Evidence map›Paper›PMID 29218271›Full record

ReviewTranslational lung cancer research2017

Magnetic resonance imaging in precision radiation therapy for lung cancer.

Hannah Bainbridge, Ahmed Salem, Rob H N Tijssen, Michael Dubec, Andreas Wetscherek, Corinne Van Es, Jose Belderbos, Corinne Faivre-Finn, Fiona McDonald, lung tumour site group of the international Atlantic MR-Linac Consortium

Open access · hybridAbstract readReview
In one paragraph

Review in Translational lung cancer research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
10.5field-weighted citation impact, top 1% 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

33 citing papers in PubMed, 69 citations in OpenAlex.

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  11. Correlation of KJournal for immunotherapy of cancer · 2024
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  16. Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2021
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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

10 authors at 6 institutions in 2 countries.

Hannah BainbridgeThe Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, UK.
Ahmed SalemThe University of Manchester and The Christie NHS Foundation Trust, Manchester, UK.
Rob H N TijssenThe University Medical Center Utrecht, Utrecht, the Netherlands.
Michael DubecThe University of Manchester and The Christie NHS Foundation Trust, Manchester, UK.
Andreas WetscherekThe Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, UK.
Corinne Van EsThe University Medical Center Utrecht, Utrecht, the Netherlands.
Jose BelderbosThe Netherlands Cancer Institute and The Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands.
Corinne Faivre-FinnThe University of Manchester and The Christie NHS Foundation Trust, Manchester, UK.
Fiona McDonaldThe Institute of Cancer Research and The Royal Marsden Hospital NHS Foundation Trust, London, UK.
lung tumour site group of the international Atlantic MR-Linac Consortium
Institute of Cancer Research · GBThe Christie NHS Foundation Trust · GBUniversity Medical Center Utrecht · NLRoyal Marsden Hospital · GBThe Netherlands Cancer Institute · NLUniversity of Manchester · GB

Funding

Cancer Research UK 19278Cancer Research UK 19727Cancer Research UK 19908Cancer Research UK 20465
6 · The paper itself

Abstract

Radiotherapy remains the cornerstone of curative treatment for inoperable locally advanced lung cancer, given concomitantly with platinum-based chemotherapy. With poor overall survival, research efforts continue to explore whether integration of advanced radiation techniques will assist safe treatment intensification with the potential for improving outcomes. One advance is the integration of magnetic resonance imaging (MRI) in the treatment pathway, providing anatomical and functional information with excellent soft tissue contrast without exposure of the patient to radiation. MRI may complement or improve the diagnostic staging accuracy of F-18 fluorodeoxyglucose position emission tomography and computerized tomography imaging, particularly in assessing local tumour invasion and is also effective for identification of nodal and distant metastatic disease. Incorporating anatomical MRI sequences into lung radiotherapy treatment planning is a novel application and may improve target volume and organs at risk delineation reproducibility. Furthermore, functional MRI may facilitate dose painting for heterogeneous target volumes and prediction of normal tissue toxicity to guide adaptive strategies. MRI sequences are rapidly developing and although the issue of intra-thoracic motion has historically hindered the quality of MRI due to the effect of motion, progress is being made in this field. Four-dimensional MRI has the potential to complement or supersede 4D CT and 4D F-18-FDG PET, by providing superior spatial resolution. A number of MR-guided radiotherapy delivery units are now available, combining a radiotherapy delivery machine (linear accelerator or cobalt-60 unit) with MRI at varying magnetic field strengths. This novel hybrid technology is evolving with many technical challenges to overcome. It is anticipated that the clinical benefits of MR-guided radiotherapy will be derived from the ability to adapt treatment on the fly for each fraction and in real-time, using 'beam-on' imaging. The lung tumour site group of the Atlantic MR-Linac consortium is working to generate a challenging MR-guided adaptive workflow for multi-institution treatment intensification trials in this patient group.

Indexed as

Lung cancermagnetic resonance imaging (MRI)MR-Linacradiotherapy

Identifiers

PMID29218271
PMCPMC5709138
OpenAlexW2761721704

What OpenQuestion holds

Textmetadata
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.