Evidence map›Paper›PMID 33617034›Full record

ArticleMedical physics2021

Mapping lung ventilation through stress maps derived from biomechanical models of the lung.

Guillaume Cazoulat, James M Balter, Martha M Matuszak, Shruti Jolly, Dawn Owen, Kristy K Brock

Open access · bronzeAbstract read
In one paragraph

Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 13% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
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  5. Article
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  7. Article
  8. Article
  9. Article
  10. Metrics of dose to highly ventilated lung are predictive of radiation-induced pneumonitis in lung cancer patients.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2023
    Article
  11. Review
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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 at 2 institutions in 1 country.

Guillaume CazoulatDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
James M BalterDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Martha M MatuszakDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Shruti JollyDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Dawn OwenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA.
Kristy K BrockDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
University of Michigan–Ann Arbor · USThe University of Texas MD Anderson Cancer Center · US

Funding

TREATMENT VERIFICATION AND TREATMENT PLAN REFINEMENTP01CA059827 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KESSLER, MARC LEWIS, LAWRENCE, THEODORE S · 1993 to 2018
$37.9M
HHS | National Institutes of Health (NIH) P01CA059827NCI NIH HHS P01 CA059827
6 · The paper itself

Abstract

purposeMost existing computed tomography (CT)-ventilation imaging techniques are based on deformable image registration (DIR) of different respiratory phases of a four-dimensonal CT (4DCT) scan of the lung, followed by the quantification of local breathing-induced changes in Hounsfield Units (HU) or volume. To date, only moderate correlations have been reported between these CT-ventilation metrics and standard ventilation imaging modalities for adaptive lung radiation therapy. This study evaluates the use of stress maps derived from biomechanical model-based DIR as an alternative CT-ventilation metric. MATERIALS AND

methodsSix patients treated for lung cancer with conventional radiation therapy were retrospectively analyzed. For each patient, a 4DCT scan and Tc-99m SPECT-V image acquired for treatment planning were collected. Biomechanical model-based DIR was applied between the inhale and exhale phase of the 4DCT scans and stress maps were calculated. The voxel-wise correlation between the reference SPECT-V image and map of the maximum principal stress was measured with a Spearman correlation coefficient. The overlap between high (above the 75th percentile) and low (below the 25th percentile) functioning volumes extracted from the reference SPECT-V and the stress maps was measured with Dice similarity coefficients (DSC). The results were compared to those obtained when using two classical CT-ventilation metrics: the change in HU and Jacobian determinant.

resultsThe mean Spearman correlation coefficients were: 0.37 ± 18 and 0.39 ± 13 and 0.59 ± 0.13 considering the changes in HU, Jacobian and maximum principal stress, respectively. The corresponding mean DSC coefficients were 0.38 ± 0.09, 0.37 ± 0.07 and 0.52 ± 0.07 for the high ventilation function volumes and 0.48 ± 0.13, 0.44 ± 0.09 and 0.52 ± 0.07 for the low ventilation function volumes.

conclusionFor presenting a significantly stronger and more consistent correlation with standard SPECT-V images than previously proposed CT-ventilation metrics, stress maps derived with the proposed method appear to be a promising tool for incorporation into functional lung avoidance strategies.

Indexed as

Lung NeoplasmsPulmonary VentilationFour-Dimensional Computed TomographyHumansLungRetrospective StudiesbiomechanicsCT‐ventilation imaginglung cancer

Identifiers

PMID33617034
PMCPMC8444226
OpenAlexW3113331811

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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.