Development and validation of a diagnostic echocardiographic mass (DEM) score in the complex approach to cardiac masses

Abstract

Abstract Background Cardiac masses (CM) are an extremely heterogeneous clinical entity, including benign and malignant neoformations. 2D Echocardiography is nowadays the first-line approach to define nature and management of CM. Purpose The purpose of our study was to identify the echocardiographic predictors of malignancy and create a multiparametric score to further increase the diagnostic yield and accurately suggest the nature of CM. Material and methods 249 consecutive patients undergoing a complete echocardiographic assessment for suspected cardiac mass were enrolled from January 2004 to December 2020. A definitive diagnosis was achieved by histological examination or, in case of cardiac thrombi, with radiological evidence of thrombus resolution after an appropriate anticoagulant treatment. Logistic regression was performed to evaluate the ability of echocardiography to discriminate benign versus malignant masses. Results A scoring system was developed in a derivation cohort of 178 (70%) and validated in 71 (30%) patients. A weighted score [Diagnostic Echocardiographic Mass (DEM) Score] ranging from 0 to 9 was obtained from 6 variables: infiltration, polylobate mass, moderate-severe pericardial effusion, inhomogeneity, sessile and non-left localization. The AUC for the score was 0.965 (95% CI 0.938–0.993). In a logistic regression analysis using the DEM score as a predictor, the likelihood of malignancy increased more than 4 times for a 1-unit increase of the score (OR=4.468; 95% CI 2.733–7.304). The prognostic validity of the score was confirmed by its ability to predict survival during follow-up (median time of 31 months). Conclusions The application of a multiparametric echocardiographic score in the approach to CM accurately predicts mass malignancy thereby reducing the need for second-level investigations, and minimizing the diagnostic delay in such a complex clinical scenario. Funding Acknowledgement Type of funding sources: None.