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However, even recommended multiple-time-point (MTP) dosimetry remains subject to uncertainties related to limited sampling schedules, pharmacokinetic, and curve-fitting modeling assumptions. In patients with metastatic castration-resistant prostate cancer (mCRPC) treated with [\n                      <jats:sup>177<\/jats:sup>\n                      Lu]Lu-PSMA-617 RPT, we explored an outcome-driven dosimetry optimization strategy by comparing MTP and single-time-point (STP) dosimetry, and identifying optimal time-points (TPs) for H\u00e4nscheid approximation based on therapy outcomes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Clinical and image data from 50 patients were retrospectively analyzed. Transient treatment-emergent adverse events (TEAEs) and prostate-specific antigen (PSA) response were monitored following CTCAE v5.0 and PCWG3. Cycle-level mean absorbed doses (\n                      <jats:italic>MTPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      , and\n                      <jats:italic>1d-<\/jats:italic>\n                      ,\n                      <jats:italic>2d-<\/jats:italic>\n                      ,\n                      <jats:italic>3d-STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      based on single SPECT acquisitions at 1-, 2-, 3-day(s) p.i.) were computed for organs-at-risk and whole-body tumors. Additionally, cumulative absorbed doses (\n                      <jats:italic>STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      &amp;\n                      <jats:italic>MTPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      ) were derived for whole-body tumors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Bone marrow STP dosimetry correlated significantly with anaemia grading (\n                      <jats:italic>1d-STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      : Spearman\u2019s \u03c1=0.35;\n                      <jats:italic>2d-STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      : Spearman\u2019s \u03c1=0.41;\n                      <jats:italic>3d-STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      : Spearman\u2019s \u03c1=0.46; all\n                      <jats:italic>p<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>adj<\/jats:italic>\n                      <\/jats:sub>\n                      &lt;0.001), aligning with\n                      <jats:italic>MTPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      (Spearman\u2019s \u03c1=0.43,\n                      <jats:italic>p<\/jats:italic>\n                      &lt;0.001). Williams\u2019\n                      <jats:italic>F<\/jats:italic>\n                      -test confirmed no significant difference in correlation strength between\n                      <jats:italic>STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      &amp;\n                      <jats:italic>MTPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>tox<\/jats:italic>\n                      <\/jats:sub>\n                      derived correlations at any TPs. For PSA response, both\n                      <jats:italic>MTPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      (Spearman\u2019s \u03c1=-0.26,\n                      <jats:italic>p<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>adj<\/jats:italic>\n                      <\/jats:sub>\n                      &lt;0.05) and\n                      <jats:italic>STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      (\n                      <jats:italic>1d-<\/jats:italic>\n                      &amp;\n                      <jats:italic>2d-STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      : Spearman\u2019s \u03c1=-0.34,\n                      <jats:italic>p<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>adj<\/jats:italic>\n                      <\/jats:sub>\n                      &lt;0.001) showed significant correlations, without statistically significant differences between\n                      <jats:italic>STPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      &amp;\n                      <jats:italic>MTPD<\/jats:italic>\n                      <jats:sub>\n                        <jats:italic>cum<\/jats:italic>\n                      <\/jats:sub>\n                      derived correlations.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The outcome-driven TP selection for H\u00e4nscheid-based STP dosimetry converges with the physics-based choice within 2-day p.i., the clinically driven approach offers an alternative and complementary strategy for dosimetry development and may facilitate its translation into clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00259-026-07936-w","type":"journal-article","created":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T06:40:20Z","timestamp":1781332820000},"page":"6461-6472","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Outcome-driven dosimetry optimization for [177Lu]Lu-PSMA-617 radiopharmaceutical therapy: proof of concept on single time point dosimetry optimization"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8940-4727","authenticated-orcid":false,"given":"Jiaxi","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Seifert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos Vinicius","family":"Gomes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yizhou","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yibin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Warissara","family":"Jutidamrongphan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michelle","family":"Amon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiahui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Axel","family":"Rominger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Afshar-Ormieh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kuangyu","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,13]]},"reference":[{"issue":"11","key":"7936_CR1","doi-asserted-by":"publisher","first-page":"3631","DOI":"10.1088\/0031-9155\/58\/11\/3631","volume":"58","author":"L Cheng","year":"2013","unstructured":"Cheng L, Hobbs RF, Segars PW, Sgouros G, Frey EC. 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