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[Injuries of the cervical spine : Challenges in diagnostics and treatment].

Unfallchirurgie (Heidelb)

February 2025

Klinik für Unfallchirurgie und Orthopädie, Universitätsklinikum Hamburg Eppendorf, Martinistr. 52, 20246, Hamburg, Deutschland.

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Association of Obesity and Skeletal Muscle with Postoperative Survival in Non-Small Cell Lung Cancer.

Radiology

January 2025

From the Department of Radiology (J.H.L.) and Department of Thoracic and Cardiovascular Surgery (J.L., Y.J.J., S.Y.P., J.H.C., Y.S.C., J.K., Y.M.S., H.K.K.), Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea; Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, 115 Irwon-ro, Gangnam-gu, Seoul 06355, Korea (D.K., J.L., S.Y.P., S.K., J.C.); Center for Clinical Epidemiology, Sungkyunkwan University, Samsung Medical Center, Seoul, Korea (D.K., J.C.); Patient-Centered Outcomes Research Institute, Samsung Medical Center, Seoul, Korea (J.L., Y.M.S., S.K., H.K.K., J.C.); and Department of Epidemiology and Medicine, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (J.C.).

Background A comprehensive assessment of skeletal muscle health is crucial to understanding the association between improved clinical outcomes and obesity as defined by body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) in lung cancer, but limited studies have been conducted on this topic. Purpose To investigate the association between BMI-defined obesity and survival in patients with non-small cell lung cancer who underwent curative resection, with a specific focus on the status of skeletal muscle assessed at CT. Materials and Methods This retrospective study investigated Korean patients with non-small cell lung cancer who underwent curative resection between January 2008 and December 2019.

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Deep Learning Superresolution for Simultaneous Multislice Parallel Imaging-Accelerated Knee MRI Using Arthroscopy Validation.

Radiology

January 2025

From the Department of Radiology, Division of Musculoskeletal Radiology, NYU Grossman School of Medicine, 660 1st Ave, 3rd Fl, Rm 313, New York, NY 10016 (S.S.W., J.V., R.K., E.H.P., J.F.); Department for Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, University Hospital Tübingen, Tübingen, Germany (S.S.W.); Department of Radiology, University Hospital Basel, Basel, Switzerland (J.V.); Department of Radiology, Hospital do Coraçao, São Paulo, Brazil (T.C.R.); Academic Surgical Unit, South West London Elective Orthopaedic Centre (SWLEOC), London, United Kingdom (D.D.); Department of Radiology, Balgrist University Hospital, Zurich, Switzerland (B.F.); Department of Radiology, Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Research Institute of Clinical Medicine of Jeonbuk National University, Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea (E.H.P.); Medscanlagos Radiology, Cabo Frio, Brazil (A.S.); Centre for Data Analytics, Bond University, Gold Coast, Australia (S.E.S.); Siemens Healthineers AG, Erlangen, Germany (I.B.); and Siemens Medical Solutions USA, Malvern, Pa (G.K.).

Background Deep learning (DL) methods can improve accelerated MRI but require validation against an independent reference standard to ensure robustness and accuracy. Purpose To validate the diagnostic performance of twofold-simultaneous-multislice (SMSx2) twofold-parallel-imaging (PIx2)-accelerated DL superresolution MRI in the knee against conventional SMSx2-PIx2-accelerated MRI using arthroscopy as the reference standard. Materials and Methods Adults with painful knee conditions were prospectively enrolled from December 2021 to October 2022.

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