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Background <p>To maintain diagnostic accuracy, positron emission tomography-computed tomography (PET/CT) systems require rigorous quality control (QC) protocols. This study presents a four-year (2020–2024) longitudinal analysis of PET/CT system stability, introducing quantum efficiency as a novel QC metric alongside key performance parameters, including time-of-flight (TOF) accuracy, energy drift in silicon photomultipliers (SiPMs), and look-up table (LUT) stability.</p> Methods <p>Weekly QC procedures were performed using ISO-Rod and cylindrical calibration phantoms under standard accepted protocols. Key performance metrics analyzed included TOF accuracy, energy drift, LUT stability, and quantum efficiency. Environmental factors (temperature and humidity) and voltage stability were monitored. Statistical analyses, including ANOVA and sensitivity assessments, were applied to identify significant trends and correlations. A p-value &lt; 0.05 was considered statistically significant.</p> Results <p>The PET/CT system exhibited stable performance throughout the four years, with significant deviations in 2022, primarily due to increased humidity (<i>p</i> = 0.013). These deviations affected TOF accuracy and energy drift, reducing spatial resolution and increasing image noise, potentially impacting diagnostic precision. Sensitivity analysis confirmed these factors as the primary contributors to system instability in 2022. Despite minor quantum efficiency and LUT stability fluctuations, all deviations remained within clinically acceptable limits, confirming the robustness of applied calibration protocols.</p> Conclusion <p>This study underscores the importance of TOF accuracy, energy drift, and quantum efficiency in PET/CT system performance. The findings provide actionable insights for optimizing clinical QC protocols by integrating enhanced monitoring practices and preventive maintenance strategies, ensuring consistent system reliability and high-quality imaging in clinical practice.</p>

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Longitudinal quality control analysis of PET/CT Systems: analyzing system stability, image quality, and the performance of silicon photomultipliers (SiPMs)

  • 期刊论文

  • 发表日期：

    2025年5月20日

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  • Morad El Kafhali,
  • Marziyeh Tahmasbi,
  • Nor El Houda Baghous,
  • Amina El Kessioui,
  • El Mahjoub Chakir,
  • Rajaa Sebihi,
  • Mohammed Khalis

摘要

Background

To maintain diagnostic accuracy, positron emission tomography-computed tomography (PET/CT) systems require rigorous quality control (QC) protocols. This study presents a four-year (2020–2024) longitudinal analysis of PET/CT system stability, introducing quantum efficiency as a novel QC metric alongside key performance parameters, including time-of-flight (TOF) accuracy, energy drift in silicon photomultipliers (SiPMs), and look-up table (LUT) stability.

Methods

Weekly QC procedures were performed using ISO-Rod and cylindrical calibration phantoms under standard accepted protocols. Key performance metrics analyzed included TOF accuracy, energy drift, LUT stability, and quantum efficiency. Environmental factors (temperature and humidity) and voltage stability were monitored. Statistical analyses, including ANOVA and sensitivity assessments, were applied to identify significant trends and correlations. A p-value < 0.05 was considered statistically significant.

Results

The PET/CT system exhibited stable performance throughout the four years, with significant deviations in 2022, primarily due to increased humidity (p = 0.013). These deviations affected TOF accuracy and energy drift, reducing spatial resolution and increasing image noise, potentially impacting diagnostic precision. Sensitivity analysis confirmed these factors as the primary contributors to system instability in 2022. Despite minor quantum efficiency and LUT stability fluctuations, all deviations remained within clinically acceptable limits, confirming the robustness of applied calibration protocols.

Conclusion

This study underscores the importance of TOF accuracy, energy drift, and quantum efficiency in PET/CT system performance. The findings provide actionable insights for optimizing clinical QC protocols by integrating enhanced monitoring practices and preventive maintenance strategies, ensuring consistent system reliability and high-quality imaging in clinical practice.