@Radiology_AI

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. To investigate if a deep learning convolutional neural network (CNN) could enable low-dose 18F fluorodeoxyglucose (18F-FDG) PET/MRI imaging for correct treatment response assessment of pediatric patients and young adults with lymphoma. In this secondary analysis of prospectively collected data (NCT01542879), 20 patients (mean age, 16.4 6.4 years) with lymphoma underwent 18F-FDG PET/MRI scans between July 2015 and August 2019 at baseline and after induction chemotherapy.