Evidence map›Paper›PMID 38631538›Full record

SynthesisInternational journal of radiation oncology, biology, physics2024

Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis.

Julie Midroni, Rohan Salunkhe, Zhihui Liu, Ronald Chow, Gabriel Boldt, David Palma, Douglas Hoover, Yevgeniy Vinogradskiy, Srinivas Raman

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in International journal of radiation oncology, biology, physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

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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

9 authors at 5 institutions in 2 countries.

Julie MidroniTemerty Faculty of Medicine, University of Toronto, Toronto, Canada; Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada.
Rohan SalunkheRadiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
Zhihui LiuBiostatistics, Princess Margaret Cancer Center, Toronto, Canada.
Ronald ChowTemerty Faculty of Medicine, University of Toronto, Toronto, Canada; Radiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; London Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada.
Gabriel BoldtLondon Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada.
David PalmaLondon Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada; Ontario Institute for Cancer Research, Toronto, Canada.
Douglas HooverLondon Regional Cancer Program, London Health Sciences Centre, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada.
Yevgeniy VinogradskiyDepartment of Radiation Oncology, University of Colorado School of Medicine, Aurora, United States of America; Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, United States of America.
Srinivas RamanRadiation Medicine Program, Princess Margaret Cancer Center, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada. Electronic address: srinivas.raman@rmp.uhn.ca.
University of Toronto · CAWestern University · CAOntario Institute for Cancer Research · CAPrincess Margaret Cancer Centre · CAThomas Jefferson University · US

Funding

Development of a Novel Lung Function Imaging Modality for comprehensive management of lung cancerR01CA236857 · NCI · UNIVERSITY OF COLORADO DENVER · PI CASTILLO, EDWARD, CASTILLO, RICHARD · 2020 to 2025
$2.4M
Quantitative Lung Function Imaging to Reduce Toxicity for patients treated with Radiation and ImmunotherapyUG3CA247605 · NCI · THOMAS JEFFERSON UNIVERSITY · PI CASTILLO, EDWARD, CASTILLO, RICHARD · 2021 to 2022
$664k
NCI NIH HHS R01 CA236857NCI NIH HHS UG3 CA247605
6 · The paper itself

Abstract

Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.

Indexed as

LungLung NeoplasmsRadiation PneumonitisRadiotherapy Planning, Computer-AssistedHumansRadiotherapy Dosage

Identifiers

PMID38631538
PMCPMC11580018
OpenAlexW4394824542

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.