Evidence map›Paper›PMID 28651599›Full record

Trial reportRadiation oncology (London, England)2017

Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer.

Hesheng Wang, Hersh Chandarana, Kai Tobias Block, Thomas Vahle, Matthias Fenchel, Indra J Das

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Radiation oncology (London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Quality evaluation of synthetic CT using a gamma analysis for prostate cancer MR-only radiotherapy.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2025
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Role and future of MRI in radiation oncology.The British journal of radiology · 2019
    Review
  20. Emerging role of MRI in radiation therapy.Journal of magnetic resonance imaging : JMRI · 2018
    Review
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 at 3 institutions in 2 countries.

Hesheng WangDepartment of Radiation Oncology, New York University School of Medicine, Langone Medical Center, New York, NY, USA. wangh15@nyumc.org.ORCID http://orcid.org/0000-0003-2313-1823
Hersh ChandaranaBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA.
Kai Tobias BlockBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA.
Thomas VahleBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA.
Matthias FenchelSiemens Healthcare GmbH, Erlangen, Germany.
Indra J DasDepartment of Radiation Oncology, New York University School of Medicine, Langone Medical Center, New York, NY, USA.
New York University · USNYU Langone Health · USSiemens Healthineers (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInterest in MR-only treatment planning for radiation therapy is growing rapidly with the emergence of integrated MRI/linear accelerator technology. The purpose of this study was to evaluate the feasibility of using synthetic CT images generated from conventional Dixon-based MRI scans for radiation treatment planning of lung cancer.

methodsEleven patients who underwent whole-body PET/MR imaging following a PET/CT exam were randomly selected from an ongoing prospective IRB-approved study. Attenuation maps derived from the Dixon MR Images and atlas-based method was used to create CT data (synCT). Treatment planning for radiation treatment of lung cancer was optimized on the synCT and subsequently copied to the registered CT (planCT) for dose calculation. Planning target volumes (PTVs) with three sizes and four different locations in the lung were planned for irradiation. The dose-volume metrics comparison and 3D gamma analysis were performed to assess agreement between the synCT and CT calculated dose distributions.

resultsMean differences between PTV doses on synCT and CT across all the plans were -0.1% ± 0.4%, 0.1% ± 0.5%, and 0.4% ± 0.5% for D95, D98 and D100, respectively. Difference in dose between the two datasets for organs at risk (OARs) had average differences of -0.14 ± 0.07 Gy, 0.0% ± 0.1%, and -0.1% ± 0.2% for maximum spinal cord, lung V20, and heart V40 respectively. In patient groups based on tumor size and location, no significant differences were observed in the PTV and OARs dose-volume metrics (p > 0.05), except for the maximum spinal-cord dose when the target volumes were located at the lung apex (p = 0.001). Gamma analysis revealed a pass rate of 99.3% ± 1.1% for 2%/2 mm (dose difference/distance to agreement) acceptance criteria in every plan.

conclusionsThe synCT generated from Dixon-based MRI allows for dose calculation of comparable accuracy to the standard CT for lung cancer treatment planning. The dosimetric agreement between synCT and CT calculated doses warrants further development of a MR-only workflow for radiotherapy of lung cancer.

Indexed as

AlgorithmsAdultAgedFeasibility StudiesFemaleFollow-Up StudiesHumansLung NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedPositron Emission Tomography Computed TomographyPrognosisProspective StudiesRadiotherapy DosageRadiotherapy, Intensity-ModulatedLung cancerMR-only radiotherapyRadiotherapy treatment planningSynthetic CT

Identifiers

PMID28651599
PMCPMC5485621
OpenAlexW2630100750

What OpenQuestion holds

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LicenceCC BY
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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.