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The Caption Interpretation Automated Ejection Fraction software is used to process previously acquired transthoracic cardiac ultrasound images, to store images, and to manipulate and make measurements on images using an ultrasound device, personal computer, or a compatible DICOM-compliant PACS system in order to provide automated estimation of left ventricular ejection fraction. This measurement can be used to assist the clinician in a cardiac evaluation. The Caption Interpretation Automated Ejection Fraction Software is indicated for use in adult patients.

The Caption Interpretation Automated Ejection Fraction Software ("AutoEF") applies machine learning algorithms to process two-dimensional transthoracic echocardiography images for calculating left ventricular ejection fraction. The current implementation of the device adds a predetermined change control plan (PCCP) to the device cleared under K210747, which allows future modifications to the device. The version of Caption Interpretation AutoEF cleared under K210747 performs left ventricular ejection fraction estimation using apical four chamber (A4C), apical two chamber (A2C) and the parasternal long-axis (PLAX) cardiac ultrasound images. The software uses an algorithm that was derived through use of deep learning and locked prior to validation. The product operates as an add-in to a DICOM PACS system, ultrasound device, or personal computer. Caption Interpretation receives imaging data either directly from an ultrasound system or from a module in a PACS system. The device includes the following main components: 1. Clip Annotation and Selection: The AutoEF software includes a function that processes video clips in a study to automatically classify clips that are PLAX. AP4, and AP2 views. This view selection is based on a convolutional network. It also includes a function, Image Quality Score (IQS), that allows selection of best available PLAX, AP4, and AP2 clips within the study or provide an indication to the user if there are no clips with sufficient quality to estimate ejection fraction, based on prespecified IQS thresholds. 2. Eiection Fraction Estimator and Confidence Metric: The automated eiection fraction estimation is performed using a machine learning model trained on apical and parasternal long-axis views. The model is trained with a dataset from a large number of patients. representative of the intended patient population and variety of contemporary cardiac ultrasound scanners. The EF calculation can be performed on a 3-view combination (PLAX, AP4 and AP2), 2-view combinations (AP4 and AP2, AP2 and PLAX, AP4 and PLAX), or single views (AP4, AP2). The confidence metric provides expected error in left-ventricle ejection fraction estimation and is based on IQS.