PURPOSE: Targeted radionuclide therapy is being increasingly used in malignancies. According to regulatory requirements patient-specific dosimetry must be performed in the context of any radiotherapeutic procedure. A calculatory model is presented demonstrating how to individualize radionuclide therapy through dosimetric data by weighing the success of therapy against risk. The model is exemplarily implemented for radioiodine therapy of differentiated thyroid carcinoma (DTC). METHODS: For DTC dose-response relationships were retrieved from the literature. From these data a three-variable model was developed which consists of a target variable weighing response against risk, a measured variable representing the lesion dose per activity [LDpA, in units gray per gigabecquerel (Gy/GBq)] and a manipulated variable constituting the therapeutic activity. RESULTS: Dosimetry-related radioiodine therapy along the three-variable model increases response probability in individual patients by up to > 50% (e.g. from 18 to 72% at a LDpA of 6 Gy/GBq) compared to "standard" therapy with 7 GBq. On a patient population scale, by escalating and de-escalating activity along the model, the overall response rate can be enhanced by 8% (62 vs 70%) while saving on average 0.9 GBq per patient (7 vs 6.1 GBq). CONCLUSION: Redistribution of therapeutic activities along the model, i.e. taking into account success and risk, may enhance response while on average saving activity as exemplarily shown by a virtual comparison with standard approaches using literature data from DTC for implementation. The model may thus provide a guideline for the prescription of therapeutic activities; the results underline the potential impact of individual dosimetry in radionuclide therapy.
PURPOSE: Targeted radionuclide therapy is being increasingly used in malignancies. According to regulatory requirements patient-specific dosimetry must be performed in the context of any radiotherapeutic procedure. A calculatory model is presented demonstrating how to individualize radionuclide therapy through dosimetric data by weighing the success of therapy against risk. The model is exemplarily implemented for radioiodine therapy of differentiated thyroid carcinoma (DTC). METHODS: For DTC dose-response relationships were retrieved from the literature. From these data a three-variable model was developed which consists of a target variable weighing response against risk, a measured variable representing the lesion dose per activity [LDpA, in units gray per gigabecquerel (Gy/GBq)] and a manipulated variable constituting the therapeutic activity. RESULTS: Dosimetry-related radioiodine therapy along the three-variable model increases response probability in individual patients by up to > 50% (e.g. from 18 to 72% at a LDpA of 6 Gy/GBq) compared to "standard" therapy with 7 GBq. On a patient population scale, by escalating and de-escalating activity along the model, the overall response rate can be enhanced by 8% (62 vs 70%) while saving on average 0.9 GBq per patient (7 vs 6.1 GBq). CONCLUSION: Redistribution of therapeutic activities along the model, i.e. taking into account success and risk, may enhance response while on average saving activity as exemplarily shown by a virtual comparison with standard approaches using literature data from DTC for implementation. The model may thus provide a guideline for the prescription of therapeutic activities; the results underline the potential impact of individual dosimetry in radionuclide therapy.
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