Echocardiographic Markers in the Diagnosis of Cardiac Masses.

BACKGROUND

The echocardiographic parameters required for a comprehensive assessment of cardiac masses (CMs) are still largely unknown. The aim of this study was to identify and integrate the echocardiographic features of CMs that can accurately predict malignancy.

METHODS

An observational cohort study was conducted among 286 consecutive patients who underwent standard echocardiographic assessment for suspected CM at Bologna University Hospital between 2004 and 2022. A definitive diagnosis was achieved by histologic examination or, in the case of cardiac thrombi, with radiologic evidence of thrombus resolution after appropriate anticoagulant treatment. Logistic and multivariable regression analysis was performed to confirm the ability of six echocardiographic parameters to discriminate malignant from benign masses. The unweighted count of these parameters was used as a numeric score, ranging from 0 to 6, with a cutoff of ≥3 balancing sensitivity and specificity with respect to the histologic diagnosis of malignancy. Classification tree analysis was used to determine the ability of echocardiographic parameters to discriminate subgroups of patients with differential risk for malignancy.

RESULTS

Benign masses were more frequently pedunculated, mobile, and adherent to the interatrial septum (P < .001). Malignant masses showed a greater diameter and exhibited a higher frequency of irregular margins, an inhomogeneous appearance, sessile implantation, polylobate shape, and pericardial effusion (P < .001). Infiltration, moderate to severe pericardial effusion, nonleft localization, sessile implantation, polylobate shape, and inhomogeneity were confirmed to be independent predictors of malignancy in both univariate and multivariable models. The predictive ability of the unweighted score of ≥3 was very high (>0.90) and similar to that of the previously published weighted score. Classification tree analysis generated an algorithm in which infiltration was the best discriminator of malignancy, followed by nonleft localization and sessile implantation. The percentage correctly classified by classification tree analysis as malignant was 87.5%. Agreement between observer readings and CM histology ranged between 85.1% and 91.5%. The presence of at least three echocardiographic parameters was associated with lower survival.

CONCLUSIONS

In the approach to CMs, some echocardiographic parameters can serve as markers to accurately predict malignancy, thereby informing the need for second-level investigations and minimizing the diagnostic delay in such a complex clinical scenario.