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Evaluation of PET List Data-Driven Gated Motion Correction Technique Applied in Lung Tumors

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Abstract

Purpose

Positron emission tomography/computed tomography (PET/CT) is an important tool for tumor staging or treatment response evaluation, especially for lung tumors. However, the captured static PET image could be blurry due to patients' free breathing, resulting in decreased image quality and incorrect quantitative values. This study aimed to evaluate whether the Q.Static scan mode with the novel PET list data-driven gated (DDG) technique decreases the lesion blurring problems in the PET/CT images of patients with lung cancer.

Methods

Data of 194 patients with lung tumors were retrospectively reviewed. DDG Q.Static scan mode was set up in three beds to cover the whole chest and the upper abdomen in the routine PET/CT scans and was activated automatically when sensing significant respiratory motion. Routine reconstruction algorithm was applied for data analysis. Only the lesions in the motion-corrected areas were measured and calculated for statistics.

Results

Among the 194 patients, 124 had at least one bed that activated the DDG Q.Static procedure. However, only 49 out of the 124 patients showed lesions in their activated beds. Compared with the non-corrected data, the DDG Q.Static data showed improved accuracy with increased SUVmax and SUVmean of 8.52% (9.20 ± 5.42 to 9.74 ± 5.42) and 8.65% (6.11 ± 3.68 to 6.48 ± 3.68), respectively. In addition, metabolic tumor volume was reduced from 6.54 ± 8.58 to 5.55 ± 7.33 (14.79% reduction). For subjective image quality, the DDG Q.Static data scored higher than the non-corrected data.

Conclusion

This study showed that the quantitative values and image quality were improved after the correction. Therefore, the DDG Q.Static technique is an effective method to correct motion artifacts in PET/CT scans.

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Authors and Affiliations

  1. Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei City, Taiwan

    Yi-Lun Chen, Bang-Hung Yang & Ko-Han Lin

  2. Association of Taipei Radiological Technologist, Taipei, Taiwan

    Yi-Lun Chen & Bang-Hung Yang

  3. GE Healthcare, Taipei, Taiwan

    I.-Ling Shih

Authors
  1. Yi-Lun Chen
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  2. Bang-Hung Yang
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  3. I.-Ling Shih
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  4. Ko-Han Lin
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Correspondence to Ko-Han Lin.

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Chen, YL., Yang, BH., Shih, IL. et al. Evaluation of PET List Data-Driven Gated Motion Correction Technique Applied in Lung Tumors. J. Med. Biol. Eng. 42, 382–387 (2022). https://doi.org/10.1007/s40846-022-00719-2

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  • DOI: https://doi.org/10.1007/s40846-022-00719-2

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