{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T08:18:45Z","timestamp":1787559525269,"version":"build-2736575974"},"reference-count":48,"publisher":"IOP Publishing","issue":"16","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2026,8,28]]},"abstract":"Abstract<\/jats:title>\n \n Objective.<\/jats:italic>\n Develop a probabilistic framework that maps high-dose-rate brachytherapy dose and dose-gradient magnitude onto MR-informed, TRUS-guided prostate core-needle biopsies, explicitly propagating millimetre-scale localization uncertainty.\n Approach.<\/jats:italic>\n We reconstructed two representative second-fraction biopsy cores, voxelized them at\n \n \n \n <\/jats:tex-math>\n \n \n 1<\/mml:mn>\n \n \n \n mm<\/mml:mi>\n <\/mml:mrow>\n 3<\/mml:mn>\n <\/mml:msup>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n , and registered them to the clinical\n \n \n \n <\/jats:tex-math>\n \n \n 1<\/mml:mn>\n \u00d7<\/mml:mo>\n 1<\/mml:mn>\n \u00d7<\/mml:mo>\n 0.5<\/mml:mn>\n \n \n \n mm<\/mml:mi>\n <\/mml:mrow>\n 3<\/mml:mn>\n <\/mml:msup>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n dose lattice. Spatial uncertainty from registration, segmentation, and biopsy length mismatch was modelled as\n \n \n \n <\/jats:tex-math>\n \n \n \n N<\/mml:mi>\n T<\/mml:mi>\n <\/mml:msub>\n =<\/mml:mo>\n 10<\/mml:mn>\n \u2009<\/mml:mtext>\n 000<\/mml:mn>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n rigid translations sampled from\n \n \n \n <\/jats:tex-math>\n \n \n \n N<\/mml:mi>\n <\/mml:mrow>\n (<\/mml:mo>\n \n 0<\/mml:mn>\n <\/mml:mrow>\n ,<\/mml:mo>\n \n \u03c3<\/mml:mi>\n 2<\/mml:mn>\n <\/mml:msup>\n \n I<\/mml:mi>\n <\/mml:mrow>\n )<\/mml:mo>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n with\n \n \n \n <\/jats:tex-math>\n \n \n \u03c3<\/mml:mi>\n =<\/mml:mo>\n 1.25<\/mml:mn>\n \n \n mm<\/mml:mi>\n <\/mml:mrow>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n , plus an independent axial shift along the core. For each voxel we obtained Monte Carlo distributions of dose\n \n \n \n <\/jats:tex-math>\n \n \n D<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n and dose-gradient magnitude\n \n \n \n <\/jats:tex-math>\n \n \n G<\/mml:mi>\n =<\/mml:mo>\n \u2016<\/mml:mo>\n \u2207<\/mml:mi>\n D<\/mml:mi>\n \u2016<\/mml:mo>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n , distributional DVHs,\n \n \n \n <\/jats:tex-math>\n \n \n \u0394<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n -metrics comparing nominal to probability-weighted summaries, and spatial summaries including axial length-scale dose-difference curves and voxel-pair contrast maps.\n Main results.<\/jats:italic>\n Two exemplar second-fraction cores from a representative patient, selected as mechanistic exemplars of steep- versus low-gradient dose environments, showed right-skewed trialwise dose distributions in high-gradient segments, with widened uncertainty bands and larger nominal-summary discrepancies in the steep-gradient core. In that core, the typical per-trial perturbation in mapped dose was substantially larger (median\n \n \n \n <\/jats:tex-math>\n \n \n |<\/mml:mo>\n \u0394<\/mml:mi>\n \n D<\/mml:mi>\n \n b<\/mml:mi>\n ,<\/mml:mo>\n v<\/mml:mi>\n ,<\/mml:mo>\n t<\/mml:mi>\n <\/mml:mrow>\n <\/mml:msub>\n \n |<\/mml:mo>\n <\/mml:mrow>\n \u2248<\/mml:mo>\n 7<\/mml:mn>\n \n Gy<\/mml:mtext>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n versus\n \n \n \n <\/jats:tex-math>\n \n \n \u2248<\/mml:mo>\n 1<\/mml:mn>\n \n Gy<\/mml:mtext>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n in the low-gradient core). Length-scale curves increased with axial separation and then plateaued, indicating centimetre-scale along-core spatial structure in these exemplars; voxel-pair maps highlighted both near-uniform subsegments and voxel pairs achieving prescribed inter-voxel contrast.\n Significance.<\/jats:italic>\n The framework converts biopsy localization uncertainty into probability-weighted voxel- and core-level dose descriptors and interpretable\n \n \n \n <\/jats:tex-math>\n \n \n \u0394<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n -metrics that separate nominal bias from propagated variability. These estimands can be used to assess feasibility for dose-biology studies, guide selection or pairing of subsegments with specified homogeneity or contrast, and provide dose and gradient covariates for Raman, biochemical, and genomic assays, including settings where\n ex vivo<\/jats:italic>\n biopsy orientation or integrity is partially lost. Cohort-level dosimetric characterization and robustness analyses are outside the scope of this exemplar-focused paper.\n <\/jats:p>","DOI":"10.1088\/1361-6560\/ae9823","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T13:53:00Z","timestamp":1786456380000},"page":"165017","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Dosimetric analysis along core-needle biopsies in prostate HDR brachytherapy"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8285-6512","authenticated-orcid":true,"given":"Matthew","family":"Muscat","sequence":"first","affiliation":[{"name":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia"},{"name":"BC Cancer, Sindi Ahluwalia Hawkins Centre"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0711-3318","authenticated-orcid":false,"given":"Juanita","family":"Crook","sequence":"additional","affiliation":[{"name":"BC Cancer, Sindi Ahluwalia Hawkins Centre"},{"name":"University of British Columbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0844-2092","authenticated-orcid":true,"given":"Andrew","family":"Jirasek","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6521-5780","authenticated-orcid":false,"given":"Jeffrey","family":"Andrews","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5088-8540","authenticated-orcid":true,"given":"Nathan","family":"Becker","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia"},{"name":"BC Cancer, Sindi Ahluwalia Hawkins Centre"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"pmbae9823bib1","doi-asserted-by":"publisher","first-page":"R1","DOI":"10.1088\/0031-9155\/55\/5\/R01","type":"journal-article","article-title":"Polymer gel dosimetry","volume":"55","author":"Baldock","year":"2010","journal-title":"Phys. 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