Evidence map›Paper›PMID 36063983›Full record

ArticleRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology2022

Development and validation of a population-based anatomical colorectal model for radiation dosimetry in late effects studies of survivors of childhood cancer.

Constance A Owens, Bastien Rigaud, Ethan B Ludmir, Aashish C Gupta, Suman Shrestha, Arnold C Paulino, Susan A Smith, Christine B Peterson, Stephen F Kry, Choonsik Lee and 4 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. 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

14 authors at 5 institutions in 1 country.

Constance A OwensThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Graduate Program in Medical Physics, Houston, TX, USA. Electronic address: caowens@mdanderson.org.
Bastien RigaudThe University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX, USA.
Ethan B LudmirThe University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Houston, TX, USA; The University of Texas MD Anderson Cancer Center, Department of Biostatistics, Houston, TX, USA.
Aashish C GuptaThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Graduate Program in Medical Physics, Houston, TX, USA.
Suman ShresthaThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Graduate Program in Medical Physics, Houston, TX, USA.
Arnold C PaulinoThe University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Houston, TX, USA.
Susan A SmithThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA.
Christine B PetersonThe University of Texas MD Anderson Cancer Center, Department of Biostatistics, Houston, TX, USA.
Stephen F KryThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Graduate Program in Medical Physics, Houston, TX, USA.
Choonsik LeeNational Cancer Institute, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA.
Tara O HendersonThe University of Chicago, Department of Pediatrics, Chicago, IL, USA.
Gregory T ArmstrongSt. Jude Children's Research Hospital, Department of Epidemiology and Cancer Control, Memphis, TN, USA.
Kristy K BrockThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA; The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, Houston, TX, USA.
Rebecca M HowellThe University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, TX, USA; MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Graduate Program in Medical Physics, Houston, TX, USA. Electronic address: rhowell@mdanderson.org.
The University of Texas MD Anderson Cancer Center · USThe University of Texas Health Science Center at Houston · USDivision of Cancer Epidemiology and GeneticsSt. Jude Children's Research Hospital · USUniversity of Chicago · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Viral Vector Technology (VVTSR)P30CA021765 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI CHARLES ROBERTS · 1985 to 2026
$166.9M
Mach-LETSGO: Machine-LEarning of Treatment, Survey, and Genetics towards Obtaining Correct Classification of Chronic Conditions in Adult Survivors in the Childhood Cancer Survivor Study - CCSS SupplU24CA055727 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Gregory Armstrong · 1999 to 2026
$96.7M
NCI NIH HHS P30 CA016672NCI NIH HHS P30 CA021765NCI NIH HHS U24 CA055727
6 · The paper itself

Abstract

purposeThe purposes of this study were to develop and integrate a colorectal model that incorporates anatomical variations of pediatric patients into the age-scalable MD Anderson Late Effects (MDA-LE) computational phantom, and validate the model for pediatric radiation therapy (RT) dose reconstructions.

methodsColorectal contours were manually derived from whole-body non-contrast computed tomography (CT) scans of 114 pediatric patients (age range: 2.1-21.6 years, 74 males, 40 females). One contour was used for an anatomical template, 103 for training and 10 for testing. Training contours were used to create a colorectal principal component analysis (PCA)-based statistical shape model (SSM) to extract the population's dominant deformations. The SSM was integrated into the MDA-LE phantom. Geometric accuracy was assessed between patient-specific and SSM contours using several overlap metrics. Two alternative colorectal shapes were generated using the first 17 dominant modes of the PCA-based SSM. Dosimetric accuracy was assessed by comparing colorectal doses from test patients' CT-based RT plans (ground truth) with reconstructed doses for the mean and two alternative models in age-matched MDA-LE phantoms.

resultsWhen using all 103 PCA modes, the mean (min-max) Dice similarity coefficient, distance-to-agreement and Hausdorff distance between the patient-specific and reconstructed contours for the test patients were 0.89 (0.85-0.91), 2.1 mm (1.7-3.0), and 8.6 mm (5.7-14.3), respectively. The average percent difference between reconstructed and ground truth mean and maximum colorectal doses for the mean (alternative 1, 2) model were 6.3% (8.1%, 6.1%) and 4.4% (4.3%, 4.7%), respectively.

conclusionsWe developed, validated and integrated a colorectal PCA-based SSM into the MDA-LE phantom and demonstrated its dosimetric performance for accurate pediatric RT dose reconstruction.

Indexed as

Adult Survivors of Child Adverse EventsCancer SurvivorsColorectal NeoplasmsAdolescentAdultChildChild, PreschoolFemaleHumansMalePhantoms, ImagingRadiometryTomography, X-Ray ComputedYoung AdultChildhood cancerComputational phantomDose reconstructionLate effectsRadiation-related late effectsRadiation therapy

Identifiers

PMID36063983
PMCPMC9845018
OpenAlexW4294631184

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.