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<p>Positron emission tomography (PET) images can be compromised by respiratory motion, leading to a decreased standardized uptake value (SUV) of the lesion and overestimation of the metabolic tumor volume (MTV). This study aimed to determine the optimal settings for auto-gating, a deviceless respiratory synchronization technique, using advanced intelligent clear-IQ engines (AiCE) and clear adaptive low-noise method (CaLM) reconstruction conditions. We performed phantom and clinical studies on 57 patients with pulmonary lesions. We acquired images at various %count settings (nongated, 30%, 50%, and 70%) using both AiCE and CaLM. In each setting, we measured the SUVmax, SUVpeak, and MTV of the lesions and calculated and compared the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) in the liver. Additionally, we visually assessed lesion blurring and image noise to confirm whether the quantitative evaluation was consistent with the visual evaluation. Considering our findings, the optimal auto-gating setting at an acquisition time of 180&#xa0;s is 50% for the lower lobe in AiCE and for both the lower and middle lobes in CaLM.</p>

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Investigation of optimal settings for deviceless respiratory synchronization in PET/CT examinations: effects of different reconstructions on image quality

  • 期刊论文

  • 发表日期：

    2025年9月26日

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  • Naoto Mori,
  • Kunihiro Iwata,
  • Takahiro Uno,
  • Taku Uchibe,
  • Atsutaka Okizaki

摘要

Positron emission tomography (PET) images can be compromised by respiratory motion, leading to a decreased standardized uptake value (SUV) of the lesion and overestimation of the metabolic tumor volume (MTV). This study aimed to determine the optimal settings for auto-gating, a deviceless respiratory synchronization technique, using advanced intelligent clear-IQ engines (AiCE) and clear adaptive low-noise method (CaLM) reconstruction conditions. We performed phantom and clinical studies on 57 patients with pulmonary lesions. We acquired images at various %count settings (nongated, 30%, 50%, and 70%) using both AiCE and CaLM. In each setting, we measured the SUVmax, SUVpeak, and MTV of the lesions and calculated and compared the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) in the liver. Additionally, we visually assessed lesion blurring and image noise to confirm whether the quantitative evaluation was consistent with the visual evaluation. Considering our findings, the optimal auto-gating setting at an acquisition time of 180 s is 50% for the lower lobe in AiCE and for both the lower and middle lobes in CaLM.