Evidence map›Paper›PMID 41451147›Full record

ArticlePhysics and imaging in radiation oncology2025

Individualised dose mapping uncertainty estimation in the reirradiation setting.

Chelmis Muthoni Thiong'o, Marcel van Herk, Kathryn Banfill, Clara Chan, Catherine Harris, Matthew Lowe, Tom Marchant, Iskandar Mohamed, Golnoosh Motamedi-Ghahfarokhi, David Thomson and 2 more

Abstract read
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Article in Physics and imaging in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Chelmis Muthoni Thiong'oDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Marcel van HerkDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Kathryn BanfillDepartment of Clinical Oncology, The Christie Hospitals NHS Foundation Trust, Manchester, UK.
Clara ChanDepartment of Clinical Oncology, The Christie Hospitals NHS Foundation Trust, Manchester, UK.
Catherine HarrisDepartment of Medical Physics and Engineering, The Christie Hospitals NHS Foundation Trust, Manchester, UK.
Matthew LoweDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Tom MarchantDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Iskandar MohamedDepartment of Clinical Oncology, The Christie Hospitals NHS Foundation Trust, Manchester, UK.
Golnoosh Motamedi-GhahfarokhiDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
David ThomsonDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Ane AppeltLeeds Institute of Medical Research, University of Leeds, Leeds, UK.
Eliana Vasquez OsorioDivision of Cancer Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: Deformable image registration (DIR) allows assessing radiation doses of previous treatment courses in reirradiation planning scans. However, DIR can introduce uncertainties in dose mapping. Estimating these uncertainties for individual patients remains a key challenge. We developed an individualised approach to estimate uncertainties in dose mapping using a commercially available treatment planning system. Materials and methods: For 54 patients who underwent reirradiation (27 head and neck, H&N, and 27 lung cases), we performed 16 DIRs per patient. We assessed each DIR geometrically using the mean distance to agreement (mDTA) between mapped contours and the corresponding structures of 30 to 34 organs at risk (OARs). We then estimated dose mapping uncertainties for structures where DIR resulted in plausible registrations, defined as mDTA ≤ 0.3 cm. We calculated the uncertainty of dose-volume-histogram estimates (mean and D0.1 cm Results: DIR resulted in plausible mappings for both patient cohorts' OARs, ranging between 78.6 % and 88.2 %, varying between patients and OARs. Mean dose uncertainties ranged between 0 Gy and 0.43 Gy, while larger differences were observed for D0.1 cm3, between 0 Gy and 0.78 Gy. As expected, large voxel-wise uncertainties were in regions of steep dose gradients. Performance between registration sets was similar. Conclusion: We developed a method to estimate dose mapping uncertainties with integrated quality control for reirradiation. Differences between patients were observed, justifying the need for individualised DIR assessment. Few registrations were a pragmatic approach.

Indexed as

Deformable registrationDose mapping uncertaintiesHead and neck cancerLung cancerReirradiation

Identifiers

PMID41451147
PMCPMC12732311

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