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. 2021 Oct 6;3(6):e200232. doi: 10.1148/ryai.2021200232

Figure 1:

Low-dose and deep learning–enhanced PET images in a 14-year-old boy with Hodgkin lymphoma. (A) Full-dose fluorine 18 (18F) fluorodeoxyglucose (FDG) PET image (3 MBq/kg) shows hypermetabolic mediastinal and left infra- and supraclavicular lymph nodes (arrows). (B–F) Simulated 75% (75% Sim) (B), 50% (50% Sim) (C), 25% (25% Sim) (D), 12.5% (25% Sim) (E), and 6.25% (6.25% Sim) (F) dose 18F-FDG PET images and (G) corresponding MRI scan obtained with liver acquisition with volume acceleration sequence show increased noise and reduced contrast between tumor (arrows) and liver (arrowheads in G) with simulated reduced radiotracer dose. (H–L) Convolutional neural network (CNN)–augmented low-dose 18F-FDG PET images at 75% (H), 50% (I), 25% (J), 12.5% (K), and 6.25% (L) dose show reduced noise and improved contrast between tumor and liver compared with non-CNN–augmented PET images.

Low-dose and deep learning–enhanced PET images in a 14-year-old boy with Hodgkin lymphoma. (A) Full-dose fluorine 18 (18F) fluorodeoxyglucose (FDG) PET image (3 MBq/kg) shows hypermetabolic mediastinal and left infra- and supraclavicular lymph nodes (arrows). (B–F) Simulated 75% (75% Sim) (B), 50% (50% Sim) (C), 25% (25% Sim) (D), 12.5% (25% Sim) (E), and 6.25% (6.25% Sim) (F) dose 18F-FDG PET images and (G) corresponding MRI scan obtained with liver acquisition with volume acceleration sequence show increased noise and reduced contrast between tumor (arrows) and liver (arrowheads in G) with simulated reduced radiotracer dose. (H–L) Convolutional neural network (CNN)–augmented low-dose 18F-FDG PET images at 75% (H), 50% (I), 25% (J), 12.5% (K), and 6.25% (L) dose show reduced noise and improved contrast between tumor and liver compared with non-CNN–augmented PET images.