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Objective: Describe the radiograph-based screening program and frequencies of ineligibility in 3 large, international, randomized, double-blind, phase 3 studies of subcutaneous tanezumab in patients with osteoarthritis (OA).
Design: Standardized bilateral shoulder, hip, and knee screening radiographs were obtained by trained imaging technologists and centrally read by 1 of 5 musculoskeletal radiology experts trained using a program-specific imaging atlas. Inter-reader consistency was tracked with test cases blindly inserted into the reader queue. Readers attended quarterly calibration meetings. Protocol-specified radiographic exclusion criteria included rapidly progressive OA (RPOA) or risk factors for RPOA (including severe malalignment of the knee, subchondral insufficiency fracture, atrophic OA, and osteonecrosis). Patients reporting disproportionate pain to radiographic evidence of OA in the hip or knee (without other pathology) were ineligible under a nonradiographic exclusion criterion.
Results: At >480 international sites, 23,079 patients entered screening and 13,797 were radiographically assessed. Across 6 sets of quarterly testing, pairwise central reader agreement on radiographic eligibility was 72-87% (kappa: 0.41-0.71) and on radiographic OA grading 77-84% (kappa: 0.68-0.75). Among the 5,773/13,797 (41.8%) patients who met exclusionary criteria, 27% had disproportionate pain to radiographic findings (~10% of knee/hip radiographs). RPOA or risk factors for RPOA were each identified in <5% of patients (usually 1 joint) and <3% of knee/hip/shoulders.
Conclusions: The phase 3 tanezumab screening program demonstrated the utility of radiographs to screen patients entering NGF inhibitor trials. A high degree of reader concordance was achieved. RPOA and risk factors for RPOA were not commonly observed. NCT02697773, NCT02709486, NCT02528188.
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http://dx.doi.org/10.1016/j.ostima.2022.100082 | DOI Listing |
Eur Radiol Exp
September 2025
Department of Radio-diagnosis, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt.
Background: Bone marrow (BM) lesion differentiation remains challenging, and quantitative magnetic resonance imaging (MRI) may enhance accuracy over conventional methods. We evaluated the diagnostic value and inter-reader reliability of Dixon-based signal drop (%drop) and fat fraction percentage (%fat) as adjuncts to existing protocols.
Materials And Methods: In this prospective two-center study, 172 patients with BM signal abnormalities underwent standardized 1.
Eur 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 PDFEur Radiol
August 2025
Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Objectives: To assess the impact of reconstruction parameters on AI's performance in detecting and classifying risk-dominant nodules in a baseline low-dose CT (LDCT) screening among a Chinese general population.
Materials And Methods: Baseline LDCT scans from 300 consecutive participants in the Netherlands and China Big-3 (NELCIN-B3) trial were included. AI analyzed each scan reconstructed with four settings: 1 mm/0.
Biomedicines
August 2025
IRCCS San Raffaele Roma, Via della Pisana 235, 00163 Rome, Italy.
: Despite its central role in pediatric pre-surgical evaluation of drug-resistant focal epilepsy, conventional analog F-fluorodeoxyglucose (F-FDG) PET/CT (aPET) systems often yield modest epileptogenic zone (EZ) detection rates (~50-60%). Silicon photomultiplier-based digital PET/CT (dPET) promises enhanced image quality, but its performance in pediatric epilepsy remains untested. : We retrospectively analyzed 22 children (mean age 11.
View Article and Find Full Text PDFBJU Int
August 2025
Department of Urology, Stanford School of Medicine, Palo Alto, CA, USA.
Objectives: To improve sensitivity and inter-reader consistency of prostate cancer localisation on micro-ultrasonography (MUS) by developing a deep learning model for automatic cancer segmentation, and to compare model performance with that of expert urologists.
Patients And Methods: We performed an institutional review board-approved prospective collection of MUS images from patients undergoing magnetic resonance imaging (MRI)-ultrasonography fusion guided biopsy at a single institution. Patients underwent 14-core systematic biopsy and additional targeted sampling of suspicious MRI lesions.