Evidence map›Paper›PMID 30967601›Full record

ArticleScientific reports2019

Perfusion-ventilation CT via three-material differentiation in dual-layer CT: a feasibility study.

Andreas P Sauter, Johannes Hammel, Sebastian Ehn, Klaus Achterhold, Felix K Kopp, Melanie A Kimm, Kai Mei, Alexis Laugerette, Franz Pfeiffer, Ernst J Rummeny and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. K-Edge imaging using a clinical dual-source photon-counting CT system.Journal of applied clinical medical physics · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Quantitative imaging in medicine and surgery · 2021
    Article
  10. Article
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.

Andreas P SauterDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany. andreas.sauter@tum.de.ORCID http://orcid.org/0000-0003-4394-862X
Johannes HammelDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Sebastian EhnChair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Klaus AchterholdChair of Biomedical Physics, Department of Physics and Munich School of BioEngineering, Technical University of Munich, Garching, Germany.ORCID http://orcid.org/0000-0002-8724-1637
Felix K KoppDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Melanie A KimmDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-6833-9738
Kai MeiDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Alexis LaugeretteDepartment 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.
Daniela PfeifferDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.
Peter B NoëlDepartment of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-9671-6171

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dual-Energy Computed Tomography is of significant clinical interest due to the possibility of material differentiation and quantification. In current clinical routine, primarily two materials are differentiated, e.g., iodine and soft-tissue. A ventilation-perfusion-examination acquired within a single CT scan requires two contrast agents, e.g., xenon and gadolinium, and a three-material differentiation. In the current study, we have developed a solution for three-material differentiation for a ventilation-perfusion-examination. A landrace pig was examined using a dual-layer CT, and three scans were performed: (1) native; (2) xenon ventilation only; (3) xenon ventilation and gadolinium perfusion. An in-house developed algorithm was used to obtain xenon- and gadolinium-density maps. Firstly, lung tissue was segmented from other tissue. Consequently, a two-material decomposition was performed for lung tissue (xenon/soft-tissue) and for remaining tissue (gadolinium/soft-tissue). Results reveal that it was possible to differentiate xenon and gadolinium in a ventilation/perfusion scan of a pig, resulting in xenon and gadolinium density maps. By summation of both density maps, a three-material differentiation (xenon/gadolinium/soft tissue) can be performed and thus, xenon ventilation and gadolinium perfusion can be visualized in a single CT scan. In an additionally performed phantom study, xenon and gadolinium quantification showed very accurate results (r > 0.999 between measured and known concentrations).

Indexed as

AlgorithmsAnimalsFeasibility StudiesLungSwineTomography, X-Ray Computed

Identifiers

PMID30967601
PMCPMC6456734

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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.