Evidence map›Paper›PMID 40239820›Full record

ArticleInternational journal of radiation oncology, biology, physics2025

Deformable Image Registration Uncertainty-Encompassing Dose Accumulation for Adaptive Radiation Therapy.

Sebastian Meyer, Yu-Chi Hu, Andreas Rimner, James Mechalakos, Laura Cerviño, Pengpeng Zhang

Abstract read
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. First dosimetric evaluation of deformable dose accumulation in human individuals.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026
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  2. Radiological physics and technology · 2026
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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.

Sebastian MeyerDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. Electronic address: meyers4@mskcc.org.
Yu-Chi HuDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Andreas RimnerDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York; Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, German Cancer Consortium (DKTK), Partner Site DKTK-Freiburg, Freiburg, Germany.
James MechalakosDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Laura CerviñoDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
Pengpeng ZhangDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

purposeDeformable image registration (DIR) represents an inherently ill-posed problem, and its quality highly depends on the algorithm and user input, which can severely affect its applications in adaptive radiation therapy. We propose an automated framework for integrating DIR uncertainty into dose accumulation. METHODS AND MATERIALS: A hyperparameter perturbation approach was applied to estimate an ensemble of deformation vector fields for a given computed tomography (CT) to cone beam CT (CBCT) DIR. For each voxel, a principal component analysis was performed on the distribution of homologous points to construct voxel-specific DIR uncertainty confidence ellipsoids. During the resampling process for dose mapping, the complete dose within each ellipsoid was evaluated via interpolation to estimate the upper and lower dose limits for the particular voxel. We applied the proposed framework in a retrospective dose accumulation study of 20 patients with lung cancer who underwent image guided radiation therapy with weekly CBCTs.

resultsThe average computational time was around 30 minutes, making the approach clinically feasible for automated offline evaluations. The uncertainty (ie, largest ellipsoid semiaxis length) for the fifth week CBCT DIR was 3.8 ± 1.8, 2.5 ± 0.7, 1.5 ± 0.4, 3.2 ± 1.3, and 4.5 ± 1.8 mm for the gross tumor volume, esophagus, spinal cord, lungs, and heart, respectively. Confidence ellipsoids were markedly elongated, with the largest semiaxis 5.5 and 2.5 times longer than the other axes. The dosimetric uncertainties were mainly within 4 Gy but exhibited significant spatial variation because of the interplay between dose gradient and DIR uncertainty. When DIR uncertainty was considered in dose accumulation, 3 cases exceeded institutional limits for dose-volume histogram metrics, highlighting the importance of considering the inherent uncertainty of DIR.

conclusionsThis framework has the potential to facilitate the clinical implementation of dose accumulation, which can improve clinical decision-making in adaptive radiation therapy and provide more personalized radiation therapy treatments.

Indexed as

Cone-Beam Computed TomographyLung NeoplasmsRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-AssistedAlgorithmsHumansOrgans at RiskRadiotherapy DosageRetrospective StudiesUncertainty

Identifiers

PMID40239820
PMCPMC12202161

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Registered trials

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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.