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Erschienen in: European Radiology 8/2022

11.03.2022 | Cardiac

Diagnostic accuracy and performance of artificial intelligence in measuring left atrial volumes and function on multiphasic CT in patients with atrial fibrillation

verfasst von: Gilberto J. Aquino, Jordan Chamberlin, Basel Yacoub, Madison R. Kocher, Ismail Kabakus, Selcuk Akkaya, Megan Mercer, Jeffrey Waltz, Matthew Fiegel, Nathan Leaphart, Athira Jacob, Mehmet Akif Gulsun, James Gilkes, Joe Stephenson, Puneet Sharma, Pooyan Sahbaee, Joseph Schoepf, Stefan Zimmerman, Michael E. Field, Ali M. Agha, Jeremy R. Burt

Erschienen in: European Radiology | Ausgabe 8/2022

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Abstract

Objectives

To evaluate the effectiveness of a novel artificial intelligence (AI) algorithm for fully automated measurement of left atrial (LA) volumes and function using cardiac CT in patients with atrial fibrillation.

Methods

We included 79 patients (mean age 63 ± 12 years; 35 with atrial fibrillation (AF) and 44 controls) between 2017 and 2020 in this retrospective study. Images were analyzed by a trained AI algorithm and an expert radiologist. Left atrial volumes were obtained at cardiac end-systole, end-diastole, and pre-atrial contraction, which were then used to obtain LA function indices. Intraclass correlation coefficient (ICC) analysis of the LA volumes and function parameters was performed and receiver operating characteristic (ROC) curve analysis was used to compare the ability to detect AF patients.

Results

The AI was significantly faster than manual measurement of LA volumes (4 s vs 10.8 min, respectively). Agreement between the manual and automated methods was good to excellent overall, and there was stronger agreement in AF patients (all ICCs ≥ 0.877; p < 0.001) than controls (all ICCs ≥ 0.799; p < 0.001). The AI comparably estimated LA volumes in AF patients (all within 1.3 mL of the manual measurement), but overestimated volumes by clinically negligible amounts in controls (all by ≤ 4.2 mL). The AI’s ability to distinguish AF patients from controls using the LA volume index was similar to the expert’s (AUC 0.81 vs 0.82, respectively; p = 0.62).

Conclusion

The novel AI algorithm efficiently performed fully automated multiphasic CT-based quantification of left atrial volume and function with similar accuracy as compared to manual quantification.

Summary statement

Novel CT-based AI algorithm efficiently quantifies left atrial volumes and function with similar accuracy as manual quantification in controls and atrial fibrillation patients.

Key Points

There was good-to-excellent agreement between manual and automated methods for left atrial volume quantification.
The AI comparably estimated LA volumes in AF patients, but overestimated volumes by clinically negligible amounts in controls.
The AI’s ability to distinguish AF patients from controls was similar to the manual methods.
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Metadaten
Titel
Diagnostic accuracy and performance of artificial intelligence in measuring left atrial volumes and function on multiphasic CT in patients with atrial fibrillation
verfasst von
Gilberto J. Aquino
Jordan Chamberlin
Basel Yacoub
Madison R. Kocher
Ismail Kabakus
Selcuk Akkaya
Megan Mercer
Jeffrey Waltz
Matthew Fiegel
Nathan Leaphart
Athira Jacob
Mehmet Akif Gulsun
James Gilkes
Joe Stephenson
Puneet Sharma
Pooyan Sahbaee
Joseph Schoepf
Stefan Zimmerman
Michael E. Field
Ali M. Agha
Jeremy R. Burt
Publikationsdatum
11.03.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
European Radiology / Ausgabe 8/2022
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08657-y

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