Evidence map›Paper›PMID 30802258›Full record

ArticlePloS one2019

Differentiation between blood and iodine in a bovine brain-Initial experience with Spectral Photon-Counting Computed Tomography (SPCCT).

Isabelle Riederer, Salim Si-Mohamed, Sebastian Ehn, Daniel Bar-Ness, Peter B Noël, Alexander A Fingerle, Franz Pfeiffer, Ernst J Rummeny, Philippe Douek, Daniela Pfeiffer

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

14 citing papers in PubMed, 33 citations in OpenAlex.

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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

10 authors at 2 institutions in 2 countries.

Isabelle RiedererDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.ORCID 0000-0002-7856-8283
Salim Si-MohamedDepartment of Interventional Radiology and Cardio-vascular and Thoracic Diagnostic Imaging, Louis Pradel University Hospital, Bron, France.
Sebastian EhnChair of Biomedical Physics & Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Daniel Bar-NessUniversity Claude Bernard Lyon 1, CREATIS, CNRS UMR 5220, INSERM U1206, INSA-Lyon, France.
Peter B NoëlDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Alexander A FingerleDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Franz PfeifferDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Ernst J RummenyDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Philippe DouekDepartment of Interventional Radiology and Cardio-vascular and Thoracic Diagnostic Imaging, Louis Pradel University Hospital, Bron, France.
Daniela PfeifferDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Technical University of Munich · DEUniversité Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the accuracy of Spectral Photon-Counting Computed Tomography (SPCCT) in the quantification of iodine concentrations and its potential for the differentiation between blood and iodine.

methodsTubes with blood and a concentration series of iodine were scanned with a preclinical SPCCT system (both in vitro and in an ex vivo bovine brain tissue sample). Iodine density maps (IDM) and virtual non-contrast (VNC) images were generated using the multi-bin spectral information to perform material decomposition. Region-of-interest (ROI) analysis was performed within the tubes to quantitatively determine the absolute content of iodine (mg/ml).

resultsIn conventional CT images, ROI analysis showed similar Hounsfield Unit (HU) values for the tubes with blood and iodine (59.9 ± 1.8 versus 59.2 ± 1.5). Iodine density maps enabled clear differentiation between blood and iodine in vitro, as well as in the bovine brain model. Quantitative measurements of the different iodine concentrations matched well with those of actual known concentrations even for very small iodine concentrations with values below 1mg/ml (RMSE = 0.19).

conclusionsSPCCT providing iodine maps and virtual non-contrast images allows material decomposition, differentiation between blood and iodine in vitro and ex vivo in a bovine brain model and reliably quantifies the iodine concentration.

Indexed as

PhotonsTomography, Emission-ComputedAnimalsBloodBrainCattleContrast MediaIodineContrast MediaIodine

Identifiers

PMID30802258
PMCPMC6388929
OpenAlexW2916796389

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.