Physics & Spacearticle2026-08-10

Technical note: reconstructing dose distributions from manually planned electron boosts in breast radiotherapy

Open access0 citations

Abstract

Purpose In breast radiotherapy, delivery of manually-calculated electron boosts limits retrospective dose–response analyses as dose distribution is unavailable. This work evaluates the feasibility of reconstructing dose distributions from manually planned electron boosts in breast-conserving radiotherapy. Methods Only 72 out of 198 breast cancer patients had complete stored dose distributions from sequential electron boosts in the REQUITE study. Arbitrary data from 70/72 patients were used to develop and validate dose reconstruction method. Twenty patients were used to determine optimal parameters for Monte-Carlo-based (MC) electron dose reconstruction on RayStation (v.11B-R), considering CT-calibration curve, MC-history number, andcalculation grid resolution. Remaining 50 patients were used to quantify dose reconstruction accuracy. The similarity between reconstructed and stored dose was evaluated using 3D-gamma index and dosimetric parameters extracted from breast and tumour bed contours. Dose difference location was evaluated using dose-location histogram. Results Calculation grid resolution significantly impacted electron dose distribution ( p < 0.01), where the finest grid (0.15 cm) showed highest similarity to stored doses. CT-calibration curve and MC-history number had a negligible influence on dose reconstruction. Dosimetric difference between reconstructed and stored doses was < 1 Gy for breast and tumour bed. Reconstructed dose was achieved > 90% gamma passing rate in the validation set. However, around 2.5 Gy dose differences were observed at the skin and tissue interface regions. Conclusions Retrospective electron boost dose reconstruction is feasible with acceptable accuracy, and could increase data completeness in large cohort studies. Caution is advised when assessing dose near tissue interface and further validation is needed outside the REQUITE dataset.

// Source

View paper (DOI)Open access versionOpenAlexPhysica MedicaPublished 2026-08-10

Authors: Tanwiwat Jaikuna, Isobel Dawes, Hannah Chamberlin, D. Azria, Jenny Chang-Claude, Maria Carmen De Santis, Sara Gutiérrez‐Enríquez, Marcel van Herk, Peter Hoskin, Léa Kotzki, Gilles Defraene, Maarten Lambrecht, Zoe Lingard, Petra Seibold, Alejandro Seoane, Elena Sperk, Paul Symonds, Chris J. Talbot, Tiziana Rancati, Tim Rattay, Victoria Reyes, Barry S. Rosenstein, Dirk De Ruysscher, Ana Vega, Liv Veldeman, Adam Webb, Catharine West, Eliana Vásquez Osorio, Marianne Aznar

Institutions: Icahn School of Medicine at Mount Sinai, KU Leuven, University of Manchester, Siriraj Hospital, Mahidol University, Inserm, Heidelberg University, University Hospital Heidelberg, Maastricht University, Ghent University Hospital, German Cancer Research Center, Universität Hamburg, University Medical Center Hamburg-Eppendorf, Vall d'Hebron Hospital Universitari, University Medical Centre Mannheim, Instituto de Investigación Sanitaria de Santiago, University of Leicester, Fondazione IRCCS Istituto Nazionale dei Tumori, Centre Hospitalier Universitaire de Nîmes, Maastro Clinic, Centre for Biomedical Network Research on Rare Diseases, The Christie NHS Foundation Trust, Institut de Recherche en Cancérologie de Montpellier, University Cancer Center Hamburg, Vall d'Hebron Institute of Oncology, Fundación Pública Galega de Medicina Xenómica