Evidence map›Paper›PMID 35440773›Full record

ReviewNature reviews. Clinical oncology2022

Integrated MRI-guided radiotherapy - opportunities and challenges.

Paul J Keall, Caterina Brighi, Carri Glide-Hurst, Gary Liney, Paul Z Y Liu, Suzanne Lydiard, Chiara Paganelli, Trang Pham, Shanshan Shan, Alison C Tree and 3 more

Open access · greenAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Clinical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
40.2field-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

73 citing papers in PubMed, 157 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

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

13 authors at 7 institutions in 5 countries.

Paul J KeallACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia. paul.keall@sydney.edu.au.ORCID 0000-0003-4803-6507
Caterina BrighiACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
Carri Glide-HurstDepartment of Human Oncology, University of Wisconsin, Madison, WI, USA.
Gary LineyIngham Institute of Applied Medical Research, Sydney, New South Wales, Australia.
Paul Z Y LiuACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
Suzanne LydiardACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
Chiara PaganelliDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.
Trang PhamFaculty of Medicine and Health, The University of New South Wales, Sydney, New South Wales, Australia.ORCID 0000-0002-7759-8296
Shanshan ShanACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
Alison C TreeThe Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, London, UK.ORCID 0000-0002-5033-424X
Uulke A van der HeideDepartment of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands.
David E J WaddingtonACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-7017-1556
Brendan WhelanACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
The University of Sydney · AUIngham Institute · AUPolitecnico di Milano · ITRoyal Marsden NHS Foundation Trust · GBThe Netherlands Cancer Institute · NLUniversity of Wisconsin–Madison · USUNSW Sydney · AU

Funding

Cancer Research UK 28284Cancer Research UK C33589/A28284Cancer Research UK C7224/A28724Department of Health
6 · The paper itself

Abstract

MRI can help to categorize tissues as malignant or non-malignant both anatomically and functionally, with a high level of spatial and temporal resolution. This non-invasive imaging modality has been integrated with radiotherapy in devices that can differentially target the most aggressive and resistant regions of tumours. The past decade has seen the clinical deployment of treatment devices that combine imaging with targeted irradiation, making the aspiration of integrated MRI-guided radiotherapy (MRIgRT) a reality. The two main clinical drivers for the adoption of MRIgRT are the ability to image anatomical changes that occur before and during treatment in order to adapt the treatment approach, and to image and target the biological features of each tumour. Using motion management and biological targeting, the radiation dose delivered to the tumour can be adjusted during treatment to improve the probability of tumour control, while simultaneously reducing the radiation delivered to non-malignant tissues, thereby reducing the risk of treatment-related toxicities. The benefits of this approach are expected to increase survival and quality of life. In this Review, we describe the current state of MRIgRT, and the opportunities and challenges of this new radiotherapy approach.

Indexed as

NeoplasmsRadiotherapy, Image-GuidedHumansMagnetic Resonance ImagingQuality of LifeRadiotherapy Planning, Computer-Assisted

Identifiers

PMID35440773
OpenAlexW4224284961

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.