Evidence map›Paper›PMID 27300649›Full record

ArticleLa Radiologia medica2016

Three-dimensional surface imaging for detection of intra-fraction setup variations during radiotherapy of pelvic tumors.

Giuseppina Apicella, Gianfranco Loi, Sara Torrente, Silvia Crespi, Debora Beldì, Marco Brambilla, Marco Krengli

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Article in La Radiologia medica, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

8 citing papers in PubMed.

  1. Article
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  6. Review
  7. Recent advances in radiation oncology.Ecancermedicalscience · 2017
    Review
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Giuseppina ApicellaDivision of Radiotherapy, University Hospital "Maggiore della Carità", Novara, Italy.
Gianfranco LoiMedical Physics, University Hospital "Maggiore della Carità", Novara, Italy.
Sara TorrenteDivision of Radiotherapy, University Hospital "Maggiore della Carità", Novara, Italy.
Silvia CrespiDivision of Radiotherapy, University Hospital "Maggiore della Carità", Novara, Italy.
Debora BeldìDivision of Radiotherapy, University Hospital "Maggiore della Carità", Novara, Italy.
Marco BrambillaMedical Physics, University Hospital "Maggiore della Carità", Novara, Italy.
Marco KrengliDivision of Radiotherapy, University Hospital "Maggiore della Carità", Novara, Italy. krengli@med.unipmn.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSurface-based image guided radiotherapy (IGRT) allows positioning and/or monitoring patients in 3 dimensions (3D), without the use of ionizing radiation. In this study, we report on intra-fraction motion measured by acquisition of multiple images of 3D body surfaces. MATERIALS AND

methodsTwenty-nine patients treated for pelvic tumors were enrolled. Setup variations (SV) through three consecutive body surfaces acquired by the optical IGRT system Align-RT (Vision-RT, London, UK) were analyzed before, during and at the end of treatment delivery. Displacements along the main axes (X, Y and Z) from initial (I) to mid-treatment (MT) and final (F) acquisitions were recorded. Time and direction of SV were assessed.

resultsA total of 6272 images from 792 fractions of 29 patients were available. The main source of misalignment was between I and MT acquisition (p < 0.001). The dominant SV direction was the vertical one (Z axis), with mean SV of -1.20 ± 0.06 mm and -1.55 ± 0.06 mm for I-MT and I-F acquisitions, respectively. The Y mean components of SV were, respectively, -0.95 ± 0.10 mm and -1.0 ± 0.10 for I-MT and I-F acquisitions, while the X deviations were 0.07 ± 0.08 mm for I-MT and 0.26 ± 0.08 mm I-F.

conclusionThree-D surface imaging for patient setup monitoring highlighted remarkable mobility of patients during RT session, especially in the anterior-posterior direction (Z axis). The largest magnitude in patient movements occurred during the first part of delivery. These findings suggest that the initial setup control cannot not to be sufficient to guarantee treatment reproducibility, especially for long-lasting RT treatments.

Indexed as

AgedAged, 80 and overFemaleGenital Neoplasms, FemaleGenital Neoplasms, MaleHumansMaleMiddle AgedPatient PositioningQuality Assurance, Health CareRadiotherapy, Image-GuidedRadiotherapy Setup ErrorsReproducibility of ResultsIGRTIntra-fractionOrgan motionRadiotherapySetupSurface imaging

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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.