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Background: The accurate evaluation of tumor response after locoregional therapy is crucial for adjusting therapeutic strategy and guiding individualized follow-up.
Purpose: To determine the inter-reader agreement of the LR-TR algorithm for hepatocellular carcinoma treated with locoregional therapy among radiologists with different seniority.
Material And Methods: A total of 275 treated observations on 249 MRI scans from 99 patients were retrospectively collected. Three readers of different seniorities (senior, intermediate, and junior with 10, 6, and 2 years of experience in hepatic imaging, respectively) analyzed the presence or absence of features (arterial-phase hyperenhancement and washout) and evaluated LR-TR category.
Results: There were substantial inter-reader agreements for overall LR-TR categorization (kappa = 0.704), LR-TR viable (kappa = 0.715), and LR-TR non-viable (kappa = 0.737), but fair inter-reader agreement for LR-TR equivocal (kappa = 0.231) among three readers. The inter-reader agreement was substantial for arterial-phase hyperenhancement (kappa = 0.725), but moderate for washout (kappa = 0.443) among three readers. The inter-reader agreements between two readers were substantial for overall LR-TR categorization (kappa = 0.734, 0.727, 0.652), LR-TR viable (kappa = 0.719, 0.752, 0.678), and LR-TR non-viable (kappa = 0.758, 0.760, 0.694), which were at the same level as the inter-reader agreements among three readers. In addition, the inter-reader agreements between two readers were substantial for arterial-phase hyperenhancement (kappa = 0.733, 0.766, 0.678), but moderate for washout (kappa = 0.473, 0.422, 0.446), which were at the same level as the inter-reader agreements among three readers.
Conclusion: LR-TR algorithm demonstrated overall substantial inter-reader agreement among radiologists with different seniority.
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http://dx.doi.org/10.1177/02841851241289130 | DOI Listing |
Comput Methods Programs Biomed
August 2025
The Institute of Cancer Research, London, UK. Electronic address:
Background And Objective: Apparent Diffusion Coefficient (ADC) values and Total Diffusion Volume (TDV) from Whole-body diffusion-weighted MRI (WB-DWI) are recognised cancer imaging biomarkers. However, manual disease delineation for ADC and TDV measurements is unfeasible in clinical practice, demanding automation. As a first step, we propose an algorithm to generate fast and reproducible probability maps of the skeleton, adjacent internal organs (liver, spleen, urinary bladder, and kidneys), and spinal canal.
View Article and Find Full Text PDFEur Radiol Exp
September 2025
Department of Orthopaedics and Trauma Surgery, Orthopaedic Oncology, Musculoskeletal University Center Munich (MUM), University Hospital, LMU Munich, Munich, Germany.
Computed tomography (CT) and magnetic resonance imaging (MRI) are commonly used to assess femoral and tibial torsion. While CT offers high spatial resolution, it involves ionizing radiation. MRI avoids radiation but requires multiple sequences and extended acquisition time.
View Article and Find Full Text PDFSkeletal Radiol
September 2025
Department of Radiology, Federal University of Sao Paulo (UNIFESP), Napoleão de Barros St, 800, São Paulo, SP, 04024-000, Brazil.
Objective: To evaluate multiparametric MRI features of pediatric soft-tissue sarcomas, comparing pre-treatment and post-treatment features, and assessing correlation with clinical outcomes.
Materials And Methods: Retrospective cohort study, including pediatric patients (≤ 18 years) with histologically-confirmed soft-tissue sarcomas who underwent MRI with anatomic and functional sequences in consecutive series. Post-treatment MRI was available for a subset, and features were recorded by two readers.
Introduction: Precise prediction of pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT) in rectal cancer may identify candidates for non-operative management. The optimal selection of diagnostic tools is therefore of major clinical importance.
Methods: Clinical, laboratory, endoscopic and radiological data of patients with rectal cancer treated with nCRT and surgery at an academic medical center from 2010 to 2020 were retrospectively collected.
Eur J Radiol
August 2025
Department of Radiology, Pusan National University School of Medicine and Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Beomeo-ri, Mulgeum-eup, Yangsan-si 626-770 Gyeongsangnam-do, Republic of Korea. Electronic address: kschoo061
Objectives: This study externally tests the performance of an artificial intelligence algorithm (AI) for diagnosing ascending aortic dilatation (AAD) using PA view chest radiography (PA CXR).
Materials And Methods: Two retrospectively collected cohorts with paired CXR/CT within 30 days (Group 1) and 90 days (Group 2) were gathered as external test sets. The performance of AI (DeepCatch X Aorta v1.