Evidence map›Paper›PMID 42376805›Full record

Observational studyMedical physics2026

Surface-guided analysis of breast shape changes during postoperative radiotherapy by using a functional map framework.

Pierre Galmiche, Hyewon Seo, Yvan Pin, Philippe Meyer, Georges Noël, Michel De Mathelin

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03801850 (Quantitative Evaluation of the Breast's Morphological Variations During Radiotherapy), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03801850 nacompletednot on this map

Quantitative Evaluation of the Breast's Morphological Variations During Radiotherapy: Monocentric Feasibility Study MorphoBreast3D

TypeinterventionalSponsorCentre Paul StraussRan2018 to 2020Enrolled60ConditionsBreast Cancer Female, Adjuvant RadiotherapyArms3D surface scan
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Pierre GalmicheLaboiratoire ICube, CNRS-University of Strasbourg, Strasbourg, France.
Hyewon SeoLaboiratoire ICube, CNRS-University of Strasbourg, Strasbourg, France.
Yvan PinInstitut Privé de Radiothérapie de Metz (IPRM), Metz, France.
Philippe MeyerLaboiratoire ICube, CNRS-University of Strasbourg, Strasbourg, France.
Georges NoëlLaboiratoire ICube, CNRS-University of Strasbourg, Strasbourg, France.
Michel De MathelinLaboiratoire ICube, CNRS-University of Strasbourg, Strasbourg, France.

Funding

French Ministry of Higher Education and Research
6 · The paper itself

Abstract

backgroundWhile positioning errors during radiotherapy are increasingly well-characterized and accounted for in the Planning Target Volume (PTV), little is known about the shape and volume changes of the breast in the course of radiotherapy. Yet they represent an unknown factor that may impact treatment effectiveness, highlighting the need to analyze inter-fractional breast deformations to enable promising approaches such as patient-specific adaptive irradiation planning. PURPOSE: In this study, we develop a geometric approach to analyze inter-fractional breast deformation throughout the radiotherapy treatment, based on a dataset of 3D surface scans of patients' frontal torso acquired during radiotherapy sessions.

methodsWe used a handheld 3D range scanner to collect surface scans of 22 patients prior to, during, and after radiotherapy sessions following breast-conserving surgery (lumpectomy). We begin by adapting functional map framework to compute inter- and intra-patient nonrigid correspondences. To study shape changes during radiotherapy, we then perform both intrinsic and extrinsic analyses of the collected breast surface shapes, by leveraging the intra- and inter-patient correspondences. These analysis provide complementary insights into how the breast changes over time: The intrinsic analysis evaluates deformation patterns directly on the shape manifolds, enabling the identification of regions exhibiting high conformal (bending) or area distortions (stretching). We also perform extrinsic analysis, where we align surface acquisitions of the treated breast with the CT-derived skin surface to assess pointwise surface displacements and volume changes in the treated area, thereby producing quantitative measures such as displacement amplitudes (in mm) and relative volume changes (in percentage).

resultsThe qualitative shape collection analysis highlight deformations in the contra-lateral breast and armpit areas, along with positioning shifts on the head or abdominal regions. On average, displacements within the treated breast exhibit amplitudes of 1-2 mm across sessions, with higher values observed at the time of the 25th irradiation session. Volume changes, inferred from surface variations, reached up to 10% over the course of treatment, with the majority of values ranging between 2% and 5%.

conclusionsA -based geometric approach has been proposed for analyzing breast shape changes over the course of radiotherapy from surface data acquisitions. Based on a functional map framework, we develop a shape matching specialized for the breast data as well as a shape variability analysis within a unified space. Analysis across multiple patient datasets revealed a wide spectrum of breast changes despite a clinically acceptable quantitative average, demonstrating the power of our method to perform both quantitative and qualitative analysis of deformation patterns both on the individual and group level.

trial registrationThe clinical trial data used in this paper is registered under the ClinicalTrials.gov ID NCT03801850.

Indexed as

BreastBreast NeoplasmsImaging, Three-DimensionalFemaleHumansMastectomy, SegmentalPostoperative PeriodRadiotherapy Planning, Computer-AssistedSurface Propertiesbreast shape changespost‐operative radiotherapyshape analysis

Identifiers

PMID42376805
PMCPMC13316813

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.