Comparison of ultrahigh and standard resolution photon-counting CT angiography of the femoral arteries in a continuously perfused in vitro model.

CT angiography Femoral arteries Photon-counting computed tomography (CT) Small pixel effect Ultrahigh resolution

Journal

European radiology experimental
ISSN: 2509-9280
Titre abrégé: Eur Radiol Exp
Pays: England
ID NLM: 101721752

Informations de publication

Date de publication:
18 Dec 2023
Historique:
received: 27 07 2023
accepted: 17 10 2023
medline: 19 12 2023
pubmed: 19 12 2023
entrez: 19 12 2023
Statut: epublish

Résumé

With the emergence of photon-counting CT, ultrahigh-resolution (UHR) imaging can be performed without dose penalty. This study aims to directly compare the image quality of UHR and standard resolution (SR) scan mode in femoral artery angiographies. After establishing continuous extracorporeal perfusion in four fresh-frozen cadaveric specimens, photon-counting CT angiographies were performed with a radiation dose of 5 mGy and tube voltage of 120 kV in both SR and UHR mode. Images were reconstructed with dedicated convolution kernels (soft: Body-vascular (Bv)48; sharp: Bv60; ultrasharp: Bv76). Six radiologists evaluated the image quality by means of a pairwise forced-choice comparison tool. Kendall's concordance coefficient (W) was calculated to quantify interrater agreement. Image quality was further assessed by measuring intraluminal attenuation and image noise as well as by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR). UHR yielded lower noise than SR for identical reconstructions with kernels ≥ Bv60 (p < 0.001). UHR scans exhibited lower intraluminal attenuation compared to SR (Bv60: 406.4 ± 25.1 versus 418.1 ± 30.1 HU; p < 0.001). Irrespective of scan mode, SNR and CNR decreased while noise increased with sharper kernels but UHR scans were objectively superior to SR nonetheless (Bv60: SNR 25.9 ± 6.4 versus 20.9 ± 5.3; CNR 22.7 ± 5.8 versus 18.4 ± 4.8; p < 0.001). Notably, UHR scans were preferred in subjective assessment when images were reconstructed with the ultrasharp Bv76 kernel, whereas SR was rated superior for Bv60. Interrater agreement was high (W = 0.935). Combinations of UHR scan mode and ultrasharp convolution kernel are able to exploit the full image quality potential in photon-counting CT angiography of the femoral arteries. The UHR scan mode offers improved image quality and may increase diagnostic accuracy in CT angiography of the peripheral arterial runoff when optimized reconstruction parameters are chosen. • UHR photon-counting CT improves image quality in combination with ultrasharp convolution kernels. • UHR datasets display lower image noise compared with identically reconstructed standard resolution scans. • Scans in UHR mode show decreased intraluminal attenuation compared with standard resolution imaging.

Sections du résumé

BACKGROUND BACKGROUND
With the emergence of photon-counting CT, ultrahigh-resolution (UHR) imaging can be performed without dose penalty. This study aims to directly compare the image quality of UHR and standard resolution (SR) scan mode in femoral artery angiographies.
METHODS METHODS
After establishing continuous extracorporeal perfusion in four fresh-frozen cadaveric specimens, photon-counting CT angiographies were performed with a radiation dose of 5 mGy and tube voltage of 120 kV in both SR and UHR mode. Images were reconstructed with dedicated convolution kernels (soft: Body-vascular (Bv)48; sharp: Bv60; ultrasharp: Bv76). Six radiologists evaluated the image quality by means of a pairwise forced-choice comparison tool. Kendall's concordance coefficient (W) was calculated to quantify interrater agreement. Image quality was further assessed by measuring intraluminal attenuation and image noise as well as by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR).
RESULTS RESULTS
UHR yielded lower noise than SR for identical reconstructions with kernels ≥ Bv60 (p < 0.001). UHR scans exhibited lower intraluminal attenuation compared to SR (Bv60: 406.4 ± 25.1 versus 418.1 ± 30.1 HU; p < 0.001). Irrespective of scan mode, SNR and CNR decreased while noise increased with sharper kernels but UHR scans were objectively superior to SR nonetheless (Bv60: SNR 25.9 ± 6.4 versus 20.9 ± 5.3; CNR 22.7 ± 5.8 versus 18.4 ± 4.8; p < 0.001). Notably, UHR scans were preferred in subjective assessment when images were reconstructed with the ultrasharp Bv76 kernel, whereas SR was rated superior for Bv60. Interrater agreement was high (W = 0.935).
CONCLUSIONS CONCLUSIONS
Combinations of UHR scan mode and ultrasharp convolution kernel are able to exploit the full image quality potential in photon-counting CT angiography of the femoral arteries.
RELEVANCE STATEMENT CONCLUSIONS
The UHR scan mode offers improved image quality and may increase diagnostic accuracy in CT angiography of the peripheral arterial runoff when optimized reconstruction parameters are chosen.
KEY POINTS CONCLUSIONS
• UHR photon-counting CT improves image quality in combination with ultrasharp convolution kernels. • UHR datasets display lower image noise compared with identically reconstructed standard resolution scans. • Scans in UHR mode show decreased intraluminal attenuation compared with standard resolution imaging.

Identifiants

pubmed: 38110729
doi: 10.1186/s41747-023-00398-x
pii: 10.1186/s41747-023-00398-x
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

83

Subventions

Organisme : Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum Würzburg
ID : Z-02CSP/18
Organisme : Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum Würzburg
ID : Z-3BC/02
Organisme : Julius-Maximilians-Universität Würzburg
ID : Publication Fund

Informations de copyright

© 2023. The Author(s).

Références

McCollough CH, Leng S, Yu L et al (2015) Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology 276:637–653. https://doi.org/10.1148/radiol.2015142631
doi: 10.1148/radiol.2015142631 pubmed: 26302388
Lell MM, Wildberger JE, Alkadhi H et al (2015) Evolution in computed tomography: the battle for speed and dose. Invest Radiol 50:629–644. https://doi.org/10.1097/RLI.0000000000000172
doi: 10.1097/RLI.0000000000000172 pubmed: 26135019
Willemink MJ, Persson M, Pourmorteza A et al (2018) Photon-counting CT: technical principles and clinical prospects. Radiology 289:293–312. https://doi.org/10.1148/radiol.2018172656
doi: 10.1148/radiol.2018172656 pubmed: 30179101
Flohr TG, Stierstorfer K, Süss C et al (2007) Novel ultrahigh resolution data acquisition and image reconstruction for multi-detector row CT. Med Phys 34:1712–1723. https://doi.org/10.1118/1.2722872
doi: 10.1118/1.2722872 pubmed: 17555253
Esquivel A, Ferrero A, Mileto A et al (2022) Photon-counting detector CT: key points radiologists should know. Korean J Radiol 23:854–865. https://doi.org/10.3348/kjr.2022.0377
doi: 10.3348/kjr.2022.0377 pubmed: 36047540 pmcid: 9434736
Kawashima H, Ichikawa K, Takata T et al (2020) Technical note: performance comparison of ultra-high-resolution scan modes of two clinical computed tomography systems. Med Phys 47:488–497. https://doi.org/10.1002/mp.13949
doi: 10.1002/mp.13949 pubmed: 31808550
Lell M, Kachelrieß M (2023) Computed tomography 2.0: new detector technology, ai, and other developments. Invest Radiol 58:587–601. https://doi.org/10.1097/RLI.0000000000000995
doi: 10.1097/RLI.0000000000000995 pubmed: 37378467 pmcid: 10332658
Leng S, Yu Z, Halaweish A et al (2016) Dose-efficient ultrahigh-resolution scan mode using a photon counting detector computed tomography system. J Med Imaging (Bellingham) 3:43504. https://doi.org/10.1117/1.JMI.3.4.043504
doi: 10.1117/1.JMI.3.4.043504
Meloni A, Frijia F, Panetta D et al. (2023) Photon-counting computed tomography (PCCT): technical background and cardio-vascular applications. Diagnostics (Basel) 13. https://doi.org/10.3390/diagnostics13040645
Leng S, Rajendran K, Gong H et al (2018) 150-μm spatial resolution using photon-counting detector computed tomography technology: technical performance and first patient images. Invest Radiol 53:655–662. https://doi.org/10.1097/RLI.0000000000000488
doi: 10.1097/RLI.0000000000000488 pubmed: 29847412 pmcid: 6173631
Alkadhi H, Euler A (2020) The future of computed tomography: personalized, functional, and precise. Invest Radiol 55:545–555. https://doi.org/10.1097/RLI.0000000000000668
doi: 10.1097/RLI.0000000000000668 pubmed: 32209817
Wildberger JE, Alkadhi H (2023) New horizons in vascular imaging with photon-counting detector CT. Invest Radiol 58:499–504. https://doi.org/10.1097/RLI.0000000000000957
doi: 10.1097/RLI.0000000000000957 pubmed: 36735383
Zsarnóczay E, Varga-Szemes A, Emrich T et al (2023) Characterizing the heart and the myocardium with photon-counting CT. Invest Radiol 58:505–514. https://doi.org/10.1097/RLI.0000000000000956
doi: 10.1097/RLI.0000000000000956 pubmed: 36822653
Mannil M, Hickethier T, von Spiczak J et al (2018) Photon-counting CT: high-resolution imaging of coronary stents. Invest Radiol 53:143–149. https://doi.org/10.1097/RLI.0000000000000420
doi: 10.1097/RLI.0000000000000420 pubmed: 28945655
von Spiczak J, Mannil M, Peters B et al (2018) Photon counting computed tomography with dedicated sharp convolution kernels: tapping the potential of a new technology for stent imaging. Invest Radiol 53:486–494. https://doi.org/10.1097/RLI.0000000000000485
doi: 10.1097/RLI.0000000000000485
Si-Mohamed SA, Boccalini S, Lacombe H et al (2022) Coronary CT angiography with photon-counting CT: first-in-human results. Radiology 303:303–313. https://doi.org/10.1148/radiol.211780
doi: 10.1148/radiol.211780 pubmed: 35166583
Rajagopal JR, Farhadi F, Richards T et al (2021) Evaluation of coronary plaques and stents with conventional and photon-counting CT: benefits of high-resolution photon-counting CT. Radiol Cardiothorac Imaging 3:e210102. https://doi.org/10.1148/ryct.2021210102
doi: 10.1148/ryct.2021210102 pubmed: 34778782 pmcid: 8581588
Gassenmaier T, Petri N, Allmendinger T et al (2014) Next generation coronary CT angiography: In vitro evaluation of 27 coronary stents. Eur Radiol 24:2953–2961. https://doi.org/10.1007/s00330-014-3323-6
doi: 10.1007/s00330-014-3323-6 pubmed: 25038859
Zsarnoczay E, Fink N, Schoepf UJ et al (2023) Ultra-high resolution photon-counting coronary CT angiography improves coronary stenosis quantification over a wide range of heart rates - a dynamic phantom study. Eur J Radiol 161:110746. https://doi.org/10.1016/j.ejrad.2023.110746
doi: 10.1016/j.ejrad.2023.110746 pubmed: 36821957
Remy-Jardin M, Hutt A, Flohr T et al (2023) Ultra-high-resolution photon-counting CT imaging of the chest: a new era for morphology and function. Invest Radiol 58:482–487. https://doi.org/10.1097/RLI.0000000000000968
doi: 10.1097/RLI.0000000000000968 pubmed: 36897831
Si-Mohamed S, Boccalini S, Rodesch P-A et al (2021) Feasibility of lung imaging with a large field-of-view spectral photon-counting CT system. Diagn Interv Imaging 102:305–312. https://doi.org/10.1016/j.diii.2021.01.001
doi: 10.1016/j.diii.2021.01.001 pubmed: 33610503
Grunz J-P, Huflage H, Heidenreich JF et al (2021) Image quality assessment for clinical cadmium telluride-based photon-counting computed tomography detector in cadaveric wrist imaging. Invest Radiol 56:785–790. https://doi.org/10.1097/RLI.0000000000000789
doi: 10.1097/RLI.0000000000000789 pubmed: 33882030
Conrads N, Grunz JP, Huflage H et al (2023) Ultrahigh-resolution computed tomography of the cervical spine without dose penalty employing a cadmium-telluride photon-counting detector. Eur J Radiol 160:110718. https://doi.org/10.1016/j.ejrad.2023.110718
doi: 10.1016/j.ejrad.2023.110718 pubmed: 36731400
Patzer TS, Kunz AS, Huflage H et al. (2023) Ultrahigh-resolution photon-counting CT in cadaveric fracture models: spatial frequency is not everything. Diagnostics (Basel) 13. https://doi.org/10.3390/diagnostics13101677
Rajendran K, Baffour F, Powell G et al (2023) Improved visualization of the wrist at lower radiation dose with photon-counting-detector CT. Skeletal Radiol 52:23–29. https://doi.org/10.1007/s00256-022-04117-2
doi: 10.1007/s00256-022-04117-2 pubmed: 35831718
Gruschwitz P, Hartung V, Kleefeldt F et al (2023) Photon-counting versus energy-integrating detector CT angiography of the lower extremity in a human cadaveric model with continuous extracorporeal perfusion. Invest Radiol. https://doi.org/10.1097/RLI.0000000000000982
doi: 10.1097/RLI.0000000000000982 pubmed: 37812470
Sandfort V, Choi Y, Symons R et al (2020) An optimized test bolus contrast injection protocol for consistent coronary artery luminal enhancement for coronary CT angiography. Acad Radiol 27:371–380. https://doi.org/10.1016/j.acra.2019.05.003
doi: 10.1016/j.acra.2019.05.003 pubmed: 31155485
Gruschwitz P, Hartung V, Kleefeldt F et al (2023) Continuous extracorporeal femoral perfusion model for intravascular ultrasound, computed tomography and digital subtraction angiography. PLoS One 18:e0285810. https://doi.org/10.1371/journal.pone.0285810
doi: 10.1371/journal.pone.0285810 pubmed: 37220113 pmcid: 10204951
Bradley RA, Terry ME (1952) Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika 39:324–345. https://doi.org/10.2307/2334029
doi: 10.2307/2334029
Booij R, Kämmerling NF, Oei EHG et al (2023) Assessment of visibility of bone structures in the wrist using normal and half of the radiation dose with photon-counting detector CT. Eur J Radiol 159:110662. https://doi.org/10.1016/j.ejrad.2022.110662
doi: 10.1016/j.ejrad.2022.110662 pubmed: 36565594
Kämmerling N, Sandstedt M, Farnebo S et al (2022) Assessment of image quality in photon-counting detector computed tomography of the wrist - an ex vivo study. Eur J Radiol 154:110442. https://doi.org/10.1016/j.ejrad.2022.110442
doi: 10.1016/j.ejrad.2022.110442 pubmed: 35849959
Kosmala A, Weng AM, Schmid A et al (2022) Dual-energy CT angiography in peripheral arterial occlusive disease: diagnostic accuracy of different image reconstruction approaches. Acad Radiol 29(Suppl 4):S59–S68. https://doi.org/10.1016/j.acra.2020.10.028
doi: 10.1016/j.acra.2020.10.028 pubmed: 33189548
Klink T, Wilhelm T, Roth C et al (2017) Dual-energy CTA in patients with symptomatic peripheral arterial occlusive disease: study: Studie über die diagnostische Genauigkeit und limitierende Faktoren (dual-energy CTA in patients with symptomatic peripheral arterial occlusive disease: study of diagnostic accuracy and impeding factors). Rofo 189:441–452. https://doi.org/10.1055/s-0043-101526
doi: 10.1055/s-0043-101526 pubmed: 28249314
Decker JA, O’Doherty J, Schoepf UJ et al (2023) Stent imaging on a clinical dual-source photon-counting detector CT system-impact of luminal attenuation and sharp kernels on lumen visibility. Eur Radiol 33:2469–2477. https://doi.org/10.1007/s00330-022-09283-4
doi: 10.1007/s00330-022-09283-4 pubmed: 36462045
Petritsch B, Petri N, Weng AM et al (2021) Photon-Counting Computed Tomography for Coronary Stent Imaging. In Vitro Evaluation of 28 Coronary Stents. Invest Radiol 56:653–660. https://doi.org/10.1097/RLI.0000000000000787
doi: 10.1097/RLI.0000000000000787 pubmed: 33867450
Hata A, Yanagawa M, Honda O et al (2018) Effect of Matrix Size on the Image Quality of Ultra-high-resolution CT of the Lung: Comparison of 512 × 512, 1024 × 1024, and 2048 × 2048. Acad Radiol 25:869–876. https://doi.org/10.1016/j.acra.2017.11.017
doi: 10.1016/j.acra.2017.11.017 pubmed: 29373211
Hsieh SS, Leng S, Rajendran K et al (2021) Photon Counting CT: Clinical Applications and Future Developments. IEEE Trans Radiat Plasma Med Sci 5:441–452. https://doi.org/10.1109/TRPMS.2020.3020212
doi: 10.1109/TRPMS.2020.3020212 pubmed: 34485784
Huflage H, Hendel R, Kunz AS et al (2023) Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung. Invest Radiol. https://doi.org/10.1097/RLI.0000000000001013
doi: 10.1097/RLI.0000000000001013 pubmed: 37812470
Milos R-I, Röhrich S, Prayer F et al (2023) Ultrahigh-Resolution Photon-Counting Detector CT of the Lungs: Association of Reconstruction Kernel and Slice Thickness With Image Quality. AJR Am J Roentgenol 220:672–680. https://doi.org/10.2214/AJR.22.28515
doi: 10.2214/AJR.22.28515 pubmed: 36475813
Rajendran K, Petersilka M, Henning A et al (2022) First Clinical Photon-counting Detector CT System: Technical Evaluation. Radiology 303:130–138. https://doi.org/10.1148/radiol.212579
doi: 10.1148/radiol.212579 pubmed: 34904876
Klein L, Dorn S, Amato C et al (2020) Effects of Detector Sampling on Noise Reduction in Clinical Photon-Counting Whole-Body Computed Tomography. Invest Radiol 55:111–119. https://doi.org/10.1097/RLI.0000000000000616
doi: 10.1097/RLI.0000000000000616 pubmed: 31770298
Heye T, Knoerl R, Wehrle T et al (2020) The Energy Consumption of Radiology: Energy- and Cost-saving Opportunities for CT and MRI Operation. Radiology 295:593–605. https://doi.org/10.1148/radiol.2020192084
doi: 10.1148/radiol.2020192084 pubmed: 32208096

Auteurs

Philipp Gruschwitz (P)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany. Gruschwitz_P@ukw.de.

Viktor Hartung (V)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Süleyman Ergün (S)

Institute of Anatomy and Cell Biology, University of Würzburg, Würzburg, Germany.

Dominik Peter (D)

Department of General, Visceral, Transplant, Vascular, and Pediatric Surgery, University Hospital of Würzburg, Würzburg, Germany.

Sven Lichthardt (S)

Department of General, Visceral, Transplant, Vascular, and Pediatric Surgery, University Hospital of Würzburg, Würzburg, Germany.

Henner Huflage (H)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Robin Hendel (R)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Pauline Pannenbecker (P)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Anne Marie Augustin (AM)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Andreas Steven Kunz (AS)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Philipp Feldle (P)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Thorsten Alexander Bley (TA)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Jan-Peter Grunz (JP)

Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.

Classifications MeSH