Evidence map›Paper›PMID 38371894›Full record

ArticlePolish journal of radiology2024

Optimisation of virtual monoenergetic reconstructions for the diagnosis of pulmonary embolism using photon-counting detector computed tomography angiography.

Jordan H Chamberlin, Adrienn Toth, Shaun Hinen, Jim O'Doherty, Dhiraj Baruah, Dhruw Maisuria, Aaron McGuire, Heather Knight, U Joseph Schoepf, Reginald F Munden and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Polish journal of radiology, 2024. 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
0.9field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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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

11 authors at 1 institution in 1 country.

Jordan H ChamberlinDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Adrienn TothDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Shaun HinenDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Jim O'DohertyDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Dhiraj BaruahDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Dhruw MaisuriaDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Aaron McGuireDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Heather KnightDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
U Joseph SchoepfDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Reginald F MundenDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Ismail M KabakusDivision of Cardiothoracic Imaging, Department of Radiology and Radiologic Sciences, Medical University of South Carolina, Charleston, SC, United States.
Medical University of South Carolina · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Computed tomography (CT) pulmonary angiography is considered the gold standard for pulmonary embolism (PE) diagnosis, relying on the discrimination between contrast and embolus. Photon-counting detector CT (PCD-CT) generates monoenergetic reconstructions through energy-resolved detection. Virtual monoenergetic images (VMI) at low keV can be used to improve pulmonary artery opacification. While studies have assessed VMI for PE diagnosis on dual-energy CT (DECT), there is a lack of literature on optimal settings for PCD-CT-PE reconstructions, warranting further investigation. Material and methods: Twenty-five sequential patients who underwent PCD-CT pulmonary angiography for suspicion of acute PE were retrospectively included in this study. Quantitative metrics including signal-to-noise ratio (SNR) and contrast-to-noise (CNR) ratio were calculated for 4 VMI values (40, 60, 80, and 100 keV). Qualitative measures of diagnostic quality were obtained for proximal to distal pulmonary artery branches by 2 cardiothoracic radiologists using a 5-point modified Likert scale. Results: SNR and CNR were highest for the 40 keV VMI (49.3 ± 22.2 and 48.2 ± 22.1, respectively) and were inversely related to monoenergetic keV. Qualitatively, 40 and 60 keV both exhibited excellent diagnostic quality (mean main pulmonary artery: 5.0 ± 0 and 5.0 ± 0; subsegmental pulmonary arteries 4.9 ± 0.1 and 4.9 ± 0.1, respectively) while distal segments at high (80-100) keVs had worse quality. Conclusions: 40 keV was the best individual VMI for the detection of pulmonary embolism by quantitative metrics. Qualitatively, 40-60 keV reconstructions may be used without a significant decrease in subjective quality. VMIs at higher keV lead to reduced opacification of the distal pulmonary arteries, resulting in decreased image quality.

Indexed as

optimisationPCCTpulmonary embolismVMI

Identifiers

PMID38371894
PMCPMC10867981
OpenAlexW4391660376

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.