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European Journal of Nuclear Medicine and Molecular Imaging

Open Access 09-05-2024 | Positron Emission Tomography | Original Article

Pre-therapy PET-based voxel-wise dosimetry prediction by characterizing intra-organ heterogeneity in PSMA-directed radiopharmaceutical theranostics

Authors: Song Xue, Andrei Gafita, Yu Zhao, Lorenzo Mercolli, Fangxiao Cheng, Isabel Rauscher, Calogero D’Alessandria, Robert Seifert, Ali Afshar-Oromieh, Axel Rominger, Matthias Eiber, Kuangyu Shi

Published in: European Journal of Nuclear Medicine and Molecular Imaging

Abstract

Background and objective

Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.

Methods

23 patients with metastatic castration-resistant prostate cancer treated with [¹⁷⁷Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.

Results

Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R² = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.

Conclusion

Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.

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Title: Pre-therapy PET-based voxel-wise dosimetry prediction by characterizing intra-organ heterogeneity in PSMA-directed radiopharmaceutical theranostics
Authors: Song Xue
Andrei Gafita
Yu Zhao
Lorenzo Mercolli
Fangxiao Cheng
Isabel Rauscher
Calogero D’Alessandria
Robert Seifert
Ali Afshar-Oromieh
Axel Rominger
Matthias Eiber
Kuangyu Shi
Publication date: 09-05-2024
Publisher: Springer Berlin Heidelberg
Keywords: Positron Emission Tomography
Pharmacokinetics
Published in: European Journal of Nuclear Medicine and Molecular Imaging
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-024-06737-3

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Pre-therapy PET-based voxel-wise dosimetry prediction by characterizing intra-organ heterogeneity in PSMA-directed radiopharmaceutical theranostics

Abstract

Background and objective

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background and objective

Methods

Results

Conclusion

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