Evidence map›Paper›PMID 31516607›Full record

ArticleOncology letters2019

Validation of magnetic resonance imaging-based automatic high-grade glioma segmentation accuracy via

Tomohiko Ozaki, Manabu Kinoshita, Hideyuki Arita, Naoki Kagawa, Yasunori Fujimoto, Yonehiro Kanemura, Mio Sakai, Yoshiyuki Watanabe, Katsuyuki Nakanishi, Eku Shimosegawa and 2 more

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

Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 46% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 3 institutions in 1 country.

Tomohiko OzakiDepartment of Neurosurgery, Osaka International Cancer Institute, Osaka 5418567, Japan.
Manabu KinoshitaDepartment of Neurosurgery, Osaka International Cancer Institute, Osaka 5418567, Japan.
Hideyuki AritaDepartment of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Naoki KagawaDepartment of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Yasunori FujimotoDepartment of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Yonehiro KanemuraDepartment of Biomedical Research and Innovation, Institute for Clinical Research, Osaka National Hospital, National Hospital Organization, Osaka 5400006, Japan.
Mio SakaiDepartment of Radiology, Osaka International Cancer Institute, Osaka 5418567, Japan.
Yoshiyuki WatanabeDepartment of Radiology, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Katsuyuki NakanishiDepartment of Radiology, Osaka International Cancer Institute, Osaka 5418567, Japan.
Eku ShimosegawaDepartment of Nuclear Medicine and Tracer Kinetics, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Jun HatazawaDepartment of Nuclear Medicine and Tracer Kinetics, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Haruhiko KishimaDepartment of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan.
Osaka University · JPOsaka Medical Center for Cancer and Cardiovascular Diseases · JPOsaka National Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain Tumor Image Analysis (BraTumIA) is a fully automated segmentation tool dedicated to detecting brain tumors imaged by magnetic resonance imaging (MRI). BraTumIA has recently been applied to several clinical investigations; however, the validity of this novel method has not yet been fully examined. The present study was conducted to validate the quality of tumor segmentation with BraTumIA in comparison with results from

Indexed as

11C-methionine positron emission tomographyautomatic segmentationmagnetic resonance imagingmalignant glioma

Identifiers

PMID31516607
PMCPMC6732988
OpenAlexW2967429605

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.