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Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imaging

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Item Type:Article
Title:Introduction of Lazy Luna an automatic software-driven multilevel comparison of ventricular function quantification in cardiovascular magnetic resonance imaging
Creators Name:Hadler, T., Wetzl, J., Lange, S., Geppert, C., Fenski, M., Abazi, E., Gröschel, J., Ammann, C., Wenson, F., Töpper, A., Däuber, S. and Schulz-Menger, J.
Abstract:Cardiovascular magnetic resonance imaging is the gold standard for cardiac function assessment. Quantification of clinical results (CR) requires precise segmentation. Clinicians statistically compare CRs to ensure reproducibility. Convolutional Neural Network developers compare their results via metrics. Aim: Introducing software capable of automatic multilevel comparison. A multilevel analysis covering segmentations and CRs builds on a generic software backend. Metrics and CRs are calculated with geometric accuracy. Segmentations and CRs are connected to track errors and their effects. An interactive GUI makes the software accessible to different users. The software's multilevel comparison was tested on a use case based on cardiac function assessment. The software shows good reader agreement in CRs and segmentation metrics (Dice > 90%). Decomposing differences by cardiac position revealed excellent agreement in midventricular slices: > 90% but poorer segmentations in apical (> 71%) and basal slices (> 74%). Further decomposition by contour type locates the largest millilitre differences in the basal right cavity (> 3 ml). Visual inspection shows these differences being caused by different basal slice choices. The software illuminated reader differences on several levels. Producing spreadsheets and figures concerning metric values and CR differences was automated. A multilevel reader comparison is feasible and extendable to other cardiac structures in the future.
Keywords:Cardiology, Quality Control, Software
Source:Scientific Reports
ISSN:2045-2322
Publisher:Nature Publishing Group
Volume:12
Number:1
Page Range:6629
Date:22 April 2022
Official Publication:https://doi.org/10.1038/s41598-022-10464-w
PubMed:View item in PubMed

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