Abstract
BackgroundIndividualized dosimetry is recommended for [177Lu]Lu-PSMA radioligand therapy (RLT) which is resource-intensive and protocols are often not optimized. Therefore, a simulation study was performed focusing on the determination of efficient optimal sampling schedules (OSS) for renal and tumour dosimetry by investigating different numbers of time points (TPs).MethodsSampling schedules with 1–4 TPs were investigated. Time-activity curves of the kidneys and two tumour lesions were generated based on a physiologically based pharmacokinetic (PBPK) model and biokinetic data of 13 patients who have undergone [177Lu]Lu-PSMA I&T therapy. Systematic and stochastic noise of different ratios was considered when modelling time-activity data sets. Time-integrated activity coefficients (TIACs) were estimated by simulating the hybrid planar/SPECT method for schedules comprising at least two TPs. TIACs based on one single SPECT/CT measurement were estimated using an approximation for reducing the number of fitted parameters. For each sampling schedule, the root-mean-squared error (RMSE) of the deviations of the simulated TIACs from the ground truths for 1000 replications was used as a measure for accuracy and precision.ResultsAll determined OSS included a late measurement at 192 h p.i., which was necessary for accurate and precise tumour TIACs. OSS with three TPs were identified to be 3–4, 96–100 and 192 h with an additional SPECT/CT measurement at the penultimate TP. Kidney and tumour RMSE of 6.4 to 7.7% and 6.3 to 7.8% were obtained, respectively. Shortening the total time for dosimetry to e.g. 96 h resulted in kidney and tumour RMSE of 6.8 to 8.3% and 9.1 to 11%, respectively. OSS with four TPs showed similar results as with three TPs. Planar images at 4 and 68 h and a SPECT/CT shortly after the 68 h measurement led to kidney and tumour RMSE of 8.4 to 12% and 12 to 16%, respectively. One single SPECT/CT measurement at 52 h yielded good approximations for the kidney TIACs (RMSE of 7.0%), but led to biased tumour TIACs.ConclusionOSS allow improvements in accuracy and precision of renal and tumour dosimetry for [177Lu]Lu-PSMA therapy with potentially less effort. A late TP is important regarding accurate tumour TIACs.
Highlights
In recent years, radioligands labelled with 177Lu targeting the prostate-specific membrane antigen (PSMA), such as [177Lu]Lu-PSMA-617 [1] and [177Lu]Lu-PSMA I&T [2], were established as promising treatment options for patients with metastasized castration-resistant prostate cancer after exhaustion of approved treatments [3, 4].Renal dosimetry should be applied for therapy monitoring as kidneys have been identified as a potential dose-limiting organ [2, 5]
Optimal sampling schedules The determined optimal sampling schedules (OSS) for estimating renal and tumour Time-integrated activity coefficient (TIAC) using the hybrid planar/ Singlephoton emission computed tomography (SPECT) method were independent on the investigated fraction of systematic error fsyst to the total error with one exception (Table 1)
The method with a single SPECT/X-ray computed tomography (CT) resulted in kidney RMSE for the kidneys (RMSEK) values similar to those estimated with 2–4 time points (TPs) and the hybrid planar/SPECT method
Summary
Renal dosimetry should be applied for therapy monitoring as kidneys have been identified as a potential dose-limiting organ [2, 5]. Inter-patient variabilities in anatomy and (patho‐)physiology can lead to large differences in absorbed dose coefficients. Okamoto et al reported renal absorbed dose coefficients in the range of 0.33–1.22 Gy/GBq in a cohort of 15 patients with mCRPC treated with [177Lu]Lu-PSMA I&T [1]. Individualized treatments are expected to lead to better outcomes than population-based treatments. Individualized dosimetry is recommended for [177Lu]Lu-PSMA radioligand therapy (RLT) which is resource-intensive and protocols are often not optimized. A simulation study was performed focusing on the determination of efficient optimal sampling schedules (OSS) for renal and tumour dosimetry by investigating different numbers of time points (TPs)
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