Evidence map›Paper›PMID 33735848›Full record

ArticlePhysics in medicine and biology2021

Atlas construction and spatial normalisation to facilitate radiation-induced late effects research in childhood cancer.

Catarina Veiga, Pei Lim, Virginia Marin Anaya, Edward Chandy, Reem Ahmad, Derek D'Souza, Mark Gaze, Syed Moinuddin, Jennifer Gains

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Image-based data mining applies to data collected from children.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2022
    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

9 authors.

Catarina VeigaCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.ORCID 0000-0002-4132-2554
Pei LimDepartment of Oncology, University College London Hospital NHS Foundation Trust, London, United Kingdom.ORCID 0000-0001-9633-7908
Virginia Marin AnayaRadiotherapy Physics Services, University College London Hospital NHS Foundation Trust, London, United Kingdom.ORCID 0000-0001-7844-7759
Edward ChandyCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.ORCID 0000-0002-6117-8692
Reem AhmadCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.ORCID 0000-0001-5529-9802
Derek D'SouzaRadiotherapy Physics Services, University College London Hospital NHS Foundation Trust, London, United Kingdom.ORCID 0000-0002-4393-7683
Mark GazeDepartment of Oncology, University College London Hospital NHS Foundation Trust, London, United Kingdom.ORCID 0000-0002-8344-7902
Syed MoinuddinRadiotherapy, University College London Hospital NHS Foundation Trust, London, United Kingdom.
Jennifer GainsDepartment of Oncology, University College London Hospital NHS Foundation Trust, London, United Kingdom.

Funding

Cancer Research UK C7893/A28990Wellcome Trust
6 · The paper itself

Abstract

Reducing radiation-induced side effects is one of the most important challenges in paediatric cancer treatment. Recently, there has been growing interest in using spatial normalisation to enable voxel-based analysis of radiation-induced toxicities in a variety of patient groups. The need to consider three-dimensional distribution of doses, rather than dose-volume histograms, is desirable but not yet explored in paediatric populations. In this paper, we investigate the feasibility of atlas construction and spatial normalisation in paediatric radiotherapy. We used planning computed tomography (CT) scans from twenty paediatric patients historically treated with craniospinal irradiation to generate a template CT that is suitable for spatial normalisation. This childhood cancer population representative template was constructed using groupwise image registration. An independent set of 53 subjects from a variety of childhood malignancies was then used to assess the quality of the propagation of new subjects to this common reference space using deformable image registration (i.e. spatial normalisation). The method was evaluated in terms of overall image similarity metrics, contour similarity and preservation of dose-volume properties. After spatial normalisation, we report a dice similarity coefficient of 0.95 ± 0.05, 0.85 ± 0.04, 0.96 ± 0.01, 0.91 ± 0.03, 0.83 ± 0.06 and 0.65 ± 0.16 for brain and spinal canal, ocular globes, lungs, liver, kidneys and bladder. We then demonstrated the potential advantages of an atlas-based approach to study the risk of second malignant neoplasms after radiotherapy. Our findings indicate satisfactory mapping between a heterogeneous group of patients and the template CT. The poorest performance was for organs in the abdominal and pelvic region, likely due to respiratory and physiological motion and to the highly deformable nature of abdominal organs. More specialised algorithms should be explored in the future to improve mapping in these regions. This study is the first step toward voxel-based analysis in radiation-induced toxicities following paediatric radiotherapy.

Indexed as

NeoplasmsRadiotherapy Planning, Computer-AssistedAlgorithmsChildHumansPelvisTomography, X-Ray Computedanatomical atlaschildhood cancercomputed tomographyimage registrationradiotherapyspatial normalisation

Identifiers

PMID33735848
PMCPMC8112163

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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.