Proof-of-concept of DosiTest: A virtual multicentric clinical trial for assessing uncertainties in molecular radiotherapy dosimetry

Gunjan Kayal, Noami Clayton, Alex Vergara Gil, Lara Struelens, Manuel Bardiès

Research outputpeer-review


Clinical dosimetry in molecular radiotherapy (MRT) is a multi-step procedure, prone to uncertainties at every stage of the dosimetric workflow. These are difficult to assess, especially as some are complex or even impossible to measure experimentally. The DosiTest project was initiated to assess the variability associated with clinical dosimetry, by setting up a ‘virtual’ multicentric clinical dosimetry trial based on Monte Carlo (MC) modelling. A reference patient model with a realistic geometry and activity input for a specific tracer is considered. Reference absorbed dose rate distribution maps are generated at various time-points from MC modelling, combining precise information on density and activity distributions (voxel wise). Then, centre-specific calibration and patient SPECT/CT datasets are modelled, on which the clinical centres can perform clinical (i.e. image-based) dosimetry. The results of this dosimetric analysis can be benchmarked against the reference dosimetry to assess the variability induced by implementing different clinical dosimetry approaches. The feasibility of DosiTest is presented here for a clinical situation of therapeutic administration of 177Lu-DOTATATE (Lutathera®) peptide receptor radionuclide therapy (PRRT). From a real patient dataset composed of 5 SPECT/CT images and associated calibrations, we generated the reference absorbed dose rate images with GATE. Then, simulated SPECT/CT image generation based on GATE was performed, both for a calibration phantom and virtual patient images. Based on this simulated dataset, image-based dosimetry could be performed, and compared with reference dosimetry. The good agreement, between real and simulated images, and between reference and image-based dosimetry established the proof of concept of DosiTest.
Original languageEnglish
Pages (from-to)25-35
Number of pages11
JournalPhysica Medica
StatePublished - May 2022

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