Deep Learning Supplants Visual Analysis by Experienced Operators for the Diagnosis of Cardiac Amyloidosis by Cine-CMR.

Philippe Germain,Catherine Roy,Thomas Hellmut Schindler,Nicolas Padoy,Armine Vardazaryan,Soraya El Ghannudi,Aissam Labani

doi:10.3390/diagnostics12010069

Abstract

Background: Diagnosing cardiac amyloidosis (CA) from cine-CMR (cardiac magnetic resonance) alone is not reliable. In this study, we tested if a convolutional neural network (CNN) could outperform the visual diagnosis of experienced operators. Method: 119 patients with cardiac amyloidosis and 122 patients with left ventricular hypertrophy (LVH) of other origins were retrospectively selected. Diastolic and systolic cine-CMR images were preprocessed and labeled. A dual-input visual geometry group (VGG ) model was used for binary image classification. All images belonging to the same patient were distributed in the same set. Accuracy and area under the curve (AUC) were calculated per frame and per patient from a 40% held-out test set. Results were compared to a visual analysis assessed by three experienced operators. Results: frame-based comparisons between humans and a CNN provided an accuracy of 0.605 vs. 0.746 (p < 0.0008) and an AUC of 0.630 vs. 0.824 (p < 0.0001). Patient-based comparisons provided an accuracy of 0.660 vs. 0.825 (p < 0.008) and an AUC of 0.727 vs. 0.895 (p < 0.002). Conclusion: based on cine-CMR images alone, a CNN is able to discriminate cardiac amyloidosis from LVH of other origins better than experienced human operators (15 to 20 points more in absolute value for accuracy and AUC), demonstrating a unique capability to identify what the eyes cannot see through classical radiological analysis.

Highlights

Cardiac amyloidosis (CA) is a specific cardiomyopathy caused by the deposition of misfolded amyloid fibrils in the extracellular myocardial space
These signs are very nonspecific since they are seen in many other etiologies of left ventricular hypertrophy such as advanced hypertensive disease, aortic stenosis and other overload diseases such as Fabry disease and sarcomeric hypertrophic cardiomyopathies, which is why cine-CMR alone is not recognized as effective for diagnosing cardiac amyloidosis
Amyloidosis vs. left ventricular hypertrophy (LVH) Classification Obtained with the Held-Out Test Set According to the Input Shape

Summary

Introduction

Cardiac amyloidosis (CA) is a specific cardiomyopathy caused by the deposition of misfolded amyloid fibrils in the extracellular myocardial space. Myocardial wall thickening, atrial enlargement and pericardial or pleural effusion constitute the hallmarks of amyloid cardiac involvement [9] These signs are very nonspecific since they are seen in many other etiologies of left ventricular hypertrophy such as advanced hypertensive disease, aortic stenosis and other overload diseases such as Fabry disease and sarcomeric hypertrophic cardiomyopathies, which is why cine-CMR alone is not recognized as effective for diagnosing cardiac amyloidosis. Conclusion: based on cine-CMR images alone, a CNN is able to discriminate cardiac amyloidosis from LVH of other origins better than experienced human operators (15 to 20 points more in absolute value for accuracy and AUC), demonstrating a unique capability to identify what the eyes cannot see through classical radiological analysis

Objectives

Methods

Conclusion