Inferring FDG-PET-positivity of lymph node metastases in proven lung cancer from contrast-enhanced CT using radiomics and machine learning

Inferring FDG-PET-positivity of lymph node metastases in proven lung cancer from contrast-enhanced CT using radiomics and machine learning

Abstract Background We evaluated the role of radiomics applied to contrast-enhanced computed tomography (CT) in the detection of lymph node (LN) metastases in patients with known lung cancer compared to 18F-fluorodeoxyglucose positron emission tomography (PET)/CT as a reference. Methods This retrosp...

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Bibliographic Details
Main Authors: Boris Gorodetski, Philipp Hendrik Becker, Alexander Daniel Jacques Baur, Alexander Hartenstein, Julian Manuel Michael Rogasch, Christian Furth, Holger Amthauer, Bernd Hamm, Marcus Makowski, Tobias Penzkofer
Format: Article
Language:English
Published: SpringerOpen 2022-09-01
Series:European Radiology Experimental
Subjects:
Machine learning
Lymph nodes
Lymphatic metastasis
Lung neoplasms
Tomography (x-ray computed)
Online Access:https://doi.org/10.1186/s41747-022-00296-8

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