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

¹³¹I-metaiodobenzylguanidine (¹³¹I-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, ¹³¹I-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.

This study aims to develop and validate a simplified dosimetry method for ¹³¹I-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 ¹²⁴I-MIBG PET imaging data.

Five subjects with neuroblastoma underwent ¹²⁴I-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.

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.

We developed a novel dosimetry method based on two-time-point imaging and kinetic modeling that enables simplified TIA estimation in ¹³¹I-MIBG therapy. Validated using ¹²⁴I-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.