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Standard treatments such as surgical resection, external beam radiotherapy (EBRT), and chemotherapy often leave residual tumor cells that are resistant to therapy. Local targeted alpha therapy (TAT) with actinium\u2010225 (\n                      <jats:sup>225<\/jats:sup>\n                      Ac) offers high\u2010linear energy transfer (LET) cytotoxicity but is limited by short diffusion range and elevated intratumoral pressure. Convection\u2010enhanced delivery (CED), which applies mild hydraulic pressure to drive bulk flow, may improve radionuclide penetration.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      This study presents a computational model simulating the distribution of unlabeled\n                      <jats:sup>225<\/jats:sup>\n                      Ac delivered via CED. The full\n                      <jats:sup>2<\/jats:sup>\n                      <jats:sup>2<\/jats:sup>\n                      <jats:sup>5<\/jats:sup>\n                      Ac decay chain (parent + daughters) is included in the dosimetric calculations. By characterizing transport dynamics, full decay\u2010chain dose deposition, and resultant clonogenic survival, the model explores both the therapeutic potential and limitations of CED\u2010based alpha therapy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A Python\u2010based CED model was developed incorporating diffusion (diffusion coefficient\u00a0=\u00a01.0 \u00d7 10\n                      <jats:sup>\u22125<\/jats:sup>\n                      \u00a0cm\n                      <jats:sup>2<\/jats:sup>\n                      \/s), bulk flow (velocity in surgical cavity\u00a0=\u00a07.0 \u00d7 10\n                      <jats:sup>\u22125<\/jats:sup>\n                      \u00a0cm\/s; velocity in brain tissue\u00a0=\u00a05.0 \u00d7 10\n                      <jats:sup>\u22125<\/jats:sup>\n                      \u00a0cm\/s), and radioactive decay in a radially symmetric brain geometry. Time\u2010dependent activity profiles were imported into the Monte Carlo simulation platform TOol for PArticle Simulation (TOPAS) to calculate voxel\u2010level dose distributions. Simulated dose per decay was converted to clinically relevant administered activity (MBq) and integrated over 50 days, adjusted for a relative biological effectiveness (RBE) of 5 (sensitivity range: 3, 7, and 10), and applied via the linear\u2010quadratic model with tumor repopulation parameters (tumor cell doubling time\n                      <jats:italic>T<\/jats:italic>\n                      <jats:sub>p<\/jats:sub>\n                      \u00a0=\u00a014\u201350 days; repopulation onset\n                      <jats:italic>T<\/jats:italic>\n                      <jats:sub>k<\/jats:sub>\n                      \u00a0=\u00a00\u201350 days) to a probabilistic GB cell map.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      CED achieved therapeutic doses (\u2265 2\u00a0Gy (RBE)\/ MBq) to \u223c1.43\u00a0cm from injection sites. A five\u2010injection plan delivering a total of 10 MBq reduced the global survival fraction (SF) from 100% (no alpha therapy) to \u223c3.4%, with further reductions to \u223c2.0% and \u223c1.4% at 20 MBq and 30 MBq, respectively. Residual clonogenic tumor cells were mainly located\u00a0&gt;\u00a02\u00a0cm from injection sites. Sensitivity analysis identified injection site placement and total activity as the dominant efficacy factors, whereas varying the RBE had minimal effect. Early tumor repopulation (\n                      <jats:italic>T<\/jats:italic>\n                      <jats:sub>k<\/jats:sub>\n                      \u2264 14 days) substantially reduced control in fast\u2010doubling tumors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      This study supports the feasibility of CED of\n                      <jats:sup>225<\/jats:sup>\n                      Ac for GB, highlighting the need for optimized catheter placement, dosing, and scheduling to address its limited therapeutic radius and tumor repopulation. While results are promising, model assumptions require refinement, and experimental validation is essential to guide clinical translation.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70566","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T05:24:58Z","timestamp":1784697898000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Feasibility of convection\u2010enhanced delivery of unlabeled\n                    <sup>225<\/sup>\n                    Ac for glioblastoma: Transport, dosimetry, and clonogenic survival modeling"],"prefix":"10.1002","volume":"53","author":[{"given":"Maram El","family":"Sabri","sequence":"first","affiliation":[{"name":"College of Health, School of Allied Health and Human Performance Adelaide University  Adelaide South Australia Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leyla","family":"Moghaddasi","sequence":"additional","affiliation":[{"name":"Department of Medical Physics Royal North Shore Hospital  St Leonards New South Wales Australia"},{"name":"College of Science, School of Physics, Chemistry and Earth Sciences Adelaide University  South Australia Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Puthenparampil","family":"Wilson","sequence":"additional","affiliation":[{"name":"College of Science, School of Physics, Chemistry and Earth Sciences Adelaide University  South Australia Australia"},{"name":"Department of Medical Physics Royal Adelaide Hospital  Adelaide South Australia Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank","family":"Saran","sequence":"additional","affiliation":[{"name":"College of Health, School of Allied Health and Human Performance Adelaide University  Adelaide South Australia Australia"},{"name":"Department of Radiation Therapy Auckland City Hospital (Te Toka Tumai)  Auckland New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eva","family":"Bezak","sequence":"additional","affiliation":[{"name":"College of Health, School of Allied Health and Human Performance Adelaide University  Adelaide South Australia Australia"},{"name":"College of Science, School of Physics, Chemistry and Earth Sciences Adelaide University  South Australia Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,21]]},"reference":[{"key":"e_1_2_10_2_1","unstructured":"Australian Institute of Health and Welfare (AIHW).Brain and other central nervous system cancers.Australian Government. 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