Personalized image-based radiation dosimetry for routine clinical use in peptide receptor radionuclide therapy: pretherapy experience

Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy

Purpose

Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment.

Methods

Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with ¹⁷⁷Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy ⁶⁸ Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of ¹⁷⁷Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry.

Results

An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen.

Conclusion

The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05883-w.

Technical Note: Simplified and practical pretherapy tumor dosimetry - A feasibility study for 131 I-MIBG therapy of neuroblastoma using 124 I-MIBG PET/CT

PURPOSE

Radiation dose calculated on tumors for radiopharmaceutical therapy varies significantly from tumor to tumor and from patient to patient. Accurate estimation of radiation dose requires multiple time point measurements using radionuclide imaging modalities such as SPECT or PET. In this report, we show our technical development of reducing the number of scans needed for reasonable estimation of tumor and normal organ dose in our pretherapy imaging and dosimetry platform of ¹²⁴ I-metaiodobenzylguanidine (MIBG) positron emission tomography/computed tomography (PET/CT) for ¹³¹ I-MIBG therapy of neuroblastoma.

METHODS

We analyzed the simplest kinetic data, areas of two-time point data for five patients with neuroblastoma who underwent 3 or 4 times of ¹²⁴ I-MIBG PET/CT scan prior to ¹³¹ I-MIBG therapy. The data for which we derived areas were percent of injected activity (%IA) and standardized uptake value of tumors. These areas were correlated with time-integrated activity coefficients (TIACs) from full data (3 or 4 time points). TIACs are direct correlates with radiation dose as long as the volume and the radionuclide are known.

RESULTS

The areas of %IAs between data obtained from all the two-time points with time points 1 and 2 (day 0 and day 1), time points 2 and 3 (day 1 and day 2), and time points 1 and 3 (day 0 and day 2) showed reasonable correlation (Pearson's correlation coefficient |r| > 0.5) with not only tumor and organ TIACs but also tumor and organ absorbed doses. The tumor and organ doses calculated using %IA areas of time point 1 and time point 2 were our best fits at about 20% individual percent difference compared to doses calculated using 3 or 4 time points.

CONCLUSIONS

We could achieve reasonable accuracy of estimating tumor doses for subsequent radiopharmaceutical therapy using only the two-time point imaging sessions. Images obtained from these time points (within the 48-h after administration of radiopharmaceutical) were also viewed as useful for diagnostic reading. Although our analysis was specific to ¹²⁴ I-MIBG PET/CT pretherapy imaging data for ¹³¹ I-MIBG therapy of neuroblastoma and the number of imaging datasets was not large, this feasible methodology would generally be applicable to other imaging and therapeutic radionuclides with an appropriate data analysis similar to our analysis to other imaging and therapeutic radiopharmaceuticals.

Technical Note: Single time point dose estimate for exponential clearance

OBJECTIVE

Although personalized dosimetry may be desirable for radionuclide therapy treatments, the multiple time samples required to determine the total integrated activity puts a burden on patients and clinic resources. The aim of this paper is to demonstrate that when some prior knowledge is known about the tracer kinetic parameters, the total integrated activity (and thus radiation dose) can be estimated from a single time sample.

METHODS

Mathematical derivations have been performed to generate equations for the total integrated activity in terms of a single time sample of activity for monoexponential and biexponential clearance. Simulations were performed using both exponential models where the rate constants and associated parameters were randomly sampled from distributions with a known mean. The actual total integrated activity for each random sample was compared with the estimated total integrated activity using the mean value of the parameters. Retrospective analysis of ⁹⁰ Y DOTATOC data from a clinical trial provided a comparison of actual kidney dose with the estimated kidney dose using the single time point approach.

RESULTS

The optimal sampling time for the single point approach was found to be equal to the mean time of the rate constant. The simulation results for the monoexponential and biexpoential models were similar. Regressions comparing the actual and estimated total integrated activity had very high correlations (r²  > 0.95) along with acceptable standard errors of estimate, especially at the optimal sampling point. The retrospective analysis of the ⁹⁰ Y DOTATOC data also yielded similar results with an r²  = 0.95 and a standard error of estimate of 61 cGy.

CONCLUSIONS

In situations where there is prior knowledge about the population averages of kinetic parameters, these results suggest that the single time point approach can be used to estimate the total integrated activity and dose with sufficient accuracy to manage radionuclide therapy. This will make personalized dosimetry much easier to perform and more available to the community.