Reproducibility of aortic valve calcification scoring with computed tomography - An interplatform analysis.
Aged
Aged, 80 and over
Aortic Valve
/ diagnostic imaging
Aortic Valve Stenosis
/ diagnostic imaging
Calcinosis
/ diagnostic imaging
Female
Humans
Male
Observer Variation
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
/ methods
Reproducibility of Results
Retrospective Studies
Severity of Illness Index
Software
Tomography, X-Ray Computed
Aortic stenosis
Computed tomography
Reproducibility of results
Transcatheter aortic valve replacement
Journal
Journal of cardiovascular computed tomography
ISSN: 1876-861X
Titre abrégé: J Cardiovasc Comput Tomogr
Pays: United States
ID NLM: 101308347
Informations de publication
Date de publication:
Historique:
received:
12
06
2018
revised:
20
10
2018
accepted:
14
01
2019
pubmed:
23
1
2019
medline:
14
6
2019
entrez:
23
1
2019
Statut:
ppublish
Résumé
To investigate whether aortic valve calcification (AVC) scoring performed with different workstation platforms generates comparable and thus software-independent results. In this IRB-approved retrospective study, we included 100 consecutive patients with symptomatic aortic stenosis undergoing CT prior to transcatheter aortic valve implantation. Two independent observers performed AVC scoring on non-enhanced images with commercially available software platforms of four vendors (GE, Philips, Siemens, 3mensio). Gender-specific Agatston score cut-off values were applied according to current recommendations to assign patients to different likelihood categories of aortic stenosis (unlikely to very likely). Comparative analysis of Agatston scores between the four platforms were performed by using Kruskal-Wallis analysis, Spearman rank correlation, linear regression analysis, and Bland-Altman analysis. Differences in category assignment were compared using Fisher's exact test and Cohen's kappa. For both observers, each workstation platform produced slightly different numeric AVC Agatston scores, however, without statistical significance (p = 0.96 and p = 0.98). Excellent correlation was found between platforms, with r = 0.991-0.996 (Spearman) and r While absolute values differ slightly, common commercially available software platforms produce comparable results for AVC scoring, which indicates software-independence of the method.
Sections du résumé
BACKGROUND
BACKGROUND
To investigate whether aortic valve calcification (AVC) scoring performed with different workstation platforms generates comparable and thus software-independent results.
METHODS
METHODS
In this IRB-approved retrospective study, we included 100 consecutive patients with symptomatic aortic stenosis undergoing CT prior to transcatheter aortic valve implantation. Two independent observers performed AVC scoring on non-enhanced images with commercially available software platforms of four vendors (GE, Philips, Siemens, 3mensio). Gender-specific Agatston score cut-off values were applied according to current recommendations to assign patients to different likelihood categories of aortic stenosis (unlikely to very likely). Comparative analysis of Agatston scores between the four platforms were performed by using Kruskal-Wallis analysis, Spearman rank correlation, linear regression analysis, and Bland-Altman analysis. Differences in category assignment were compared using Fisher's exact test and Cohen's kappa.
RESULTS
RESULTS
For both observers, each workstation platform produced slightly different numeric AVC Agatston scores, however, without statistical significance (p = 0.96 and p = 0.98). Excellent correlation was found between platforms, with r = 0.991-0.996 (Spearman) and r
CONCLUSION
CONCLUSIONS
While absolute values differ slightly, common commercially available software platforms produce comparable results for AVC scoring, which indicates software-independence of the method.
Identifiants
pubmed: 30665879
pii: S1934-5925(18)30183-7
doi: 10.1016/j.jcct.2019.01.016
pii:
doi:
Types de publication
Comparative Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
92-98Commentaires et corrections
Type : CommentIn
Informations de copyright
Copyright © 2019. Published by Elsevier Inc.