Evidence map›Paper›PMID 30108006›Full record

ArticleInternational journal of radiation oncology, biology, physics2018

Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage.

Daniel Rocky Owen, Phillip S Boonstra, Benjamin L Viglianti, James M Balter, Matthew J Schipper, William C Jackson, Issam El Naqa, Shruti Jolly, Randall K Ten Haken, Feng-Ming Spring Kong and 1 more

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 32% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Combining Serial and Parallel Functionality in Functional Lung Avoidance Radiation Therapy.International journal of radiation oncology, biology, physics · 2022
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Daniel Rocky OwenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan. Electronic address: rockyo@umich.edu.
Phillip S BoonstraDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan.
Benjamin L VigliantiDepartment of Radiology, University of Michigan, Ann Arbor, Michigan; Nuclear Medicine Service, Veterans Affairs, Ann Arbor, Michigan.
James M BalterDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Matthew J SchipperDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan.
William C JacksonDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Issam El NaqaDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Shruti JollyDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Randall K Ten HakenDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Feng-Ming Spring KongDepartment of Radiation Oncology, Indiana University School of Medicine, Indianapolis, Indiana.
Martha M MatuszakDepartment of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
University of Michigan · USIndiana University School of Medicine

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Scott Michael Schuetze · 1988 to 2026
$178.2M
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
FUNCTIONAL IMAGE AND MOLECULAR MARKER TO INDIVIDUALIZE ADAPTIVE RADIATION DOSE ESR01CA142840 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KONG, FENG-MING P. · 2010 to 2015
$2.0M
NCI NIH HHS P01 CA059827NCI NIH HHS P30 CA046592NCI NIH HHS R01 CA142840
6 · The paper itself

Abstract

purposeFunctional-guided radiation therapy (RT) plans have the potential to limit damage to normal tissue and reduce toxicity. Although functional imaging modalities have continued to improve, a limited understanding of the functional response to radiation and its application to personalized therapy has hindered clinical implementation. The purpose of this study was to retrospectively model the longitudinal, patient-specific dose-function response in non-small cell lung cancer patients treated with RT to better characterize the expected functional damage in future, unknown patients. METHODS AND MATERIALS: Perfusion single-photon emission computed tomography/computed tomography scans were obtained at baseline (n = 81), midtreatment (n = 74), 3 months post-treatment (n = 51), and 1 year post-treatment (n = 26) and retrospectively analyzed. Patients were treated with conventionally fractionated RT or stereotactic body RT. Normalized perfusion single-photon emission computed tomography voxel intensity was used as a surrogate for local lung function. A patient-specific logistic model was applied to each individual patient's dose-function response to characterize functional reduction at each imaging time point. Patient-specific model parameters were averaged to create a population-level logistic dose-response model.

resultsA significant longitudinal decrease in lung function was observed after RT by analyzing the voxelwise change in normalized perfusion intensity. Generated dose-function response models represent the expected voxelwise reduction in function, and the associated uncertainty, for an unknown patient receiving conventionally fractionated RT or stereotactic body RT. Differential treatment responses based on the functional status of the voxel at baseline suggest that initially higher functioning voxels are damaged at a higher rate than lower functioning voxels.

conclusionsThis study modeled the patient-specific dose-function response in patients with non-small cell lung cancer during and after radiation treatment. The generated population-level dose-function response models were derived from individual patient assessment and have the potential to inform functional-guided treatment plans regarding the expected functional lung damage. This type of patient-specific modeling approach can be applied broadly to other functional response analyses to better capture intrapatient dependencies and characterize personalized functional damage.

Indexed as

Radiotherapy Planning, Computer-AssistedAdultAgedAged, 80 and overCarcinoma, Non-Small-Cell LungFemaleHumansLogistic ModelsLungLung NeoplasmsMaleMiddle AgedPatient-Specific ModelingPerfusion ImagingRadiotherapy DosageRetrospective Studies

Identifiers

PMID30108006
PMCPMC6202237
OpenAlexW2805215365

What OpenQuestion holds

Textmetadata
LicenceTDM
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.