Evidence map›Paper›PMID 26334508›Full record

ArticleEuropean radiology2016

Advanced image-based virtual monoenergetic dual-energy CT angiography of the abdomen: optimization of kiloelectron volt settings to improve image contrast.

Moritz H Albrecht, Jan-Erik Scholtz, Kristina Hüsers, Martin Beeres, Andreas M Bucher, Moritz Kaup, Simon S Martin, Sebastian Fischer, Boris Bodelle, Ralf W Bauer and 3 more

Abstract read
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In one paragraph

Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing 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

69 citing papers in PubMed.

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9 more citing papers are in PubMed but not listed here.

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.

Moritz H AlbrechtDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. MoritzAlbrecht@gmx.net.
Jan-Erik ScholtzDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Kristina HüsersDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Martin BeeresDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Andreas M BucherDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Moritz KaupDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Simon S MartinDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Sebastian FischerDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Boris BodelleDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Ralf W BauerDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Thomas LehnertDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Thomas J VoglDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
Julian L WichmannDepartment of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo compare quantitative image quality parameters in abdominal dual-energy computed tomography angiography (DE-CTA) using an advanced image-based (Mono+) reconstruction algorithm for virtual monoenergetic imaging and standard DE-CTA.

methodsFifty-five patients (36 men; mean age, 64.2 ± 12.7 years) who underwent abdominal DE-CTA were retrospectively included. Mono + images were reconstructed at 40, 50, 60, 70, 80, 90 and 100 keV levels and as standard linearly blended M_0.6 images (60 % 100 kV, 40 % 140 kV). The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the common hepatic (CHA), splenic (SA), superior mesenteric (SMA) and left renal arteries (LRA) were objectively measured.

resultsMono+ DE-CTA series showed a statistically superior CNR for 40, 50, 60, 70 and 80 keV (P < 0.031) compared to M_0.6 images for all investigated arteries except SMA at 80 keV (P = 0.08). CNR at 40 keV revealed a mean relative increase of 287.7 % compared to linearly blended images among all assessed arteries (P < 0.001). SNR of Mono+ images was consistently significantly higher at 40, 50, 60 and 70 keV compared to M_0.6 for CHA and SA (P < 0.009).

conclusionsCompared to linearly blended images, Mono+ reconstructions at low keV levels of abdominal DE-CTA datasets significantly improve quantitative image quality. KEY POINTS: • Mono+ combines increased attenuation with reduced image noise compared to standard DE-CTA. • Mono+ shows superior contrast-to-noise ratios at low keV compared to linearly-blended images. • Contrast-to-noise ratio in monoenergetic DE-CTA peaks at 40 keV. • Mono+ reconstructions significantly improve quantitative image quality at low keV levels.

Indexed as

AlgorithmsAbdominal CavityComputed Tomography AngiographyFemaleHumansMaleMiddle AgedRadiography, Dual-Energy Scanned ProjectionRetrospective StudiesSignal-To-Noise RatioComputed tomography angiographyDual-energy CTImage qualityMonochromatic imagingMonoenergetic plus

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Registered trials

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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.