{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T23:17:04Z","timestamp":1789514224130,"version":"build-2803163510"},"reference-count":38,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T00:00:00Z","timestamp":1758153600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T00:00:00Z","timestamp":1758153600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Molecular radiotherapy with [\n                      <jats:sup>177<\/jats:sup>\n                      Lu]Lu\u2010PSMA\u2010617 is an effective treatment for metastatic castration\u2010resistant prostate cancer. Accurate dosimetry is essential for maximizing therapeutic efficacy while minimizing toxicity. However, standard dosimetry requires multiple imaging sessions, posing logistical challenges. Single\u2010time\u2010point (STP) dosimetry offers a practical alternative but remains challenging for tumor kinetics due to high inter\u2010patient variability. Nonlinear mixed\u2010effects (NLME) modeling, combined with population\u2010based model selection (PBMS), has demonstrated potential for improving STP dosimetry accuracy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      The purpose of this study was to evaluate the accuracy of STP tumor dosimetry using SPECT\/CT data, PBMS, and an NLME model in a large population with diverse biokinetic measurements for [\n                      <jats:sup>177<\/jats:sup>\n                      Lu]Lu\u2010PSMA\u2010617 therapy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Biokinetic data for [\n                      <jats:sup>177<\/jats:sup>\n                      Lu]Lu\u2010PSMA\u2010617 in tumors were obtained from forty\u2010nine patients with metastatic castration\u2010resistant prostate cancer using SPECT\/CT at time points (1.80\u00a0\u00b1\u00a00.80), (18.67\u00a0\u00b1\u00a00.90), (42.63\u00a0\u00b1\u00a01.03), (66.27\u00a0\u00b1\u00a00.96), and (159.02\u00a0\u00b1\u00a023.35)\u00a0h after injection. Ten different functions, derived from various parameterizations of two\u2010 to four\u2010exponential functions, were fitted to the data using the NLME framework. Each function's parameters were defined as a combination of fixed and random effects. A PBMS approach was employed, using goodness\u2010of\u2010fit tests and Akaike weights to identify the function best supported by the data. The selected function from the NLME fitting of all time points with the leave\u2010one\u2010out method was used to calculate the reference time\u2010integrated activities per volume (TIAVs). The parameters from STP fitting were used to calculate the STP TIAVs. Additionally, STP dosimetry was performed using the H\u00e4nscheid method to calculate the TIAVs. Relative deviations (RDs) and root\u2010mean\u2010square errors (RMSEs) were used to analyse the accuracy of the calculated STP TIAVs and H\u00e4nscheid method TIAVs compared with the reference TIAVs.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The function  was selected as the fit function most supported by the data with an Akaike weight of 93%. For STP dosimetry, a single SPECT\/CT measurement at time point 4 (66.3\u00a0\u00b1\u00a00.9\u00a0h) after injection showed a relatively low mean RD of 0.5%\u00a0\u00b1\u00a011.0% and median RD of \u20100.6%. The RMSEs for the STP TIAVs RDs for time points 1\u20135 were 53%, 29%, 17%, 11%, and 38%, respectively. The STP tumor dosimetry using the PBMS NLME method outperformed the H\u00e4nscheid method for all investigated time points.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Our findings demonstrate that a single SPECT\/CT measurement at 3 days after injection may be used to estimate tumor TIAVs in [\n                      <jats:sup>177<\/jats:sup>\n                      Lu]Lu\u2010PSMA\u2010617 therapy using the NLME method and PBMS.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70000","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T03:41:17Z","timestamp":1758253277000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Single\u2010time\u2010point tumor dosimetry using population\u2010based model selection and 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