Evidence map›Paper›PMID 28926370›Full record

ArticleInvestigative radiology2018

Photon-Counting Computed Tomography for Vascular Imaging of the Head and Neck: First In Vivo Human Results.

Rolf Symons, Daniel S Reich, Mohammadhadi Bagheri, Tyler E Cork, Bernhard Krauss, Stefan Ulzheimer, Steffen Kappler, David A Bluemke, Amir Pourmorteza

Abstract read
In one paragraph

Article in Investigative radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 3% 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

100 citing papers in PubMed, 1 synthesis or guideline pooled it, 180 citations in OpenAlex.

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  15. Clinical applications of portable CT scanners.The British journal of radiology · 2025
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40 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

9 authors at 5 institutions in 3 countries.

Rolf Symons
Daniel S Reich
Mohammadhadi Bagheri
Tyler E Cork
Bernhard Krauss
Stefan Ulzheimer
Steffen Kappler
David A Bluemke
Amir Pourmorteza
National Institutes of Health Clinical Center · USSiemens Healthcare (Germany) · DEEmory University · USNational Institute of Neurological Disorders and Stroke · USUniversity of Wisconsin–Madison · US

Funding

Multimodal MRI in Multiple SclerosisZIANS003119 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI REICH, DANIEL · 2010 to 2025
$53.4M
Molecular Biomedical Imaging Laboratory (NIBIB)ZIAEB000072 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI BLUEMKE, DAVID · 2010 to 2017
$5.0M
Molecular Biomedical Imaging Laboratory (CC)ZIACL090019 · CLC · CLINICAL CENTER · PI JONES, ELIZABETH C. · 2010 to 2017
$0k
Intramural NIH HHS Z99 CL999999Intramural NIH HHS ZIA CL090019Intramural NIH HHS ZIA EB000072Intramural NIH HHS ZIA NS003119
6 · The paper itself

Abstract

purposeThe purpose of this study was to evaluate image quality of a spectral photon-counting detector (PCD) computed tomography (CT) system for evaluation of major arteries of the head and neck compared with conventional single-energy CT scans using energy-integrating detectors (EIDs).

methodsIn this institutional review board-approved study, 16 asymptomatic subjects (7 men) provided informed consent and received both PCD and EID contrast-enhanced CT scans of the head and neck (mean age, 58 years; range, 46-75 years). Tube settings were (EID: 120 kVp/160 mA vs PCD: 140 kVp/108 mA) for all volunteers. Quantitative analysis included measurements of mean attenuation, image noise, and contrast-to-noise ratio (CNR). Spectral PCD data were used to reconstruct virtual monoenergetic images and iodine maps. A head phantom was used to validate iodine concentration measurements in PCD images only. Two radiologists blinded to detector type independently scored the image quality of different segments of the arteries, as well as diagnostic acceptability, image noise, and severity of artifacts of the PCD and EID images. Reproducibility was assessed with intraclass correlation coefficient. Linear mixed models that account for within-subject correlation of analyzed arterial segments were used. Linear regression and Bland-Altman analysis with 95% limits of agreement were used to calculate the accuracy of material decomposition.

resultsPhoton-counting detector image quality scores were significantly higher compared with EID image quality scores with lower image noise (P < 0.01) and less image artifacts (P < 0.001). Photon-counting detector image noise was 9.1% lower than EID image noise (8.0 ± 1.3 HU vs 8.8 ± 1.5 HU, respectively, P < 0.001). Arterial segments showed artifacts on EID images due to beam hardening that were not present on PCD images. On PCD images of the head phantom, there was excellent correlation (R = 0.998) between actual and calculated iodine concentrations without significant bias (bias: -0.4 mg/mL [95% limits of agreements: -1.1 to 0.4 mg/mL]). Iodine maps had 20.7% higher CNR compared with nonspectral PCD (65.2 ± 9.0 vs 54.0 ± 4.5, P = 0.01), and virtual monoenergetic image at 70 keV showed similar CNR to nonspectral images (52.6 ± 4.2 vs 54.0 ± 4.5, P = 0.39).

conclusionsPhoton-counting CT has the potential to improve the image quality of carotid and intracranial CT angiography compared with single-energy EID CT.

Indexed as

AgedBrainCarotid ArteriesCerebrovascular CirculationComputed Tomography AngiographyContrast MediaCoronary AngiographyFemaleHumansImage Processing, Computer-AssistedIodineMaleMiddle AgedPhantoms, ImagingPhotonsProspective StudiesContrast MediaIodine

Identifiers

PMID28926370
PMCPMC5792306
OpenAlexW2758647230

What OpenQuestion holds

Textmetadata
LicenceTDM
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.