Evidence map›Paper›PMID 25477277›Full record

ArticleInternational journal of computer assisted radiology and surgery2015

Improved human observer performance in digital reconstructed radiograph verification in head and neck cancer radiotherapy.

Jared D Sturgeon, John A Cox, Lauren L Mayo, G Brandon Gunn, Lifei Zhang, Peter A Balter, Lei Dong, Musaddiq Awan, Esengul Kocak-Uzel, Abdallah Sherif Radwan Mohamed and 2 more

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Setup uncertainties and PTV margins at different anatomical levels in intensity modulated radiotherapy for nasopharyngeal cancer.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology
    Article
  5. 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

12 authors.

Jared D SturgeonDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
John A CoxDepartment of Radiation Oncology, The University of Texas Medical Branch, Galveston, TX, USA.
Lauren L MayoDepartment of Radiation Oncology, The University of Texas Medical Branch, Galveston, TX, USA.
G Brandon GunnDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
Lifei ZhangDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
Peter A BalterDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
Lei DongScripps Proton Therapy Center, San Diego, CA, USA.
Musaddiq AwanDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
Esengul Kocak-UzelDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
Abdallah Sherif Radwan MohamedDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
David I RosenthalDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA.
Clifton David FullerDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 97, Houston, TX, 77030, USA. cdfuller@mdanderson.org.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Paul Calabresi Clinical Oncology AwardK12CA088084 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI David S. Hong, Scott Kopetz · 2000 to 2026
$14.0M
NCI NIH HHS 5K12 CA088084-14NCI NIH HHS CA016672NCI NIH HHS K12 CA088084NCI NIH HHS L30 CA136381NCI NIH HHS L30 CA136381-02NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

purposeDigitally reconstructed radiographs (DRRs) are routinely used as an a priori reference for setup correction in radiotherapy. The spatial resolution of DRRs may be improved to reduce setup error in fractionated radiotherapy treatment protocols. The influence of finer CT slice thickness reconstruction (STR) and resultant increased resolution DRRs on physician setup accuracy was prospectively evaluated.

methodsFour head and neck patient CT-simulation images were acquired and used to create DRR cohorts by varying STRs at 0.5, 1, 2, 2.5, and 3 mm. DRRs were displaced relative to a fixed isocenter using 0-5 mm random shifts in the three cardinal axes. Physician observers reviewed DRRs of varying STRs and displacements and then aligned reference and test DRRs replicating daily KV imaging workflow. A total of 1,064 images were reviewed by four blinded physicians. Observer errors were analyzed using nonparametric statistics (Friedman's test) to determine whether STR cohorts had detectably different displacement profiles. Post hoc bootstrap resampling was applied to evaluate potential generalizability.

resultsThe observer-based trial revealed a statistically significant difference between cohort means for observer displacement vector error ([Formula: see text]) and for [Formula: see text]-axis [Formula: see text]. Bootstrap analysis suggests a 15% gain in isocenter translational setup error with reduction of STR from 3 mm to [Formula: see text]2 mm, though interobserver variance was a larger feature than STR-associated measurement variance.

conclusionsHigher resolution DRRs generated using finer CT scan STR resulted in improved observer performance at shift detection and could decrease operator-dependent geometric error. Ideally, CT STRs [Formula: see text]2 mm should be utilized for DRR generation in the head and neck.

Indexed as

Radiographic Image Interpretation, Computer-AssistedHead and Neck NeoplasmsHumansRadiotherapy Planning, Computer-AssistedTomography, X-Ray ComputedIGRTImage-guided radiotherapyImage informaticsQuality assuranceSetup error

Identifiers

PMID25477277
PMCPMC4801514

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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.