A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information

PURPOSE: Partial volume effect (PVE) is a consequence of the limited spatial resolution of PET scanners. PVE can cause the intensity values of a particular voxel to be underestimated or overestimated due to the effect of surrounding tracer uptake. We propose a novel partial volume correction (PVC) technique to overcome the adverse effects of PVE on PET images. METHODS: Two hundred and twelve clinical brain PET scans, including 50 (18)F-Fluorodeoxyglucose ((18)F-FDG), 50 (18)F-Flortaucipir, 36 (18)F-Flutemetamol, and 76 (18)F-FluoroDOPA, and their corresponding T1-weighted MR images were enrolled in this study. The Iterative Yang technique was used for PVC as a reference or surrogate of the ground truth for evaluation. A cycle-consistent adversarial network (CycleGAN) was trained to directly map non-PVC PET images to PVC PET images. Quantitative analysis using various metrics, including structural similarity index (SSIM), root mean squared error (RMSE), and peak signal-to-noise ratio (PSNR), was performed. Furthermore, voxel-wise and region-wise-based correlations of activity concentration between the predicted and reference images were evaluated through joint histogram and Bland and Altman analysis. In addition, radiomic analysis was performed by calculating 20 radiomic features within 83 brain regions. Finally, a voxel-wise two-sample t-test was used to compare the predicted PVC PET images with reference PVC images for each radiotracer. RESULTS: The Bland and Altman analysis showed the largest and smallest variance for (18)F-FDG (95% CI: − 0.29, + 0.33 SUV, mean = 0.02 SUV) and (18)F-Flutemetamol (95% CI: − 0.26, + 0.24 SUV, mean = − 0.01 SUV), respectively. The PSNR was lowest (29.64 ± 1.13 dB) for (18)F-FDG and highest (36.01 ± 3.26 dB) for (18)F-Flutemetamol. The smallest and largest SSIM were achieved for (18)F-FDG (0.93 ± 0.01) and (18)F-Flutemetamol (0.97 ± 0.01), respectively. The average relative error for the kurtosis radiomic feature was 3.32%, 9.39%, 4.17%, and 4.55%, while it was 4.74%, 8.80%, 7.27%, and 6.81% for NGLDM_contrast feature for (18)F-Flutemetamol, (18)F-FluoroDOPA, (18)F-FDG, and (18)F-Flortaucipir, respectively. CONCLUSION: An end-to-end CycleGAN PVC method was developed and evaluated. Our model generates PVC images from the original non-PVC PET images without requiring additional anatomical information, such as MRI or CT. Our model eliminates the need for accurate registration or segmentation or PET scanner system response characterization. In addition, no assumptions regarding anatomical structure size, homogeneity, boundary, or background level are required. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00259-023-06152-0.