Generative restoration for cardiac PET attenuation correction: a two-stage 3D DDIM framework optimizing fidelity and clinical controllability
This study aims to develop a two-stage 3D denoising diffusion implicit model (DDIM) framework for CT-free attenuation correction in cardiac PET imaging, enabling direct generation of attenuation-corrected (AC) images from non-attenuation-corrected (NAC) PET scans. The method is comprehensively validated using both [18F]FDG PET and [13N]ammonia cardiac PET datasets to demonstrate its clinical applicability across different perfusion and metabolic imaging protocols. The framework employs a two-stage approach: (1) a noise-to-image DDIM was first pretrained on all available AC images (i.e., no need of paired NACs) to learn a diverse AC distributions, enabling the high-fidelity generation of AC images with varying appearances; (2) the pretrained model was fine-tuned with a limited set of paired NAC-AC images to form a conditional DDIM, ensuring anatomically aligned, controllable generation. The model architecture uses a 3D U-Net, trained on 224 paired NAC-AC and 396 unpaired AC images for [18F]FDG, and 608 paired NAC-AC images and 885 unpaired AC images for [13N]ammonia. Performance was evaluated through quantitative metrics (including NMAE, NRMSE, SSIM and PSNR) and visual assessment. The proposed two-stage DDIM framework achieved excellent agreement with clinical CT-based attenuation correction (CT-AC), demonstrating superior correlation (slope = 0.78, $$\:{R}^{2}$$ = 0.95 for [18F]FDG; slope = 0.99, $$\:{R}^{2}$$= 0.91 for [13N]ammonia) and lower errors compared to existing approaches. Ablation studies confirmed the benefits of both the two-stage training strategy and the incorporation of unpaired AC images, as evidenced by narrower confidence intervals in Bland-Altman analysis and reduced percentage errors. The two-stage 3D DDIM framework achieves performance comparable to clinical CT-AC while effectively leveraging unpaired data, demonstrating significant potential for robust cardiac PET attenuation correction.
Authors
- Xiaotong Hong (ORCID: https://orcid.org/0000-0002-6079-8638)
- Weiping Xu
- Chunfeng Lian
- Hao Sun
- Junhang Deng
- Jianhua Ma
- Lijun Lu
- Fan Wang
- Haifeng Wang
Institutions
- Huzhou Normal University (CN)
- Huzhou Vocational and Technical College (CN)
- Shanghai Liangyou (China) (CN)
- Guangdong Academy of Medical Sciences (CN)
- Guangdong Provincial People's Hospital (CN)
- Southern Medical University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- EJNMMI Physics
- Published
- 2026-02-02
- DOI
- https://doi.org/10.1186/s40658-026-00839-7
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00