Evidence map›Paper›PMID 28225485›Full record

ArticleMedicine2017

Magnetic resonance (MR) imaging for tumor staging and definition of tumor volumes on radiation treatment planning in nonsmall cell lung cancer: A prospective radiographic cohort study of single center clinical outcome.

Dan Zhao, Qiaoqiao Hu, Liping Qi, Juan Wang, Hao Wu, Guangying Zhu, Huiming Yu

Open access · goldAbstract readComparative Study
In one paragraph

Article in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

7 authors at 1 institution in 3 countries.

Dan ZhaoKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology Department of Radiology, Peking University Cancer Hospital & Institute, Beijing, China.
Qiaoqiao Hu
Liping Qi
Juan Wang
Hao Wu
Guangying Zhu
Huiming Yu
Itron (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigate the impact of magnetic resonance (MR) on the staging and radiotherapy planning for patients with nonsmall cell lung cancer (NSCLC).A total of 24 patients with NSCLC underwent MRI, which was fused with radiotherapy planning CT using rigid registration. Gross tumor volume (GTV) was delineated not only according to CT image alone (GTVCT), but also based on both CT and MR image (GTVCT/MR). For each patient, 2 conformal treatment plans were made according to GTVCT and GTVCT/MR, respectively. Dose-volume histograms (DVH) for lesion and normal organs were generated using both GTVCT and GTVCT/MR treatment plans. All patients were irradiated according to GTVCT/MR plan.Median volume of the GTVCT/MR and GTVCT were 105.42 cm and 124.45 cm, respectively, and the mean value of GTVCT/MR was significantly smaller than that of GTVCT (145.71 ± 145.04 vs 174.30 ± 150.34, P < 0.01). Clinical stage was modified in 9 patients (37.5%). The objective response rate (ORR) was 83.3% and the l-year overall survival (OS) was 87.5%.MR is a useful tool in radiotherapy treatment planning for NSCLC, which improves the definition of tumor volume, reduces organs at risk dose and does not increase the local recurrence rate.

Indexed as

Neoplasm StagingTumor BurdenAdenocarcinomaAdenocarcinoma of LungCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellFemaleFollow-Up StudiesHumansLungLung NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedPilot ProjectsProspective Studies

Identifiers

PMID28225485
PMCPMC5569433
OpenAlexW2590840552

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.