Abstract
PURPOSE: Delayed images may not be acquired due to severe pain, drowsiness, or worsening vital signs while waiting after blood pool imaging in three-phase bone scintigraphy. If the hyperemia in the blood pool image contains information from which increased uptake on the delayed images can be inferred, the generative adversarial network (GAN) can generate the increased uptake from the hyperemia. We attempted to apply pix2pix, a type of conditional GAN, to transform hyperemia into increased bone uptake. METHODS: We enrolled 1464 patients who underwent three-phase bone scintigraphy for inflammatory arthritis, osteomyelitis, complex regional pain syndrome (CRPS), cellulitis, and recent bone injury. Blood pool images were acquired 10 min after intravenous injection of Tc-99 m hydroxymethylene diphosphonate, and delayed bone images were obtained after 3 h. The model was based on the open-source code of the pix2pix model with perceptual loss. Increased uptake in the delayed images generated by the model was evaluated using lesion-based analysis by a nuclear radiologist in areas consistent with hyperemia in the blood pool images. RESULTS: The model showed sensitivities of 77.8% and 87.5% for inflammatory arthritis and CRPS, respectively. In osteomyelitis and cellulitis, their sensitivities of about 44% were observed. However, in cases of recent bone injury, the sensitivity was only 6.3% in areas consistent with focal hyperemia. CONCLUSION: The model based on pix2pix generated increased uptake in delayed images matching the hyperemia in the blood pool image in inflammatory arthritis and CRPS.