Evidence map›Paper›PMID 38077270›Full record

ArticlePhysics and imaging in radiation oncology2023

Functional lung avoidance in radiotherapy using optimisation of biologically effective dose with non-coplanar beam orientations.

James L Bedford, Merina Ahmed

Open access · goldAbstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2023. 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
1.8field-weighted citation impact, top 16% 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. Article
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

James L BedfordThe Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
Merina AhmedThe Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
Royal Marsden NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose: In external beam radiotherapy for non-small cell lung cancer, dose to functioning lung should be minimised to reduce lung morbidity. This study aimed to develop a method for avoiding beam delivery through functional lung and to quantify the possible benefit to the patients. Materials and methods: Twelve patients that were treated as part of a clinical trial of single photon emission computed tomography (SPECT) functional lung avoidance were retrospectively studied. During treatment planning, the dose in the lung was weighted by the relative intensity of the functional image. A single conformal beam was scanned systematically around the planning target volume to find optimum orientations and the resulting map of functional dose variation with gantry and couch angle was used to select five non-coplanar intensity-modulated beams, taking into account directions prohibited due to collision risk. Expected reduction in pneumonitis risk was calculated using a logistic model. Results: The volume of lung irradiated to a functionally weighted dose of 5 Gy was 11.8 % (range 3.5 %-22.0 %) for functional plans, versus 20.9 % (range 4.9 %-33.3 %) for conventional plans ( Conclusions: By seeking the optimum non-coplanar beam orientations, it is possible to reduce dose/volume lung parameters by 10% or more, consistently in all patients, regardless of the pattern of lung perfusion. A prediction model indicates that this will improve radiation-associated lung injury.

Indexed as

CarcinomaEmission-ComputedNon-Small-Cell LungPerfusionRadiation InjuriesRetrospective StudiesSingle-PhotonTomography

Identifiers

PMID38077270
PMCPMC10709084
OpenAlexW4388840291

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.