Abstract
Background
To investigate the learning curve and the minimum number of cases required for a cardiologist
in training to acquire the skills to an accurate pre-TAVI cardiac CT (CCT) analysis
using a semi-automatic software.
Methods
In this prospective, observational study, 40 CCTs of patients scheduled for TAVI were
independently evaluated twice by 5 readers (80 readings each, 400 in total): a certified
TAVI-CT specialist served as the reference reader (RR) and 4 cardiology fellows (2
interventional and 2 non-invasive cardiac imaging) as readers. The primary outcome
was the minimum number of cases required to achieve an accuracy in imaging interpretation
≥80%, defined as the agreement between each reader and the RR in both balloon and
self-expandable valve size choice. The secondary outcomes were the intra- and inter-observer
variability.
Results
After 50 readings (25 cases repeated twice) cardiology fellows were able to select
the appropriate valve size with 80% of accuracy compared to the RR, independently of valve calcification, image quality
and slice thickness. Learning curves of both interventional and non-invasive cardiac
imaging fellows showed a similar trend. Cardiology fellows achieved a very high intra-
and inter-observer reliability for both perimeter and area assessment, with an intraclass
correlation coefficient (ICC) ranging from 0.96 to 0.99.
Conclusions
Despite the individual differences, cardiology fellows required 50 readings (25 cases
repeated twice) to get adequately skilled in the pre-TAVI CCT interpretation. These
results provide valuable information for developing adequate training sessions and
education protocols for both companies and cardiologists involved.
Graphical abstract
Graphical Abstract
Keywords
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Article info
Publication history
Published online: March 11, 2022
Accepted:
March 8,
2022
Received in revised form:
March 5,
2022
Received:
December 14,
2021
Identification
Copyright
© 2022 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
