%0 Journal Article
%A Haase, Robert
%A Pinetz, Thomas
%A Kobler, Erich
%A Bendella, Zeynep
%A Zülow, Stefan
%A Schievelkamp, Arndt-Hendrik
%A Schmeel, Frederic Carsten
%A Panahabadi, Sarah
%A Stylianou, Anna Magdalena
%A Paech, Daniel
%A Foltyn-Dumitru, Martha
%A Wagner, Verena
%A Schlamp, Kai
%A Heussel, Gudula
%A Holtkamp, Mathias
%A Heussel, Claus Peter
%A Vahlensieck, Martin
%A Luetkens, Julian A
%A Schlemmer, Heinz-Peter
%A Haubold, Johannes
%A Radbruch, Alexander
%A Effland, Alexander
%A Deuschl, Cornelius
%A Deike-Hofmann, Katerina
%T Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.
%J Investigative radiology
%V 60
%N 8
%@ 0020-9996
%C Philadelphia, Pa.
%I Lippincott Williams & Wilkins
%M DZNE-2025-00778
%P 543 - 551
%D 2025
%X Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this study was to test the benefit of a deep learning-based contrast signal amplification in true single-dose T1-weighted (T-SD) images creating artificial double-dose (A-DD) images for metastasis detection in brain magnetic resonance imaging.In this prospective, multicenter study, a deep learning-based method originally trained on noncontrast, low-dose, and T-SD brain images was applied to T-SD images of 30 participants (mean age ± SD, 58.5 ± 11.8 years; 23 women) acquired externally between November 2022 and June 2023. Four readers with different levels of experience independently reviewed T-SD and A-DD images for metastases with 4 weeks between readings. A reference reader reviewed additionally acquired true double-dose images to determine any metastases present. Performances were compared using Mid-p McNemar tests for sensitivity and Wilcoxon signed rank tests for false-positive findings.All readers found more metastases using A-DD images. The 2 experienced neuroradiologists achieved the same level of sensitivity using T-SD images (62 of 91 metastases, 68.1
%K Humans
%K Deep Learning
%K Brain Neoplasms: diagnostic imaging
%K Brain Neoplasms: secondary
%K Female
%K Middle Aged
%K Male
%K Magnetic Resonance Imaging: methods
%K Prospective Studies
%K Contrast Media: administration & dosage
%K Sensitivity and Specificity
%K Aged
%K Image Interpretation, Computer-Assisted: methods
%K Image Enhancement: methods
%K artificial double-dose (Other)
%K brain metastasis (Other)
%K contrast maximization (Other)
%K convolutional neural network (Other)
%K deep learning (Other)
%K gadolinium-based contrast agent (Other)
%K magnetic resonance imaging (Other)
%K metastasis detection (Other)
%K virtual contrast (Other)
%K Contrast Media (NLM Chemicals)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:39961132
%R 10.1097/RLI.0000000000001166
%U https://pub.dzne.de/record/279447