Key result
Fully automated planning of cardiac geometries showed high agreement with manual planning for cardiac functional parameters (Lin's concordance correlation coefficient 0.91 to 0.99).
Why the study?
Does fully automated geometry planning for cardiac MR imaging provide high agreement and reproducibility of functional cardiac parameters compared to manual planning in patients referred for left-ventricular function assessment?
Cross-Sectional (n=50)
Does fully automated geometry planning for cardiac MR imaging provide high agreement and reproducibility of functional cardiac parameters compared to manual planning in patients referred for left-ventricular function assessment?
Fully automated planning for cardiac MRI is highly accurate and reproducible compared to manual planning, offering a reliable operator-independent approach.
Automated planning may boost CMR interstudy reproducibility; hypothesis-generating before routine clinical adoption.
PURPOSE: To establish operator-independent, fully automated planning of standard cardiac geometries and to determine the impact on interstudy reproducibility of cardiac functional parameters. MATERIALS AND METHODS: Cardiac MR imaging was done in 50 patients referred for left-ventricular function assessment. In all patients, first standard manual planning was performed followed by automatic planning (AUTO1) and repeat automatic planning (AUTO2) after repositioning the patient to investigate interstudy reproducibility. Cardiac functional parameters were assessed and cine scans were visually graded on a 4-point scale from nondiagnostic to excellent. RESULTS: Overall success rate of AUTO was 94% with good to excellent geometry planning in >94% of cine standard views. Comparing manual versus fully automated planning, a high agreement of cardiac functional parameters (Lin's concordance correlation coefficient, 0.91 to 0.99) with minimal percent bias (0.24 to 3.84%) was found. In addition, a high interstudy reproducibility of automatic planning was demonstrated (Lin's concordance correlation coefficient, 0.89 to 0.99; percent bias, 0.38 to 5.04%; precision, 3.46 to 9.09%). CONCLUSION: Fully automated planning of cardiac geometries could reliably be performed in patients showing a variety of cardiovascular pathologies. Standard cardiac geometries were precisely replicated and functional parameters were highly accurate.
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Frick et al. (2011) conducted a cross-sectional in left-ventricular function assessment (n=50). Fully automated planning of standard cardiac geometries vs. Standard manual planning was evaluated on Agreement of cardiac functional parameters (Lin's concordance correlation coefficient 0.91 to 0.99). Fully automated planning of cardiac geometries showed high agreement with manual planning for cardiac functional parameters (Lin's concordance correlation coefficient 0.91 to 0.99).
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