Investigating the Small Pixel Effect in Ultra-High Resolution Photon-Counting CT of the Lung.


Journal

Investigative radiology
ISSN: 1536-0210
Titre abrégé: Invest Radiol
Pays: United States
ID NLM: 0045377

Informations de publication

Date de publication:
09 Aug 2023
Historique:
medline: 8 8 2023
pubmed: 8 8 2023
entrez: 8 8 2023
Statut: aheadofprint

Résumé

The aim of this study was to investigate potential benefits of ultra-high resolution (UHR) over standard resolution scan mode in ultra-low dose photon-counting detector CT (PCD-CT) of the lung. Six cadaveric specimens were examined with 5 dose settings using tin prefiltration, each in UHR (120 × 0.2 mm) and standard mode (144 × 0.4 mm), on a first-generation PCD-CT scanner. Image quality was evaluated quantitatively by noise comparisons in the trachea and both main bronchi. In addition, 16 readers (14 radiologists and 2 internal medicine physicians) independently completed a browser-based pairwise forced-choice comparison task for assessment of subjective image quality. The Kendall rank coefficient (W) was calculated to assess interrater agreement, and Pearson's correlation coefficient (r) was used to analyze the relationship between noise measurements and image quality rankings. Across all dose levels, image noise in UHR mode was lower than in standard mode for scan protocols matched by CTDIvol (P < 0.001). UHR examinations exhibited noise levels comparable to the next higher dose setting in standard mode (P ≥ 0.275). Subjective ranking of protocols based on 5760 pairwise tests showed high interrater agreement (W = 0.99; P ≤ 0.001) with UHR images being preferred by readers in the majority of comparisons. Irrespective of scan mode, a substantial indirect correlation was observed between image noise and subjective image quality ranking (r = -0.97; P ≤ 0.001). In PCD-CT of the lung, UHR scan mode reduces image noise considerably over standard resolution acquisition. Originating from the smaller detector element size in fan direction, the small pixel effect allows for superior image quality in ultra-low dose examinations with considerable potential for radiation dose reduction.

Identifiants

pubmed: 37552040
doi: 10.1097/RLI.0000000000001013
pii: 00004424-990000000-00143
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of interest and sources of funding: J.-P.G. (Z-3BC/02) and P.G. (Z-02CSP/18) were financially supported by the Interdisciplinary Center of Clinical Research Würzburg. The radiology department in Würzburg receives ongoing research funding from Siemens Healthcare GmbH.

Références

Dunning CAS, Marsh JF Jr., Winfree T, et al. Accuracy of nodule volume and airway wall thickness measurement using low-dose chest CT on a photon-counting detector CT scanner. Invest Radiol. 2023;58:283–292.
Bartlett DJ, Koo CW, Bartholmai BJ, et al. High-resolution chest computed tomography imaging of the lungs: impact of 1024 matrix reconstruction and photon-counting detector computed tomography. Invest Radiol. 2019;54:129–137.
Lee C. Managing radiation dose from chest CT in patients with COVID-19. Radiology. 2021;298:E158–E159.
Vonder M, Dorrius MD, Vliegenthart R. Latest CT technologies in lung cancer screening: protocols and radiation dose reduction. Transl Lung Cancer Res. 2021;10:1154–1164.
Jungblut L, Euler A, von Spiczak J, et al. Potential of photon-counting detector CT for radiation dose reduction for the assessment of interstitial lung disease in patients with systemic sclerosis. Invest Radiol. 2022;57:773–779.
De Smet K, De Smet D, Ryckaert T, et al. Diagnostic performance of chest CT for SARS-CoV-2 infection in individuals with or without COVID-19 symptoms. Radiology. 2021;298:E30–E37.
Grunz J-P, Heidenreich JF, Lennartz S, et al. Spectral shaping via tin prefiltration in ultra-high-resolution photon-counting and energy-integrating detector CT of the temporal bone. Invest Radiol. 2022;57:819–825.
Willemink MJ, Persson M, Pourmorteza A, et al. Photon-counting CT: technical principles and clinical prospects. Radiology. 2018;289:293–312.
Flohr T, Ulzheimer S, Petersilka M, et al. Basic principles and clinical potential of photon-counting detector CT. Chinese J Acad Radiol. 2020;3:19–34.
Rajendran K, Petersilka M, Henning A, et al. Full field-of-view, high-resolution, photon-counting detector CT: technical assessment and initial patient experience. Phys Med Biol. 2021;66. doi:10.1088/1361-6560/ac155e.
doi: 10.1088/1361-6560/ac155e
Willemink MJ, Noël PB. The evolution of image reconstruction for CT—from filtered back projection to artificial intelligence. Eur Radiol. 2019;29:2185–2195.
Rajendran K, Petersilka M, Henning A, et al. First clinical photon-counting detector CT system: technical evaluation. Radiology. 2022;303:130–138.
Pourmorteza A, Symons R, Henning A, et al. Dose efficiency of quarter-millimeter photon-counting computed tomography: first-in-human results. Invest Radiol. 2018;53:365–372.
Klein L, Dorn S, Amato C, et al. Effects of detector sampling on noise reduction in clinical photon-counting whole-body computed tomography. Invest Radiol. 2020;55:111–119.
Sartoretti T, Racine D, Mergen V, et al. Quantum iterative reconstruction for low-dose ultra-high-resolution photon-counting detector CT of the lung. Diagnostics (Basel). 2022;12:522.
Inoue A, Johnson TF, White D, et al. Estimating the clinical impact of photon-counting-detector CT in diagnosing usual interstitial pneumonia. Invest Radiol. 2022;57:734–741.
Remy-Jardin M, Hutt A, Flohr T, et al. Ultra-high-resolution photon-counting CT imaging of the chest: a new era for morphology and function. Invest Radiol. 2023;58:482–487.
Sartoretti T, Wildberger JE, Flohr T, et al. Photon-counting detector CT: early clinical experience review. Br J Radiol. 2023;96:20220544.
The ICRP commission. The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103. 2007:1–332. Available at: http://dx.doi.org/10.1016/j.icrp.2007.10.003.
Good WF, Gur D, Feist JH, et al. Subjective and objective assessment of image quality—a comparison. J Digit Imaging. 1994;7:77–78.
Phelps AS, Naeger DM, Courtier JL, et al. Pairwise comparison versus Likert scale for biomedical image assessment. AJR Am J Roentgenol. 2015;204:8–14.
Gur D, Rubin DA, Kart BH, et al. Forced choice and ordinal discrete rating assessment of image quality: a comparison. J Digit Imaging. 1997;10:103–107.
Leng S, Rajendran K, Gong H, et al. 150-μm spatial resolution using photon-counting detector computed tomography technology: technical performance and first patient images. Invest Radiol. 2018;53:655–662.
Leng S, Yu Z, Halaweish A, et al. Dose-efficient ultrahigh-resolution scan mode using a photon counting detector computed tomography system. J Med Imaging. 2016;3:043504.
Sartoretti T, Landsmann A, Nakhostin D, et al. Quantum iterative reconstruction for abdominal photon-counting detector CT improves image quality. Radiology. 2022;303:339–348.
Kazerooni EA, Austin JHM, Black WC, et al. ACR-STR practice parameter for the performance and reporting of lung cancer screening thoracic computed tomography (CT): 2014 (resolution 4). J Thorac Imaging. 2014;29:310–316.
Demb J, Chu P, Yu S, et al. Analysis of computed tomography radiation doses used for lung cancer screening scans. JAMA Intern Med. 2019;179:1650–1657.
Gierada DS, Black WC, Chiles C, et al. Low-dose CT screening for lung cancer: evidence from 2 decades of study. Radiol Imaging Cancer. 2020;2:e190058.
Lell M, Kachelrieß M. Computed Tomography 2.0: new detector technology, AI, and other developments. Invest. Radiol. 2023. Available at: http://dx.doi.org/10.1097/RLI.0000000000000995.
doi: 10.1097/RLI.0000000000000995

Auteurs

Henner Huflage (H)

From the Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany (H.H., R.H., A.S., V.H., P.G., T.A., J.-P.G.); Institute of Anatomy and Cell Biology, University of Würzburg, Würzburg, Germany (S.E.); Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Tübingen, Germany (S.A.); and Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany (N.P.).

Classifications MeSH