Evidence map›Paper›PMID 34604606›Full record

ArticleAdvances in radiation oncology

Implementation of a Knowledge-Based Treatment Planning Model for Cardiac-Sparing Lung Radiation Therapy.

Joseph Harms, Jiahan Zhang, Oluwatosin Kayode, Jonathan Wolf, Sibo Tian, Neal McCall, Kristin A Higgins, Richard Castillo, Xiaofeng Yang

Abstract read
In one paragraph

Article in Advances in radiation oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Dosimetric comparison between laterality-specific and general knowledge-based planning models for nonsmall cell lung cancer.Medical dosimetry : official journal of the American Association of Medical Dosimetrists
    Article
  7. Article
  8. Review
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.

Joseph HarmsDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Jiahan ZhangDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Oluwatosin KayodeDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Jonathan WolfDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Sibo TianDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Neal McCallDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Kristin A HigginsDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Richard CastilloDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.
Xiaofeng YangDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia.

Funding

Winship Cancer Institute Cancer Center Support GrantP30CA138292 · NCI · EMORY UNIVERSITY · PI Suresh S Ramalingam · 2009 to 2026
$47.5M
NCI NIH HHS P30 CA138292
6 · The paper itself

Abstract

purposeHigh radiation doses to the heart have been correlated with poor overall survival in patients receiving radiation therapy for stage III non-small cell lung cancer (NSCLC). We built a knowledge-based planning (KBP) tool to limit the dose to the heart during creation of volumetric modulated arc therapy (VMAT) treatment plans for patients being treated to 60 Gy in 30 fractions for stage III NSCLC. METHODS AND MATERIALS: A previous study at our institution retrospectively delineated intracardiac volumes and optimized VMAT treatment plans to reduce dose to these substructures and to the whole heart. Two RapidPlan (RP) KBP models were built from this cohort, 1 model using the clinical plans and a separate model using the cardiac-optimized plans. Using target volumes and 6 organs at risk (OARs), models were trained to generate treatment plans in a semiautomated process. The cardiac-sparing KBP model was tested in the same cohort used for training, and both models were tested on an external validation cohort of 30 patients.

resultsBoth RP models produced clinically acceptable plans in terms of target coverage, dose uniformity, and dose to OARs. Compared with the previously created cardiac-optimized plans, cardiac-sparing RPs showed significant reductions in the mean dose to the esophagus and lungs while performing similarly or better in all evaluated heart dose metrics. When comparing the 2 models, the cardiac-sparing RP showed reduced (

conclusionsBy using a set of cardiac-optimized treatment plans for training, the proposed KBP model provided a means to reduce the dose to the heart and its substructures without the need to explicitly delineate cardiac substructures. This tool may offer reduced planning time and improved plan quality and might be used to improve patient outcomes.

Identifiers

PMID34604606
PMCPMC8463738

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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.