (42.3 %, 22/52), anterior communicating artery (34.6 %, 18/52), internal carotid artery (17.3 %, 9/52), posterior inferior cerebellar artery (7.7 %, 4/52), and basilar artery tip (3.8 %, 2/52). Single cases involved the pericallosal and posterior communicating arteries (1.9 %, 1/52 each), with other indications including arteriovenous malformations (2 cases) and a dural arteriovenous fistula (1 case). Table 2 summarizes the distribution of intracranial vascular implant types among the 52 patients identified with neurovascular devices during the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e Distribution of intracranial vascular implant types\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntracranial vascular implant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of patients (% of 52 patients)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eClip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e26 (50.0 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eCoil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e16 (30.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eCoil + clip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e2 (3.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eFlow diverter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e2 (3.8 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eStent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e1 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eWeb-device\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e1 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eCoil + stent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e1 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eFlow diverter + coil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e1 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eFlow diverter + clip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e1 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.1481%;\"\u003e\n \u003cp\u003eCoil + stent + clip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51.8519%;\"\u003e\n \u003cp\u003e1 (1.9 %)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFor image quality comparison between PCD-CTA and EID-CTA, patients were excluded in sequential steps. Four patients with CTA but without a comparable EID-CT were excluded (7.7 %, 4/52). Non-contrast CTs (73.1 %, 38/52) were also excluded, as the study focused on CTA and images with and without MAR were not consistently available. Only patients with complete PCD-CTA and EID-CTA datasets, including images with and without MAR, were included, yielding a final cohort of 10 patients (19.2 %, 10/52). The final cohort comprised 90% females (9/10) and a median age of 56.5 years (IQR 7.2, range 38\u0026ndash;72). In this subgroup, implants comprised clips (60%, 6/10), flow diverters with coils (20%, 2/10), a clip with coil (10%, 1/10), and a combination of coil, clip, and stent (10%, 1/10). Only CTA examinations were further analyzed. Figure 1 illustrates the case assignment algorithm and exclusion process. Three sequential exclusion steps were applied to derive the final study cohort.\u003c/p\u003e\n\u003cp\u003eQualitative evaluation\u003c/p\u003e\n\u003cp\u003eAll patients showed significantly fewer artifacts and higher diagnostic value for PCD-CTA compared to EID-CTA. For artifacts, PCD-CTA had a median Likert score of 4.5 (IQR 4\u0026ndash;5) compared to 3 (IQR 2.8\u0026ndash;3) for EID-CTA (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.004). For diagnostic value, PCD-CTA had a median Likert score of 5 (IQR 4\u0026ndash;5) compared to 3 (IQR 3\u0026ndash;3.75) for EID-CTA (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.004). Figure 2 illustrates the differences in image quality between PCD-CTA and EID-CTA with respect to artifact prevalence and overall diagnostic value.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQuantitative evaluation\u003c/p\u003e\n\u003cp\u003eFor signal, PCD-CTA had a median HU of 385.5 (IQR 272.8\u0026ndash;474.8) with MAR and 431 (IQR 321\u0026ndash;500) without MAR, whereas EID-CTA had a median of 211.5 (IQR 170.5\u0026ndash;301.5) with MAR and 146 (IQR 136.3\u0026ndash;188.3) without MAR. Signal was significantly higher for PCD-CTA compared to EID-CTA (\u003cem\u003ep\u003c/em\u003e = 0.005 for both MAR and no MAR).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor noise, PCD-CTA had a median SD of 10.5 (IQR 5.5\u0026ndash;17.3) with MAR and 26 (IQR 18.8\u0026ndash;53.8) without MAR, compared to 9 (IQR 6\u0026ndash;24.3) with MAR and 14.5 (IQR 11.0\u0026ndash;31.8) without MAR in EID-CTA. Noise was not significantly different with MAR (\u003cem\u003ep\u003c/em\u003e = 0.312) but was higher for PCD-CTA without MAR compared to EID-CTA (\u003cem\u003ep\u003c/em\u003e = 0.041).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor SNR, PCD-CTA achieved a median of 34.4 (IQR 17.7\u0026ndash;80.6) with MAR and 17.1 (IQR 7.2\u0026ndash;25.5) without MAR, while EID-CTA showed a median of 27.8 (IQR 7.1\u0026ndash;40.2) with MAR and 9.9 (IQR 5.0\u0026ndash;16.1) without MAR. SNR was significantly higher for PCD-CTA compared to EID-CTA with MAR (\u003cem\u003ep\u003c/em\u003e = 0.005), but not significantly different without MAR (\u003cem\u003ep\u003c/em\u003e = 0.203). Figure 3 shows the image quality differences of PCD-CTA and EID-CTA assessed by signal, noise and SNR. Figures 4 and 5 illustrate the superior vessel delineation in PCD-CTA compared to EID-CTA and the valuable effect of MAR in PCD-CTA of neurovascular implants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRadiation dose analysis\u003c/p\u003e\n\u003cp\u003eRadiation exposure was significantly lower with PCD-CTA compared to EID-CTA. Median CTDIvol was 6.1 mGy (IQR 6.1\u0026ndash;6.2) versus 13.8 mGy (IQR 12.9\u0026ndash;14.6) for EID-CTA, corresponding to a 55.8 % reduction (\u003cem\u003ep\u003c/em\u003e = 0.008). Median DLP was 109 mGy\u0026middot;cm (IQR, 106\u0026ndash;117) versus 214 mGy\u0026middot;cm (IQR, 203\u0026ndash;231), representing a 49.1 % reduction (\u003cem\u003ep\u003c/em\u003e = 0.011).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrates that PCD-CTA of intracranial implants provides superior qualitative and quantitative image quality compared to conventional EID-CTA. The higher diagnostic value of PCD-CTA was attributed to subjectively improved vascular contrast with sharper margins and objectively higher SNR with the application of MAR. This could clinically enhance visualization of vessels adjacent to the neurovascular implant (Figures 4 and 5), improve non-invasive assessment of vessel patency, and aid in the exclusion of aneurysmal remnants or reperfusion. Moreover, PCD-CTA was associated with significantly lower radiation exposure than EID-CTA, with a 56% reduction in median CTDIvol and a 49% reduction in median DLP. This reduction represents a major clinical advantage, particularly for patients requiring repeated follow-up imaging of intracranial implants, as it minimizes cumulative radiation exposure while maintaining superior image quality.\u003c/p\u003e\n\u003cp\u003eTo assess the effect of MAR on image quality, PCD-CTA and EID-CTA were analyzed with and without MAR. Improved image quality was observed for PCD-CTA only when MAR was applied, highlighting the critical role of artifact reduction [19]. Sharper vessel delineation in PCD-CTA likely reflects the superior spatial resolution of photon-counting detectors [1]. Signal measured in vessels adjacent to intracranial implants was significantly higher in PCD-CTA than in EID-CTA, both with and without MAR, likely due to PCDs\u0026rsquo; ability to capture more photons and suppress electronic noise [1]. PCD-CTA without MAR exhibited higher noise levels than EID-CTA, possibly because inclusion of low-energy photons increases beam-hardening artifacts [1, 20], which are pronounced around intracranial implants. Thus, MAR in PCD-CTA is particularly important for denoising and correcting beam-hardening artifacts.\u003c/p\u003e\n\u003cp\u003eIntracranial aneurysms were the most common indication for intracranial devices in our cohort, with clips being the most frequent implant type. The cohort showed a female predominance, which may reflect the higher prevalence of intracranial aneurysms in women [21]. The median age was 56 years, consistent with the typical peak age for aneurysm presentation [21].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSymons et al. were among the first to highlight the potential of PCD-CTA for intracranial imaging [22]. Using a prototype PCD-CT\u0026mdash;where one EID subsystem of a dual-source CT was replaced by a PCD\u0026mdash;they demonstrated benefits in artifact reduction, with both PCD-CT and EID-CT acquisitions performed sequentially after a single iodine contrast injection [22]. Our in vivo findings align with Schmitt et al., who showed in an experimental PCD-CT model that applying MAR enhances visualization of neurovascular coils by reducing beam-hardening artifacts [23]. We could confirm that PCD-CTA produces higher noise than EID-CTA without MAR, and in the absence of MAR, both modalities yielded relatively high noise levels, affecting SNR. Similar improvements in small-vessel imaging were reported by Si-Mohamed et al. in coronary stents, with PCD-CTA showing superior image quality and higher intraluminal HU signal than EID-CTA, without significantly different noise [24]. De Beukelaer et al., in comparison with DSA, demonstrated that ultra-high-resolution PCD-CTA effectively assesses in-stent stenosis and aneurysm remnants in intracranial implants [15, 16], supporting its potential as a non-invasive alternative for postinterventional follow-up. Their reported DLP values were consistent with our dose measurements [16]. However, they observed no MAR benefit within their PCD-CTA dataset. This discrepancy may be attributable to differences in technical parameters and the position and composition of the intracranial implants. In contrast, our comparison between PCD-CTA and EID-CTA showed that MAR reduced signal intensity but decreased noise proportionally more, improving SNR. Halo artifacts were observed around larger implants, occasionally obscuring adjacent vessels, but were markedly less extensive than artifacts without MAR. For smaller implants, artifact severity was generally low. Overall, MAR reduced the spatial extent of artifacts and improved diagnostic confidence, especially for coil-treated aneurysms. In addition, sharp reconstruction kernels combined with optimized tube voltage settings in PCD-CTA may further enhance image quality [14, 25-27].\u003c/p\u003e\n\u003cp\u003eAn important clinical consideration is whether the enhanced image quality provided by PCD-CTA leads to improved patient outcomes. Increased resolution may facilitate earlier detection of small residual or recurrent aneurysms. Further research is needed to determine whether these imaging advances affect treatment planning, follow-up intervals, or long-term outcomes. Given the limited availability of PCD-CT scanners, establishing the comparability of examinations across systems with different detector technologies is essential.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study has limitations, including its retrospective design, small sample size and number of readers, and single-center setting with specific CT systems, which may limit the generalizability of the findings. Despite the use of CT systems from the same manufacturer and standardized protocols, small differences in technical parameters could have influenced image quality and its evaluation. Nevertheless, the intra-individual comparison design strengthens the reliability of the findings and provides valuable clinical insights into the application of PCD-CTA for imaging intracranial vascular implants.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePhoton counting CTA combined with an iterative metal artifact reduction algorithm, offers improved image quality and radiation dose reduction compared to conventional CTA in patients with intracranial vascular implants. The improved image quality is particularly evident in patients with large implants. Our findings support the clinical integration of PCD-CTA as a non-invasive, high-resolution, dose-reduced imaging modality for neurovascular follow-up. Further multicenter studies with larger cohorts and a focused evaluation of its impact on patient management are warranted.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eNo funding was received for conducting this study.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics approval\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki and received ethical approval from the local Ethics Committee.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent to participate\u003c/p\u003e\n\u003cp\u003eThis retrospective study was conducted using data obtained during routine clinical care. As confirmed by the local Ethics Committee of the Medical Faculty of the University of Duisburg-Essen, the requirement to obtain informed consent was waived.\u003c/p\u003e\n\u003cp\u003eAvailability of data\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eD.R. and C.D. conceptualized the study, acquired and analyzed the data, and drafted the original manuscript. All authors critically reviewed previous versions and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWillemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D. Photon-counting CT: Technical Principles and Clinical Prospects. 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Diagnostics. 2022;12(6):1306.https://doi.org/10.3390/diagnostics12061306\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Energy-integrating CT angiography, Intracranial vascular implants, Neurovascular imaging, Photon-counting CT angiography","lastPublishedDoi":"10.21203/rs.3.rs-7695127/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7695127/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003ePhoton-counting detector (PCD) CT angiography (CTA) is an emerging technology that improves spatial resolution and reduces artifacts, potentially enhancing imaging of intracranial implants. No in vivo intra-individual comparisons with energy-integrating detector (EID) CTA in patients with intracranial vascular implants have been reported. The purpose was to fill that gap by directly comparing PCD-CTA and EID-CTA.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eIn this retrospective single-center observational study, all patients with intracranial vascular implants scanned with PCD-CT from April 2023 to March 2024 were included after ethics approval. Intra-individual comparisons were performed using dual-source EID-CT from the same manufacturer. Image quality was evaluated subjectively with a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;lowest, 5\u0026thinsp;=\u0026thinsp;highest) and objectively via signal-to-noise ratios (SNR). Wilcoxon signed-rank tests were used for statistical analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 693 PCD-CT scans, 52 patients (7.5%) had intracranial vascular implants; 10 underwent both PCD-CTA and EID-CTA (median age 56.5 years, IQR 53.8\u0026ndash;61; 90% female). PCD-CTA with iterative metal artifact reduction (MAR) demonstrated fewer artifacts and higher diagnostic value than EID-CTA (median Likert scores 4.5 and 5 vs. 3 and 3; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Objective image quality was superior with PCD-CTA compared to EID-CTA with MAR (SNR 34.4 vs. 17.1; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) but not significantly different without MAR (27.8 vs. 9.9; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.203).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003ePCD-CTA with MAR offers superior image quality and artifact reduction in patients with intracranial vascular implants, highlighting its potential as a non-invasive alternative for follow-up imaging. Larger studies are warranted to validate these findings.\u003c/p\u003e","manuscriptTitle":"Photon-Counting CT Angiography vs. Energy-Integrating CT Angiography for Intracranial Vascular Implant Imaging","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 23:07:23","doi":"10.21203/rs.3.rs-7695127/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4a04468b-edfa-4444-9a0b-8d976e770efe","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-21T23:07:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 23:07:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7695127","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7695127","identity":"rs-7695127","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}