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This article provides an overview on the principles of transthoracic echocardiography in horses. Indications for echocardiography, equipment, and technical considerations are discussed and a systematic approach for a complete echocardiographic examination in horses is described. Methods for assessment of chamber dimensions, allometric scaling of measurements, assessment of systolic and diastolic ventricular function, assessment of atrial function, hemodynamic assessment, and evaluation of valvular regurgitation are explained, focusing on traditional 2-dimensional (2D), motion-mode, and Doppler echocardiographic methods. Selected applications of newer echocardiographic methods, such as tissue Doppler imaging and 2D speckle tracking are also described.

Congenital heart disease should be considered when evaluating calves with chronic respiratory signs, failure to thrive, poor growth, or if a murmur is heard on physical examination. Echocardiography is currently the gold standard for diagnosing congenital heart defects. A wide variety of defects, either alone or in combination with a ventricular septal defect, are possible. A standardized approach using sequential segmental analysis is required to fully appreciate the nature and severity of more complex malformations. The prognosis for survival varies from guarded to poor and depends on the hemodynamic relevance of the defects and the degree of cardiac compensation.

Objectives To investigate the relationship of heart rate (HR) and ECG time intervals to body weight (BWT) in healthy horses and ponies. We hypothesized that HR and ECG time intervals are related to BWT. Animals 250 healthy horses of >30 breeds; 5.5 (1–30) y [median (range)]; 479 (46–1018) kg. Methods Prospective study. Standard base-apex ECGs were recorded while the horses were standing quietly in a box stall. Mean HR over 15 s was calculated and RR interval, PQ interval, QRS duration, and QT interval were measured by a single observer.QT was corrected for differences in heart rate using Fridericia's formula (QT cf = QT/ 3 √RR). The relationship between ECG variables and BWT, age, sex, and RR interval was assessed using multivariate backward stepwise regression analyses. Goodness of fit of the model was improved when using log(BWT) compared to BWT. Body weight was overall the strongest predictor of HR and ECG time intervals. Therefore, only log(BWT) was included as an independent variable in the final model. The level of significance was p = 0.05. Results HR ( R 2 = 0.21) showed a significant negative relationship and PQ ( R 2 = 0.53), QRS ( R 2 = 0.23), QT ( R 2 = 0.14), and QT cf ( R 2 = 0.02) showed significant positive relationships to log(BWT). Conclusions Small equine breeds undergoing routine ECG recordings have slightly faster heart rates and shorter ECG time intervals compared to larger equine breeds. Although the magnitude of absolute differences may be small, body weight needs to be considered among other factors when comparing HR and ECG time intervals to normal ranges in horses.