Evidence map›Paper›PMID 28476138›Full record

ArticleRadiation oncology (London, England)2017

A comprehensive dosimetric study on switching from a Type-B to a Type-C dose algorithm for modern lung SBRT.

Christina Zhou, Nathan Bennion, Rongtao Ma, Xiaoying Liang, Shuo Wang, Kristina Zvolanek, Megan Hyun, Xiaobo Li, Sumin Zhou, Weining Zhen and 3 more

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Are offline ART decisions for NSCLC impacted by the type of dose calculation algorithm?Technical innovations & patient support in radiation oncology · 2024
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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

13 authors.

Christina ZhouSchool of Biological Sciences, University of Chicago, Chicago, IL, USA.
Nathan BennionDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Rongtao MaDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Xiaoying LiangUniversity of Florida Health Proton Therapy Institute, Jacksonville, FL, USA.
Shuo WangDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Kristina ZvolanekDepartment of Biological Systems Engineering, University of Nebraska Lincoln, Lincoln, NE, USA.
Megan HyunDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Xiaobo LiDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Sumin ZhouDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Weining ZhenDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Chi LinDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Andrew WahlDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA.
Dandan ZhengDepartment of Radiation Oncology, University of Nebraska Medical Center, 42nd and Emile St, Omaha, NE, 68198, USA. sabrinadan@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType-C dose algorithms provide more accurate dosimetry for lung SBRT treatment planning. However, because current dosimetric protocols were developed based on conventional algorithms, its applicability for the new generation algorithms needs to be determined. Previous studies on this issue used small sample sizes and reached discordant conclusions. Our study assessed dose calculation of a Type-C algorithm with current dosimetric protocols in a large patient cohort, in order to demonstrate the dosimetric impacts and necessary treatment planning steps of switching from a Type-B to a Type-C dose algorithm for lung SBRT planning.

methodsFifty-two lung SBRT patients were included, each planned using coplanar VMAT arcs, normalized to D

resultsRe-calculated Type-C plans resulted in decreased PTV D

conclusionsType-B SBRT lung plans considerably overestimate target coverage for some patients, necessitating Type-C re-normalization or re-optimization. Current RTOG dosimetric criteria appear to remain appropriate.

Indexed as

AlgorithmsRadiosurgeryAgedAged, 80 and overCarcinoma, Non-Small-Cell LungFemaleFollow-Up StudiesHumansLung NeoplasmsMaleMiddle AgedOrgans at RiskPrognosisRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedDose algorithmsLungMonte CarloSBRTVMAT

Identifiers

PMID28476138
PMCPMC5420128

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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.