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Intelligent ultrafast total-body PET for sedation-free pediatric [18F]FDG imaging

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

This study aims to develop deep learning techniques on total-body PET to bolster the feasibility of sedation-free pediatric PET imaging.

Methods

A deformable 3D U-Net was developed based on 245 adult subjects with standard total-body PET imaging for the quality enhancement of simulated rapid imaging. The developed method was first tested on 16 children receiving total-body [18F]FDG PET scans with standard 300-s acquisition time with sedation. Sixteen rapid scans (acquisition time about 3 s, 6 s, 15 s, 30 s, and 75 s) were retrospectively simulated by selecting the reconstruction time window. In the end, the developed methodology was prospectively tested on five children without sedation to prove the routine feasibility.

Results

The approach significantly improved the subjective image quality and lesion conspicuity in abdominal and pelvic regions of the generated 6-s data. In the first test set, the proposed method enhanced the objective image quality metrics of 6-s data, such as PSNR (from 29.13 to 37.09, p < 0.01) and SSIM (from 0.906 to 0.921, p < 0.01). Furthermore, the errors of mean standardized uptake values (SUVmean) for lesions between 300-s data and 6-s data were reduced from 12.9 to 4.1% (p < 0.01), and the errors of max SUV (SUVmax) were reduced from 17.4 to 6.2% (p < 0.01). In the prospective test, radiologists reached a high degree of consistency on the clinical feasibility of the enhanced PET images.

Conclusion

The proposed method can effectively enhance the image quality of total-body PET scanning with ultrafast acquisition time, leading to meeting clinical diagnostic requirements of lesion detectability and quantification in abdominal and pelvic regions. It has much potential to solve the dilemma of the use of sedation and long acquisition time that influence the health of pediatric patients.

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Data availability

The data could be obtained from the corresponding authors upon request.

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Funding

This work was supported by in part by the National Key Research and Development Program of China (Grant No. 2020YFA0909000 and 2021YFA0910000), the National Natural Science Foundation of China (Grant No. 81571710, 82001878, and 82171972), and the Shanghai Rising-Star Program (Grant No. 20QA1406100).

Author information

Author notes

  1. Xiang Zhou, Yu Fu, Shunjie Dong, and Lianghua Li contributed equally to this paper.

Authors and Affiliations

  1. Department of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Xiang Zhou, Lianghua Li, Ruohua Chen, Gang Huang & Jianjun Liu

  2. College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China

    Yu Fu

  3. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Shunjie Dong

  4. College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Shunjie Dong

  5. Department of Nuclear Medicine, University of Bern, Bern, Switzerland

    Song Xue & Kuangyu Shi

Authors
  1. Xiang Zhou
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Corresponding authors

Correspondence to Shunjie Dong or Jianjun Liu.

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Ethical approval

All procedures were performed in accordance with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study design and exemption from informed consent were approved by the Institutional Review Board of the Ren Ji Hospital.

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Zhou, X., Fu, Y., Dong, S. et al. Intelligent ultrafast total-body PET for sedation-free pediatric [18F]FDG imaging. Eur J Nucl Med Mol Imaging (2024). https://doi.org/10.1007/s00259-024-06649-2

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