Evidence map›Paper›PMID 37185930›Full record

ArticleEuropean radiology experimental2023

Individualized scan protocols for CT angiography: an animal study for contrast media or radiation dose optimization.

Johannes Haubold, Sebastian Zensen, René Hosch, Benedikt Michael Schaarschmidt, Denise Bos, Bernhardt Schmidt, Thomas Flohr, Yan Li, Michael Forsting, Hubertus Pietsch and 2 more

Open access · goldAbstract read
In one paragraph

Article in European radiology experimental, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

4 citing papers in PubMed, 7 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

12 authors at 3 institutions in 1 country.

Johannes HauboldDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany. johannes.haubold@uk-essen.de.ORCID 0000-0003-4843-5911
Sebastian ZensenDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
René HoschDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
Benedikt Michael SchaarschmidtDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
Denise BosDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
Bernhardt SchmidtSiemens Healthcare GmbH, Forchheim, Germany.
Thomas FlohrSiemens Healthcare GmbH, Forchheim, Germany.
Yan LiDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
Michael ForstingDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
Hubertus PietschMR and CT Contrast Media Research, Bayer AG, Berlin, Germany.
Felix NensaDepartment of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147, Essen, Germany.
Gregor JostMR and CT Contrast Media Research, Bayer AG, Berlin, Germany.
Essen University Hospital · DEBayer (Germany) · DESiemens Healthineers (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe investigated about optimization of contrast media (CM) dose or radiation dose in thoracoabdominal computed tomography angiography (CTA) by automated tube voltage selection (ATVS) system configuration and CM protocol adaption.

methodsIn six minipigs, CTA-optimized protocols were evaluated regarding objective (contrast-to-noise ratio, CNR) and subjective (6 criteria assessed by Likert scale) image quality. Scan parameters were automatically adapted by the ATVS system operating at 90-kV semi-mode and configured for standard, CM saving, or radiation dose saving (image task, quality settings). Injection protocols (dose, flow rate) were adapted manually. This approach was tested for normal and simulated obese conditions.

resultsRadiation exposure (volume-weighted CT dose index) for normal (obese) conditions was 2.4 ± 0.7 (5.0 ± 0.7) mGy (standard), 4.3 ± 1.1 (9.0 ± 1.3) mGy (CM reduced), and 1.7 ± 0.5 (3.5 ± 0.5) mGy (radiation reduced). The respective CM doses for normal (obese) settings were 210 (240) mgI/kg, 155 (177) mgI/kg, and 252 (288) mgI/kg. No significant differences in CNR (normal; obese) were observed between standard (17.8 ± 3.0; 19.2 ± 4.0), CM-reduced (18.2 ± 3.3; 20.5 ± 4.9), and radiation-saving CTAs (16.0 ± 3.4; 18.4 ± 4.1). Subjective analysis showed similar values for optimized and standard CTAs. Only the parameter diagnostic acceptability was significantly lower for radiation-saving CTA compared to the standard CTA.

conclusionsThe CM dose (-26%) or radiation dose (-30%) for thoracoabdominal CTA can be reduced while maintaining objective and subjective image quality, demonstrating the feasibility of the personalization of CTA scan protocols. KEY POINTS: • Computed tomography angiography protocols could be adapted to individual patient requirements using an automated tube voltage selection system combined with adjusted contrast media injection. • Using an adapted automated tube voltage selection system, a contrast media dose reduction (-26%) or radiation dose reduction (-30%) could be possible.

Indexed as

Computed Tomography AngiographyContrast MediaAnimalsRadiation DosageSwineSwine, MiniatureTomography, X-Ray ComputedContrast MediaAnimalsContrast mediaRadiationTomography (x-ray computed)

Identifiers

PMID37185930
PMCPMC10130261
OpenAlexW4366998399

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.