PT - JOURNAL ARTICLE AU - Gomes, Carlos Vinícius AU - Chen, Yizhou AU - Rauscher, Isabel AU - Xue, Song AU - Gafita, Andrei AU - Hu, Jiaxi AU - Seifert, Robert AU - Mercolli, Lorenzo AU - Brosch-Lenz, Julia AU - Hong, Jimin AU - Ryhiner, Marc AU - Ziegler, Sibylle AU - Afshar-Oromieh, Ali AU - Rominger, Axel AU - Eiber, Matthias AU - Lima, Thiago Viana Miranda AU - Shi, Kuangyu TI - Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning AID - 10.2967/jnumed.124.268175 DP - 2025 May 01 TA - Journal of Nuclear Medicine PG - 778--784 VI - 66 IP - 5 4099 - http://jnm.snmjournals.org/content/66/5/778.short 4100 - http://jnm.snmjournals.org/content/66/5/778.full SO - J Nucl Med2025 May 01; 66 AB - Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practice in radiopharmaceutical therapy (RPT) compared with conventional multiple-time-point image-based dosimetry. Despite numerous advancements, current STP methods are limited by the need for strict and late timing in data acquisition, posing challenges in routine clinical settings. This study introduces a new concept of instant STP (iSTP) dosimetry, achieved by predicting the effective half-life (Teff) of organs using machine learning applied on pretherapy patient data (PET and clinical values). Methods: Data from 22 patients who underwent pretherapy 68Ga-gallium N,N-bis[2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine-N,N-diacetic acid ([68Ga]Ga-PSMA-11) imaging and subsequently [177Lu]Lu-PSMA I&T RPT were analyzed. A machine learning model was developed for Teff predictions for the left and right kidneys, liver, and spleen subsequently used to estimate time-integrated activity and absorbed dose. iSTP results were compared against multiple-time-point and previously proposed Hänscheid methods. Our method comprised 2 different prediction scenarios, using data before each therapy cycle and from the first cycle. Results: The iSTP method introduced early posttherapy time points (2, 20, 43, and 69 h) for the left kidney, right kidney, liver, and spleen. Dosimetry in the first scenario, aggregating 2 and 20 h, achieved mean differences in time-integrated activity below 27% for all organs. To assess the feasibility, these time points were compared with the best results from the Hänscheid method (kidneys, 69 h; liver and spleen, 20 h). At 2 h, a significant difference (P < 0.001) was found for almost all organs except for the spleen (P = 0.1370). However, at 20 h, no significant differences were found for the right kidney, liver, and spleen, apart from the left kidney (P < 0.01). In the scenario using only the initial PET/CT data to predict Teff for subsequent cycles, iSTP dosimetry achieved no statistical significance (P > 0.05) for all cycles in comparison to results using PET data before each therapy cycle. Conclusion: Our preliminary results prove the concept for prediction of Teff with pretherapy data and achieving STP shortly and flexibly after the RPT. The proposed method may expedite the application of dosimetry in broader contexts, such as outpatient or short-duration inpatient treatment.