Evidence map›Paper›PMID 34595112›Full record

ArticleFrontiers in oncology2021

Beam Angle Optimization for Double-Scattering Proton Delivery Technique Using an Eclipse Application Programming Interface and Convolutional Neural Network.

Wonjoong Cheon, Sang Hee Ahn, Seonghoon Jeong, Se Byeong Lee, Dongho Shin, Young Kyung Lim, Jong Hwi Jeong, Sang Hee Youn, Sung Uk Lee, Sung Ho Moon and 2 more

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

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

12 authors at 1 institution in 1 country.

Wonjoong CheonProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Sang Hee AhnProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Seonghoon JeongProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Se Byeong LeeProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Dongho ShinProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Young Kyung LimProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Jong Hwi JeongProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Sang Hee YounProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Sung Uk LeeProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Sung Ho MoonProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Tae Hyun KimProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
Haksoo KimProton Therapy Center, National Cancer Center, Goyang-si, South Korea.
National Cancer Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To automatically identify optimal beam angles for proton therapy configured with the double-scattering delivery technique, a beam angle optimization method based on a convolutional neural network (BAODS-Net) is proposed. Fifty liver plans were used for training in BAODS-Net. To generate a sequence of input data, 25 rays on the eye view of the beam were determined per angle. Each ray collects nine features, including the normalized Hounsfield unit and the position information of eight structures per 2° of gantry angle. The outputs are a set of beam angle ranking scores (

Indexed as

beam angle optimizationconvolutional neural networkdeep-learningdouble-scattering techniqueproton therapy

Identifiers

PMID34595112
PMCPMC8476903
OpenAlexW3199027776

What OpenQuestion holds

Textmetadata
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.