التفاصيل البيبلوغرافية
| العنوان: |
Deep learning to diagnose cardiac amyloidosis from cardiovascular magnetic resonance. |
| المؤلفون: |
Martini, Nicola, Aimo, Alberto, Barison, Andrea, Latta, Daniele Della, Vergaro, Giuseppe, Aquaro, Giovanni Donato, Ripoli, Andrea, Emdin, Michele, Chiappino, Dante |
| المصدر: |
Journal of Cardiovascular Magnetic Resonance (BioMed Central); 12/7/2020, Vol. 22 Issue 1, p1-11, 11p, 1 Color Photograph, 1 Black and White Photograph, 4 Charts, 4 Graphs |
| مستخلص: |
Background: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the likelihood of CA. Methods: 1.5 T CMR was performed in 206 subjects with suspected CA (n = 100, 49% with unexplained left ventricular (LV) hypertrophy; n = 106, 51% with blood dyscrasia and suspected light-chain amyloidosis). Patients were randomly assigned to the training (n = 134, 65%), validation (n = 30, 15%), and testing subgroups (n = 42, 20%). Short axis, 2-chamber, 4-chamber late gadolinium enhancement (LGE) images were evaluated by 3 networks (DL algorithms). The tags “amyloidosis present” or “absent” were attributed when the average probability of CA from the 3 networks was ≥ 50% or < 50%, respectively. The DL strategy was compared to a machine learning (ML) algorithm considering all manually extracted features (LV volumes, mass and function, LGE pattern, early blood-pool darkening, pericardial and pleural effusion, etc.), to reproduce exam reading by an experienced operator. Results: The DL strategy displayed good diagnostic accuracy (88%), with an area under the curve (AUC) of 0.982. The precision (positive predictive value), recall score (sensitivity), and F1 score (a measure of test accuracy) were 83%, 95%, and 89% respectively. A ML algorithm considering all CMR features had a similar diagnostic yield to DL strategy (AUC 0.952 vs. 0.982; p = 0.39). Conclusions: A DL approach evaluating LGE acquisitions displayed a similar diagnostic performance for CA to a MLbased approach, which simulates CMR reading by experienced operators. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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