Improved random coincidence estimation including triple coincidence detection in PET.

Area of Science:

• Medical Imaging Physics
• Nuclear Medicine Technology
• Positron Emission Tomography (PET)

Background:

• Positron Emission Tomography (PET) imaging is challenged by random coincidences, where unrelated decay events are mistakenly identified as true coincidences.
• These misidentifications, particularly random triple coincidences, can introduce bias or reduce sensitivity in quantitative PET scans.
• Accurate correction is essential for reliable imaging of beta-plus (${\beta }^{+})\; and\; beta-plus-gamma\; ($ {\beta }^{+}\text{-}\gamma $)\; emitters.$

Purpose of the Study:

• To develop and validate an accurate method for estimating random double and triple coincidences in PET.
• To improve quantitative accuracy in PET imaging, especially for ${\beta }^{+}$ and ${\beta }^{+}\text{-}\gamma$ emitters.
• To evaluate the impact of random coincidences on true triple coincidences in dual-tracer PET and positronium lifetime imaging.

Main Methods:

• Developed coincidence identification schemes using veto intervals to separate double and triple coincidences.
• Employed extended delayed window techniques to estimate random coincidences, matching interval sizes for coincidence windows and vetoes.
• Validated the method using extensive simulations across various isotopes, scanner parameters, and phantom configurations, followed by experimental measurements on a brain PET scanner.

Main Results:

• The developed method achieved high accuracy in estimating random coincidences.
• Relative deviations were less than 3% for double coincidences and less than 5% for triple coincidences.
• Results were consistent for both ${\beta }^{+}$ and ${\beta }^{+}\text{-}\gamma$ emitters across simulated and measured data.

Conclusions:

• The proposed method provides an accurate and reliable approach for correcting random coincidences in PET.
• This advancement is crucial for enhancing the quantitative precision of PET imaging, particularly for complex tracer types.
• The findings support improved diagnostic capabilities through more accurate PET data analysis.