Simplified dosimetry using two‐time‐point kinetic modeling of ¹²⁴ I‐MIBG PET for ¹³¹ I‐MIBG therapy in neuroblastoma

Background 131 I‐metaiodobenzylguanidine ( 131 I‐MIBG) therapy is an established and effective treatment for metastatic neuroblastoma. Due to the substantial variability in absorbed dose across different tumor sites and organs, 131 I‐MIBG dosimetry, such as achieved via SPECT imaging, is critical for enabling personalized therapy planning. However, conventional imaging‐based dosimetry typically requires three or more imaging sessions to reliably estimate time‐integrated activity (TIA) of tumors and organs, which imposes workflow burdens and increases patient inconvenience. Therefore, there is a clear need for dosimetry methods that can maintain accuracy while requiring fewer imaging sessions. Purpose This study aims to develop and validate a simplified dosimetry method for 131 I‐MIBG therapy that enables robust estimation of TIA using only two imaging time points. The method leverages kinetic modeling to estimate tumor and organ time‐activity curves (TACs) and TIAs from limited imaging data and was validated using 124 I‐MIBG PET imaging data. Methods Five subjects with neuroblastoma underwent 124 I‐MIBG PET/CT imaging at three or four time points post‐administration. Two imaging time points (∼28 and ∼113 h post‐administration) were selected for TIA estimation using a kinetic modeling framework. To obtain the blood input function, left ventricular activity at the two time points was extracted and fitted to a mono‐exponential function. With this input function, a one‐tissue compartmental model was then applied to estimate tumor and organ TACs from the two‐time‐point data, and the corresponding TIAs were calculated by integrating the modeled TACs. The proposed method was compared with (1) a conventional mono‐exponential fitting method using the same two‐time‐point data, and (2) a reference standard based on bi‐exponential fitting of all available three‐ or four‐time‐point data. To evaluate the performance of the proposed method, relative errors in TIA estimation for tumors and organs were calculated using the bi‐exponential fitting results as the reference. Results The proposed method achieved substantially improved accuracy over mono‐exponential fitting. Taking the bi‐exponential method as the reference, the proposed method yielded an average TIA estimation bias of 0.3%, a standard deviation of 13.8%, and a root mean square error (RMSE) of 14.2%. In contrast, mono‐exponential fitting resulted in a higher bias of 14.9%, a standard deviation of 36.3%, and an RMSE of 39.5%. Specifically, the proposed method outperformed mono‐exponential fitting in tumors, adrenal glands, brain, and thyroid. Conclusions We developed a novel dosimetry method based on two‐time‐point imaging and kinetic modeling that enables simplified TIA estimation in 131 I‐MIBG therapy. Validated using 124 I‐MIBG PET data, this approach demonstrated improved TIA estimation performance compared with conventional mono‐exponential fitting. It may offer a physiologically motivated and more clinically applicable solution that supports personalized dosimetry and facilitates individualized treatment planning in radiopharmaceutical therapy.