Technical note: A wearable radiation measurement system for collection of patient‐specific time‐activity data in radiopharmaceutical therapy: system design and Monte Carlo simulation results

Purpose: A high level of personalization in Molecular Radiotherapy (MRT) could bring advantages in terms of treatment effectiveness and toxicity reduction. Individual organ‐level dosimetry is crucial to describe the radiopharmaceutical biodistribution expressed by the patient, to estimate absorbed doses to normal organs and target tissue(s). This paper presents a proof‐of‐concept Monte Carlo simulation study of “WIDMApp” (Wearable Individual Dose Monitoring Apparatus), a multi‐channel radiation detector and data processing system for in vivo patient measurement and collection of radiopharmaceutical biokinetic data (i.e., time‐activity data). Potentially, such a system can increase the amount of such data that can be collected while reducing the need to derive it via nuclear medicine imaging. Methods: a male anthropomorphic MIRD phantom was used to simulate photons (i.e., gamma‐rays) propagation in a patient undergoing a 131I thyroid treatment. The administered activity was set to the amount usually administered for the treatment of differentiated carcinoma while its initial distribution in different organs was assigned following the ICRP indications for the 131I biokinetics. Using this information, the simulation computes the Time‐dependent Counts Curves (TCCs) that would have been measured by seven WIDMApp‐like sensors placed and oriented to face each one of five emitting organs plus two thyroid lobes. A deconvolution algorithm was then applied on this simulated data set to reconstruct the Time‐Activity Curve (TAC) of each organ. Deviations of the reconstructed TACs parameters from values used to generate them were studied as a function of the deconvolution algorithm initialization parameters and assuming non‐Poisson fluctuation of the TCCs data points. Results: This study demonstrates that it is possible, at least in the simple simulated scenario, to reconstruct the organ cumulated activity by measuring the time dependence of counts recorded by several detectors placed at selected positions on the patient's body. The ability to perform in vivo sampling more frequently than conventional biokinetic studies increases the number of time points and therefore the accuracy in TAC estimates. In this study, an accuracy on cumulated activity of 5% is obtained even with a 20% error on the TCC data points and a 50% error on the initial guess on the parameters of the deconvolution algorithm. Conclusions: the WIDMApp approach could provide an effective tool to charact