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CT Cardiomegaly is a command line software application intended to be run on its own or as part of another medical device to automatically calculate linear and area based cardiothoracic ratio (CTR) from a CT image containing the heart. CT Cardiomegaly is designed to measure the maximal transverse diameter of heart and maximal inner transverse diameter of thoracic cavity and calculate the CTR from an axial CT slice containing the heart using a non-adaptive machine learning algorithm. Intended users of the software are aimed to the physicians or other licensed practitioners in the healthcare institutions, such as clinics, hospitals, healthcare facilities, residential care facilities and long-term care services. The system is suitable for adults and transitional adolescents (18 to 21 years old but treated as an adult). Its results are not intended to be used on a stand-alone basis for clinical-decision making or otherwise preclude clinical assessment of any disease.

The CT Cardiomegaly application is a software only (SaMD) medical device which includes automated algorithms and non-adaptive machine learning to analyze chest computed tomography (CT) images. CT Cardiomegaly is a command line software intended to be run on its own or as part of another medical device. CT Cardiomegaly scans the existing images for the presence of specific anatomical structures (i.e., heart and chest cavity). If the target structures are present, the software segments and performs automated measurements which may be helpful in assisting with the detection of certain diseases and/or conditions (i.e., cardiomegaly). The quantitative information is provided to the clinician in the form of a summary report. The clinician (using all available information) then decides if further diagnostic work-up, analysis or measurements are indicated. The results from CT Cardiomegaly are not intended to be used as the primary input for clinicaldecision making or diagnosis. A reference standard was created to train the machine learning algorithms in CT Cardiomegaly. Data for training and testing were sampled from this database based on exclusion criteria. Data was also selected to ensure no site was shared by training and testing cohorts. The training dataset included 1600 unique patient cases from 267 unique sites across 20 U.S. states.