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Background <p>A deep learning-based image reconstruction (DLR) algorithm that can reduce the statistical noise has been developed for PET/CT imaging. It may reduce the administered dose of <sup>18</sup>F-FDG and minimize radiation exposure while maintaining diagnostic quality. This retrospective study evaluated whether the injected <sup>18</sup>F-FDG dose could be reduced by applying DLR to PET images. To this aim, we compared the quantitative image quality metrics and the false-positive rate between DLR with a reduced <sup>18</sup>F-FDG dose and Ordered Subsets Expectation Maximization (OSEM) with a standard dose.</p> Results <p>This study included 90 oncology patients who underwent <sup>18</sup>F-FDG PET/CT. They were divided into 3 groups (30 patients each): group A (<sup>18</sup>F-FDG dose per body weight [BW]: 2.00—2.99&#xa0;MBq/kg; PET image reconstruction: DLR), group B (3.00–3.99&#xa0;MBq/kg; DLR), and group C (standard dose group; 4.00—4.99&#xa0;MBq/kg; OSEM). The evaluation was performed using the signal-to-noise ratio (SNR), target-to-background ratio (TBR), and false-positive rate. DLR yielded significantly higher SNRs in groups A and B than group C (<i>p</i> &lt; 0.001). There was no significant difference in the TBR between groups A and C, and between groups B and C (<i>p</i> = 0.983 and 0.605, respectively). In group B, more than 80% of patients weighing less than 75&#xa0;kg had at most one false positive result. In contrast, in group B patients weighing 75&#xa0;kg or more, as well as in group A, less than 80% of patients had at most one false-positives.</p> Conclusions <p>Our findings suggest that the injected <sup>18</sup>F-FDG dose can be reduced to 3.0&#xa0;MBq/kg in patients weighing less than 75&#xa0;kg by applying DLR. Compared to the recommended dose in the European Association of Nuclear Medicine (EANM) guidelines for 90&#xa0;s per bed position (4.7&#xa0;MBq/kg), this represents a dose reduction of 36%. Further optimization of DLR algorithms is required to maintain comparable diagnostic accuracy in patients weighing 75&#xa0;kg or more.</p>

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18F-FDG dose reduction using deep learning-based PET reconstruction

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • Ryuji Akita,
  • Komei Takauchi,
  • Mana Ishibashi,
  • Shota Kondo,
  • Shogo Ono,
  • Kazushi Yokomachi,
  • Yusuke Ochi,
  • Masao Kiguchi,
  • Hidenori Mitani,
  • Yuko Nakamura,
  • Kazuo Awai

摘要

Background

A deep learning-based image reconstruction (DLR) algorithm that can reduce the statistical noise has been developed for PET/CT imaging. It may reduce the administered dose of 18F-FDG and minimize radiation exposure while maintaining diagnostic quality. This retrospective study evaluated whether the injected 18F-FDG dose could be reduced by applying DLR to PET images. To this aim, we compared the quantitative image quality metrics and the false-positive rate between DLR with a reduced 18F-FDG dose and Ordered Subsets Expectation Maximization (OSEM) with a standard dose.

Results

This study included 90 oncology patients who underwent 18F-FDG PET/CT. They were divided into 3 groups (30 patients each): group A (18F-FDG dose per body weight [BW]: 2.00—2.99 MBq/kg; PET image reconstruction: DLR), group B (3.00–3.99 MBq/kg; DLR), and group C (standard dose group; 4.00—4.99 MBq/kg; OSEM). The evaluation was performed using the signal-to-noise ratio (SNR), target-to-background ratio (TBR), and false-positive rate. DLR yielded significantly higher SNRs in groups A and B than group C (p < 0.001). There was no significant difference in the TBR between groups A and C, and between groups B and C (p = 0.983 and 0.605, respectively). In group B, more than 80% of patients weighing less than 75 kg had at most one false positive result. In contrast, in group B patients weighing 75 kg or more, as well as in group A, less than 80% of patients had at most one false-positives.

Conclusions

Our findings suggest that the injected 18F-FDG dose can be reduced to 3.0 MBq/kg in patients weighing less than 75 kg by applying DLR. Compared to the recommended dose in the European Association of Nuclear Medicine (EANM) guidelines for 90 s per bed position (4.7 MBq/kg), this represents a dose reduction of 36%. Further optimization of DLR algorithms is required to maintain comparable diagnostic accuracy in patients weighing 75 kg or more.