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Using 18F-FDG PET/CT-derived body composition features to predict lymphovascular invasion in non-small cell lung cancer.

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Title: Using 18F-FDG PET/CT-derived body composition features to predict lymphovascular invasion in non-small cell lung cancer.
Authors: Jiang, Zewen1,2 (AUTHOR), Haberl, David1,2 (AUTHOR), Spielvogel, Clemens1 (AUTHOR), Szakall, Szabolcs3 (AUTHOR), Molnar, Peter3 (AUTHOR), Yu, Josef1 (AUTHOR), Lungu, Victor4 (AUTHOR), Fillinger, Janos4 (AUTHOR), Renyi-Vamos, Ferenc4,5,6 (AUTHOR), Aigner, Clemens7 (AUTHOR), Dome, Balazs4,5,7,8 (AUTHOR), Lang, Christian7,9 (AUTHOR), Kenner, Lukas2,10,11,12,13 (AUTHOR), Megyesfalvi, Zsolt4,5,7 (AUTHOR), Hacker, Marcus1,13 (AUTHOR) marcus.hacker@meduniwien.ac.at
Source: European Journal of Nuclear Medicine & Molecular Imaging. Jan2026, Vol. 53 Issue 2, p774-785. 12p.
Database: Academic Search Ultimate
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An: 191135944
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  Data: Using <superscript>18</superscript>F-FDG PET/CT-derived body composition features to predict lymphovascular invasion in non-small cell lung cancer.
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Nuclear+Medicine+%26+Molecular+Imaging%22">European Journal of Nuclear Medicine & Molecular Imaging</searchLink>. Jan2026, Vol. 53 Issue 2, p774-785. 12p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=191135944
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        Value: 10.1007/s00259-025-07435-4
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      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 774
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      – TitleFull: Using 18F-FDG PET/CT-derived body composition features to predict lymphovascular invasion in non-small cell lung cancer.
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              Text: Jan2026
              Type: published
              Y: 2026
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