LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging

Abstract Background Photon-counting detector CT (PCD-CT) offers technical advantages over energy-integrating detector CT (EID-CT) for liver imaging. However, it is unclear whether these translate into clinical improvements regarding the classification of suspicious liver lesions using the Liver Imag...

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Main Authors: Lukas Müller, Tobias Jorg, Fabian Stoehr, Jan-Peter Grunz, Dirk Graafen, Moritz C. Halfmann, Henner Huflage, Friedrich Foerster, Jens Mittler, Daniel Pinto dos Santos, Tobias Bäuerle, Roman Kloeckner, Tilman Emrich
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Language:English
Published: BMC 2025-08-01
Series:Cancer Imaging
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Online Access:https://doi.org/10.1186/s40644-025-00922-9
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author Lukas Müller
Tobias Jorg
Fabian Stoehr
Jan-Peter Grunz
Dirk Graafen
Moritz C. Halfmann
Henner Huflage
Friedrich Foerster
Jens Mittler
Daniel Pinto dos Santos
Tobias Bäuerle
Roman Kloeckner
Tilman Emrich
author_facet Lukas Müller
Tobias Jorg
Fabian Stoehr
Jan-Peter Grunz
Dirk Graafen
Moritz C. Halfmann
Henner Huflage
Friedrich Foerster
Jens Mittler
Daniel Pinto dos Santos
Tobias Bäuerle
Roman Kloeckner
Tilman Emrich
author_sort Lukas Müller
collection DOAJ
description Abstract Background Photon-counting detector CT (PCD-CT) offers technical advantages over energy-integrating detector CT (EID-CT) for liver imaging. However, it is unclear whether these translate into clinical improvements regarding the classification of suspicious liver lesions using the Liver Imaging Reporting and Data System (LI-RADS). This study compared the intra- and intermodal agreement of EID-CT and PCD-CT with Magnetic resonance imaging (MRI) for liver lesion classification. Methods This retrospective study included patients who underwent EID-CT or PCD-CT and MRI within 30 days between 02/2023 and 01/2024. Three board-certified radiologists assessed LI-RADS classification and presence of LI-RADS major features. Fleiss’ Kappa and intraclass correlation coefficients (ICC) were used to evaluate rater agreement. Results Sixty-eight lesions in 26 patients (mean age 65.0 ± 14.2 years, 19 [73.1%] male) were analyzed. Intramodal inter-rater agreement for LI-RADS classification was 0.88 (0.62–0.88) for EID-CT, 0.90 (0.83–0.94) for PCD-CT, and 0.87 (0.81–0.91) for MRI. Agreement in PCD-CT was substantial for all LI-RADS major features, whereas in EID-CT only for washout. Intermodal agreement between CT and MRI ranged from 0.67 to 0.72. Final intermodal LI-RADS classification agreement was higher for PCD-CT (0.72–0.85) than EID-CT (0.52–0.64). Conclusions PCD-CT demonstrated higher intermodal and intramodal agreement for LI-RADS classification and major features than EID-CT. Additionally, PCD-CT shows significantly higher intramodal and inter-rater agreement for LI-RADS classification and greater concordance with MRI compared to EID-CT, reaching substantial to almost perfect agreement. These results suggest a potential benefit of PCD-CT in the management and treatment decision-making of HCC.
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spelling doaj-art-3eef83c9834148d7b639035167ea11322025-08-20T03:46:13ZengBMCCancer Imaging1470-73302025-08-0125111210.1186/s40644-025-00922-9LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imagingLukas Müller0Tobias Jorg1Fabian Stoehr2Jan-Peter Grunz3Dirk Graafen4Moritz C. Halfmann5Henner Huflage6Friedrich Foerster7Jens Mittler8Daniel Pinto dos Santos9Tobias Bäuerle10Roman Kloeckner11Tilman Emrich12Department of Diagnostic and Interventional Radiology, University Medical Center MainzDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzDepartment of Radiology, University of WisconsinDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzDepartment of Diagnostic and Interventional Radiology, University Hospital WürzburgDepartment of Internal Medicine I, University Medical Center MainzDepartment of General, Visceral and Transplant Surgery, University Medical Center MainzDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzInstitute of Interventional Radiology, University Hospital of Schleswig-Holstein - Campus LübeckDepartment of Diagnostic and Interventional Radiology, University Medical Center MainzAbstract Background Photon-counting detector CT (PCD-CT) offers technical advantages over energy-integrating detector CT (EID-CT) for liver imaging. However, it is unclear whether these translate into clinical improvements regarding the classification of suspicious liver lesions using the Liver Imaging Reporting and Data System (LI-RADS). This study compared the intra- and intermodal agreement of EID-CT and PCD-CT with Magnetic resonance imaging (MRI) for liver lesion classification. Methods This retrospective study included patients who underwent EID-CT or PCD-CT and MRI within 30 days between 02/2023 and 01/2024. Three board-certified radiologists assessed LI-RADS classification and presence of LI-RADS major features. Fleiss’ Kappa and intraclass correlation coefficients (ICC) were used to evaluate rater agreement. Results Sixty-eight lesions in 26 patients (mean age 65.0 ± 14.2 years, 19 [73.1%] male) were analyzed. Intramodal inter-rater agreement for LI-RADS classification was 0.88 (0.62–0.88) for EID-CT, 0.90 (0.83–0.94) for PCD-CT, and 0.87 (0.81–0.91) for MRI. Agreement in PCD-CT was substantial for all LI-RADS major features, whereas in EID-CT only for washout. Intermodal agreement between CT and MRI ranged from 0.67 to 0.72. Final intermodal LI-RADS classification agreement was higher for PCD-CT (0.72–0.85) than EID-CT (0.52–0.64). Conclusions PCD-CT demonstrated higher intermodal and intramodal agreement for LI-RADS classification and major features than EID-CT. Additionally, PCD-CT shows significantly higher intramodal and inter-rater agreement for LI-RADS classification and greater concordance with MRI compared to EID-CT, reaching substantial to almost perfect agreement. These results suggest a potential benefit of PCD-CT in the management and treatment decision-making of HCC.https://doi.org/10.1186/s40644-025-00922-9Hepatocellular CarcinomaLiver Imaging Reporting & Data SystemPhoton-Counting Computed TomographyMagnetic Resonance ImagingAccuracy
spellingShingle Lukas Müller
Tobias Jorg
Fabian Stoehr
Jan-Peter Grunz
Dirk Graafen
Moritz C. Halfmann
Henner Huflage
Friedrich Foerster
Jens Mittler
Daniel Pinto dos Santos
Tobias Bäuerle
Roman Kloeckner
Tilman Emrich
LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging
Cancer Imaging
Hepatocellular Carcinoma
Liver Imaging Reporting & Data System
Photon-Counting Computed Tomography
Magnetic Resonance Imaging
Accuracy
title LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging
title_full LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging
title_fullStr LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging
title_full_unstemmed LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging
title_short LI-RADS: concordance between energy-integrating computed tomography, photon-counting detector computed tomography and magnetic resonance imaging
title_sort li rads concordance between energy integrating computed tomography photon counting detector computed tomography and magnetic resonance imaging
topic Hepatocellular Carcinoma
Liver Imaging Reporting & Data System
Photon-Counting Computed Tomography
Magnetic Resonance Imaging
Accuracy
url https://doi.org/10.1186/s40644-025-00922-9
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