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A simulation-based method to determine optimal sampling schedules for dosimetry in radioligand therapy
Andreas Rinscheid1, Jeesoo Lee2, Peter Kletting1
1Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany; Department of Nuclear Medicine, Ulm University, Ulm, Germany.
Zeitschrift Fur Medizinische Physik
|January 7, 2019
Summary
Optimized sampling schedules improve radioligand therapy dosimetry by accurately determining time-integrated activity coefficients (TIACs). This method enhances accuracy and precision, outperforming existing schedules.
Area of Science:
- Nuclear Medicine
- Medical Physics
- Radiopharmaceutical Therapy
Background:
- Accurate dosimetry in radioligand therapy requires precise determination of time-integrated activity coefficients (TIACs) for organs and tumors.
- The selection of sampling schedules significantly influences TIACs and subsequent absorbed dose calculations.
- Existing sampling schemes may not be optimal for all clinical scenarios and patient populations.
Purpose of the Study:
- To develop a flexible method for analyzing various clinically applicable sampling schedules.
- To optimize sampling schedules for accurate TIAC determination using true time-activity curves (TACs) from virtual patients.
- To evaluate the impact of noise and time point variations on TIAC accuracy.
Main Methods:
- Created nine virtual patients with physiologically-based pharmacokinetic (PBPK) models and biokinetic data from patients treated with 111In-DOTATATE.
- Investigated 15,120 sampling schemes (4 time points each) with varying Gaussian noise levels.
- Determined patient-specific and population-specific optimal schedules using relative root-mean-square error (rRMSE) and deviation fractions.
Main Results:
- Optimal sampling schedules, both patient-specific and population-specific, consistently included a final time point (t4) at or after 96 hours across all noise levels.
- Shifting the latest time point to 48 hours significantly increased the deviation of TIACs (>10%) to 88% even at the lowest noise level.
- Population-specific optimal schedules yielded more accurate and precise TIACs compared to established literature schedules.
Conclusions:
- A robust method for optimizing sampling schedules in dosimetry, considering clinical constraints and measurement uncertainties, has been successfully developed and applied.
- Optimized sampling schedules significantly enhance the accuracy and precision of determined TIACs in radioligand therapy dosimetry.
- The findings support the use of tailored sampling schedules for improved patient-specific absorbed dose calculations.
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