Evidence map›Paper›PMID 34697884›Full record

ArticleJournal of applied clinical medical physics2021

Feasibility of function-guided lung treatment planning with parametric response mapping.

Charles K Matrosic, D Rocky Owen, Daniel Polan, Yilun Sun, Shruti Jolly, Caitlin Schonewolf, Matthew Schipper, Randall K Ten Haken, Craig J Galban, Martha Matuszak

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 38% 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, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
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

10 authors at 1 institution in 1 country.

Charles K MatrosicDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
D Rocky OwenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Daniel PolanDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Yilun SunDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Shruti JollyDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Caitlin SchonewolfDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Matthew SchipperDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Randall K Ten HakenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Craig J GalbanDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Martha MatuszakDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
University of Michigan–Ann Arbor · 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
Prediction of COPD Progression by PRMR01HL150023 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GALBAN, CRAIG J, HAN, MEILAN K · 2020 to 2023
$2.8M
An Early Imaging Marker of EmphysemaR01HL139690 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GALBAN, CRAIG J · 2019 to 2022
$1.9M
NCI NIH HHS P01 CA059827NCI NIH HHS P01-CA059827NHLBI NIH HHS R01 HL139690NHLBI NIH HHS R01-HL139690NHLBI NIH HHS R01 HL150023NHLBI NIH HHS R01-HL150023
6 · The paper itself

Abstract

purposeRecent advancements in functional lung imaging have been developed to improve clinicians' knowledge of patient pulmonary condition prior to treatment. Ultimately, it may be possible to employ these functional imaging modalities to tailor radiation treatment plans to optimize patient outcome and mitigate pulmonary complications. Parametric response mapping (PRM) is a computed tomography (CT)-based functional lung imaging method that utilizes a voxel-wise image analysis technique to classify lung abnormality phenotypes, and has previously been shown to be effective at assessing lung complication risk in diagnostic applications. The purpose of this work was to demonstrate the implementation of PRM guidance in radiotherapy treatment planning. METHODS AND MATERIALS: A retrospective study was performed with 18 lung cancer patients to test the incorporation of PRM into a radiotherapy planning workflow. Paired inspiration/expiration pretreatment CT scans were acquired and PRM analysis was utilized to classify each voxel as normal, parenchymal disease, small airway disease, and emphysema. Density maps were generated for each PRM classification to contour high density regions of pulmonary abnormalities. Conventional volumetric-modulated arc therapy and PRM-guided treatment plans were designed for each patient.

resultsPRM guidance was successfully implemented into the treatment planning process. The inclusion of PRM priorities resulted in statistically significant (p < 0.05) improvements to the V20Gy within the PRM avoidance contours. On average, reductions of 5.4% in the V20Gy(%) were found. The PRM-guided treatment plans did not significantly increase the dose to the organs at risk or result in insufficient planning target volume coverage, but did increase plan complexity.

conclusionsPRM guidance was successfully implemented into a treatment planning workflow and shown to be effective for dose redistribution within the lung. This work has provided a framework for the potential clinical implementation of PRM-guided treatment planning.

Indexed as

Lung NeoplasmsRadiotherapy, Intensity-ModulatedFeasibility StudiesHumansLungRadiotherapy Planning, Computer-AssistedRetrospective Studiesfunctional imaginglung cancertreatment planning

Identifiers

PMID34697884
PMCPMC8598143
OpenAlexW3208795721

What OpenQuestion holds

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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.