Evidence map›Paper›PMID 36818005›Full record

ArticleJournal of biomedical physics & engineering2023

Quantification of Lung Tumor Motion and Optimization of Treatment.

Milovan Savanović, Bojan Štrbac, Dražan Jaroš, Mauro Loi, Florence Huguet, Jean-Noël Foulquier

Abstract read
In one paragraph

Article in Journal of biomedical physics & engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

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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

6 citing papers in PubMed.

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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

6 authors.

Milovan SavanovićFaculty of Medicine, University of Paris-Saclay, 94276 Le Kremlin-Bicêtre, France.
Bojan ŠtrbacMATER Private Hospital, Department of Physics, Eccles Street, Dublin 7, Ireland.
Dražan JarošCenter for Radiotherapy, International Medical Centers, Affidea, 78000 Banja Luka, Bosnia, and Herzegovina.
Mauro LoiDepartment of Radiation Oncology, Tenon Hospital, APHP, Sorbonne University, 75020 Paris, France.
Florence HuguetDepartment of Radiation Oncology, Tenon Hospital, APHP, Sorbonne University, 75020 Paris, France.
Jean-Noël FoulquierDepartment of Radiation Oncology, Tenon Hospital, APHP, Sorbonne University, 75020 Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mobility of lung tumors is induced by respiration and causes inadequate dose coverage. Objective: This study quantified lung tumor motion, velocity, and stability for small (≤5 cm) and large (>5 cm) tumors to adapt radiation therapy techniques for lung cancer patients. Material and Methods: In this retrospective study, 70 patients with lung cancer were included that 50 and 20 patients had a small and large gross tumor volume (GTV). To quantify the tumor motion and velocity in the upper lobe (UL) and lower lobe (LL) for the central region (CR) and a peripheral region (PR), the GTV was contoured in all ten respiratory phases, using 4D-CT. Results: The amplitude of tumor motion was greater in the LL, with motion in the superior-inferior (SI) direction compared to the UL, with an elliptical motion for small and large tumors. Tumor motion was greater in the CR, rather than in the PR, by 63% and 49% in the UL compared to 50% and 38% in the LL, for the left and right lung. The maximum tumor velocity for a small GTV was 44.1 mm/s in the LL (CR), decreased to 4 mm/s for both ULs (PR), and a large GTV ranged from 0.4 to 9.4 mm/s. Conclusion: The tumor motion and velocity depend on the tumor localization and the greater motion was in the CR for both lobes due to heart contribution. The tumor velocity and stability can help select the best technique for motion management during radiation therapy.

Indexed as

Four-Dimensional Computed TomographyIntensity-Modulated RadiotherapyLung CancerRadiotherapyStereotactic Body RadiotherapyTumor MotionTumor StabilityTumor Velocity

Identifiers

PMID36818005
PMCPMC9923245

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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.