Evaluation of virtual monoenergetic imaging algorithms for dual-energy carotid and intracerebral CT angiography: Effects on image quality, artefacts and diagnostic performance for the detection of stenosis. Issue 99 (February 2018)
- Record Type:
- Journal Article
- Title:
- Evaluation of virtual monoenergetic imaging algorithms for dual-energy carotid and intracerebral CT angiography: Effects on image quality, artefacts and diagnostic performance for the detection of stenosis. Issue 99 (February 2018)
- Main Title:
- Evaluation of virtual monoenergetic imaging algorithms for dual-energy carotid and intracerebral CT angiography: Effects on image quality, artefacts and diagnostic performance for the detection of stenosis
- Authors:
- Leithner, Doris
Mahmoudi, Scherwin
Wichmann, Julian L.
Martin, Simon S.
Lenga, Lukas
Albrecht, Moritz H.
Booz, Christian
Arendt, Christophe T.
Beeres, Martin
D'Angelo, Tommaso
Bodelle, Boris
Vogl, Thomas J.
Scholtz, Jan-Erik - Abstract:
- Highlights: VMI+ improve quantitative image quality in supraaortic CTA. VMI and VMI+ provide increased suitability for artery evaluation. VMI and VMI+ show excellent accordance for the assessment of carotid stenosis. Abstract: Purpose: To investigate the impact of traditional (VMI) and noise-optimized virtual monoenergetic imaging (VMI+) algorithms on quantitative and qualitative image quality, and the assessment of stenosis in carotid and intracranial dual-energy CTA (DE-CTA). Materials and methods: DE-CTA studies of 40 patients performed on a third-generation 192-slice dual-source CT scanner were included in this retrospective study. 120-kVp image-equivalent linearly-blended, VMI and VMI+ series were reconstructed. Quantitative analysis included evaluation of contrast-to-noise ratios (CNR) of the aorta, common carotid artery, internal carotid artery, middle cerebral artery, and basilar artery. VMI and VMI+ with highest CNR, and linearly-blended series were rated qualitatively. Three radiologists assessed artefacts and suitability for evaluation at shoulder height, carotid bifurcation, siphon, and intracranial using 5-point Likert scales. Detection and grading of stenosis were performed at carotid bifurcation and siphon. Results: Highest CNR values were observed for 40-keV VMI+ compared to 65-keV VMI and linearly-blended images ( P < 0.001). Artefacts were low in all qualitatively assessed series with excellent suitability for supraaortic artery evaluation at shoulder andHighlights: VMI+ improve quantitative image quality in supraaortic CTA. VMI and VMI+ provide increased suitability for artery evaluation. VMI and VMI+ show excellent accordance for the assessment of carotid stenosis. Abstract: Purpose: To investigate the impact of traditional (VMI) and noise-optimized virtual monoenergetic imaging (VMI+) algorithms on quantitative and qualitative image quality, and the assessment of stenosis in carotid and intracranial dual-energy CTA (DE-CTA). Materials and methods: DE-CTA studies of 40 patients performed on a third-generation 192-slice dual-source CT scanner were included in this retrospective study. 120-kVp image-equivalent linearly-blended, VMI and VMI+ series were reconstructed. Quantitative analysis included evaluation of contrast-to-noise ratios (CNR) of the aorta, common carotid artery, internal carotid artery, middle cerebral artery, and basilar artery. VMI and VMI+ with highest CNR, and linearly-blended series were rated qualitatively. Three radiologists assessed artefacts and suitability for evaluation at shoulder height, carotid bifurcation, siphon, and intracranial using 5-point Likert scales. Detection and grading of stenosis were performed at carotid bifurcation and siphon. Results: Highest CNR values were observed for 40-keV VMI+ compared to 65-keV VMI and linearly-blended images ( P < 0.001). Artefacts were low in all qualitatively assessed series with excellent suitability for supraaortic artery evaluation at shoulder and bifurcation height. Suitability was significantly higher in VMI+ and VMI compared to linearly-blended images for intracranial and ICA assessment ( P < 0.002). VMI and VMI+ showed excellent accordance for detection and grading of stenosis at carotid bifurcation and siphon with no differences in diagnostic performance. Conclusion: 40-keV VMI+ showed improved quantitative image quality compared to 65-keV VMI and linearly-blended series in supraaortic DE-CTA. VMI and VMI+ provided increased suitability for carotid and intracranial artery evaluation with excellent assessment of stenosis, but did not translate into increased diagnostic performance. … (more)
- Is Part Of:
- European journal of radiology. Issue 99(2018)
- Journal:
- European journal of radiology
- Issue:
- Issue 99(2018)
- Issue Display:
- Volume 99, Issue 99 (2018)
- Year:
- 2018
- Volume:
- 99
- Issue:
- 99
- Issue Sort Value:
- 2018-0099-0099-0000
- Page Start:
- 111
- Page End:
- 117
- Publication Date:
- 2018-02
- Subjects:
- BA basilar artery -- CCA common carotid artery -- CNR contrast-to-noise ratio -- DECT dual-energy CT -- DE-CTA dual-energy CTA -- ICA internal carotid artery -- MCA middle cerebral artery -- SNR signal-to-noise ratio -- VMI virtual monoenergetic imaging -- VMI+ noise-optimized virtual monoenergetic imaging
Dual-energy CT angiography -- Virtual monoenergetic imaging -- Carotid arteries -- Carotis stenosis -- Diagnostic performance
Medical radiology -- Periodicals
Radiology -- Periodicals
Radiologie médicale -- Périodiques
Medical radiology
Periodicals
616.075705 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0720048X ↗
http://www.elsevier.com/homepage/elecserv.htt ↗
http://www.clinicalkey.com/dura/browse/journalIssue/0720048X ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/0720048X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ejrad.2017.12.024 ↗
- Languages:
- English
- ISSNs:
- 0720-048X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3829.738050
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5662.xml