Evidence map›Paper›PMID 26638163›Full record

ArticleEuropean radiology2016

Dual-energy CT-based iodine quantification for differentiating pulmonary artery sarcoma from pulmonary thromboembolism: a pilot study.

Suyon Chang, Jin Hur, Dong Jin Im, Young Joo Suh, Yoo Jin Hong, Hye-Jeong Lee, Young Jin Kim, Byoung Wook Choi

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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 17 papers.

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0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Dual-energy CT in pulmonary vascular disease.The British journal of radiology · 2022
    Review
  7. Review
  8. State of the art: utility of multi-energy CT in the evaluation of pulmonary vasculature.The international journal of cardiovascular imaging · 2019
    Review
  9. Pulmonary arteries: imaging of pulmonary embolism and beyond.Cardiovascular diagnosis and therapy · 2019
    Review
  10. Article
  11. Article
  12. Low-dose spectral CT reconstruction using image gradientApplied mathematical modelling · 2018
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. 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

8 authors.

Suyon ChangDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.
Jin HurDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea. khuhz@yuhs.ac.
Dong Jin ImDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.
Young Joo SuhDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.
Yoo Jin HongDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.
Hye-Jeong LeeDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.
Young Jin KimDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.
Byoung Wook ChoiDepartment of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 120-752, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe purpose of this study was to determine whether dual-energy computed tomography (DECT) angiography could differentiate pulmonary thromboembolism (PTE) from pulmonary artery sarcoma (PAS).

methodsWe prospectively enrolled 19 patients that had a filling defect in the main pulmonary artery on DECT. Six patients who had PAS and underwent DECT were retrospectively enrolled for comparison. Pathological results or follow-up CT after anticoagulation therapy were used to make the final diagnosis. Two investigators measured the following parameters at the filling defect in the main pulmonary artery: CT attenuation density [Hounsfield units (HU)], iodine-related HU (IHU) and iodine concentration (IC, mg/ml).

resultsFrom a total of 25 patients (M:F = 10:15; mean age, 65 years old), 19 were categorised into the PTE group and six were categorised into the PAS group. The mean HU values were not significantly different between the PTE and PAS groups (45.5 ± 15.9 vs 47.1 ± 9.2 HU; P = 0.776). However, the mean IHU and IC values of the lesions were significantly different between the PTE and PAS groups (10.6 ± 7.2 vs 27.9 ± 9.1 HU; P = 0.004, and 0.61 ± 0.39 vs 1.49 ± 0.57; P = 0.001).

conclusionsDECT angiography using a quantitative analytic methodology can be used to differentiate PTE and PAS. KEY POINTS: • DECT can be useful for differentiation of PAS and PTE. • With quantitative analysis, DECT offers tissue characterisation by detecting lesion parameter increases. • The patients without predisposing factors for PTE can be candidates for DECT.

Indexed as

AgedAngiographyDiagnosis, DifferentialFemaleHumansLung NeoplasmsMaleMiddle AgedPilot ProjectsPulmonary ArteryPulmonary EmbolismRetrospective StudiesSarcomaTomography, X-Ray ComputedDifferential diagnosisDual-energy computed tomography (DECT)Pulmonary artery sarcoma (PAS)Pulmonary thromboembolism (PTE)Quantitative analysis

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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.