Evidence map›Paper›PMID 29947267›Full record

ArticleThe British journal of radiology2018

Automatic contrast medium extraction system using electron density data with dual-energy CT.

Daisuke Kawahara, Shuichi Ozawa, Sodai Tanaka, Kazushi Yokomachi, Toru Higaki, Akito Saito, Kentaro Miki, Chikako Fujioka, Yoshimi Ohno, Yoshimi Ohno and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The British journal of radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Synthesized effective atomic numbers for commercially available dual-energy CT.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology
    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

13 authors.

Daisuke Kawahara1 Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital , Hiroshima , Japan.
Shuichi Ozawa3 Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University , Hiroshima , Japan.
Sodai Tanaka5 Department of Nuclear Engineering and Management, School of Engineering, University of Tokyo , Tokyo , Japan.
Kazushi Yokomachi1 Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital , Hiroshima , Japan.
Toru Higaki6 Departments of Diagnostic Radiology and Radiology, Hiroshima University , Hiroshima , Japan.
Akito Saito3 Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University , Hiroshima , Japan.
Kentaro Miki3 Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University , Hiroshima , Japan.
Chikako Fujioka1 Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital , Hiroshima , Japan.
Yoshimi Ohno1 Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital , Hiroshima , Japan.
Yoshimi Ohno1 Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital , Hiroshima , Japan.
Tomoki Kimura3 Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University , Hiroshima , Japan.
Yuji Murakami3 Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University , Hiroshima , Japan.
Yasushi Nagata3 Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University , Hiroshima , Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objective: The purpose of the current study is to create a contrast medium extraction method using raw-data-based electron density (rED) and CT number from dual-energy CT (DECT) for automatic delineation of the contrast region.

methods: A CT-ED phantom containing tissue-equivalent inserts and an acrylic phantom with an iodinated contrast medium were scanned by DECT. The contrast medium extraction system was created using Python. The accuracy of the contrast medium extraction was evaluated by measuring the diameter in terms of the full width at half maximum (FWHM) and the ratio of the volume (ROV).

results: Mean-2SD CT numbers and the difference of the CT numbers (DCT) of the contrast medium at 0-130 mg ml

conclusion: We created the contrast medium extraction method with rED and CT number images. The contrast medium extraction method could be used with DECT images at 80 kV/135 kV. The method is expected to only extract images from the region containing the contrast medium. ADVANCES IN KNOWLEDGE:: We created the contrast medium extraction method using raw-data-based electron density and CT number from DECT and it is expected to only extract information from the region containing the contrast medium.

Indexed as

Contrast MediaRadiotherapy Planning, Computer-AssistedHumansPhantoms, ImagingRadiography, Dual-Energy Scanned ProjectionTomography, X-Ray ComputedContrast Media

Identifiers

PMID29947267
PMCPMC6350475

What OpenQuestion holds

Textmetadata
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.