Focused Cardiac Ultrasonography for Left Ventricular Systolic Function

Focused Cardiac Ultrasound Diagnosis of Dilated Cardiomyopathy

ABSTRACT

We report the case of a 6-year-old boy presenting to the emergency department after a syncopal event during a flu-like illness. Intermittent ventricular tachycardia was noted during Emergency Medical Services transport, and a focused cardiac ultrasound (FOCUS) in the emergency department revealed a dilated left ventricle and left atrium as well as severe global systolic dysfunction. Point-of-care ultrasound findings prompted expedited evaluation and management of this critically ill patient.

Deep Learning-Based Automated Echocardiographic Quantification of Left Ventricular Ejection Fraction: A Point-of-Care Solution

BACKGROUND

We have recently tested an automated machine-learning algorithm that quantifies left ventricular (LV) ejection fraction (EF) from guidelines-recommended apical views. However, in the point-of-care (POC) setting, apical 2-chamber views are often difficult to obtain, limiting the usefulness of this approach. Since most POC physicians often rely on visual assessment of apical 4-chamber and parasternal long-axis views, our algorithm was adapted to use either one of these 3 views or any combination. This study aimed to (1) test the accuracy of these automated estimates; (2) determine whether they could be used to accurately classify LV function.

METHODS

Reference EF was obtained using conventional biplane measurements by experienced echocardiographers. In protocol 1, we used echocardiographic images from 166 clinical examinations. Both automated and reference EF values were used to categorize LV function as hyperdynamic (EF>73%), normal (53%-73%), mildly-to-moderately (30%-52%), or severely reduced (<30%). Additionally, LV function was visually estimated for each view by 10 experienced physicians. Accuracy of the detection of reduced LV function (EF<53%) by the automated classification and physicians' interpretation was assessed against the reference classification. In protocol 2, we tested the new machine-learning algorithm in the POC setting on images acquired by nurses using a portable imaging system.

RESULTS

Protocol 1: the agreement with the reference EF values was good (intraclass correlation, 0.86-0.95), with biases <2%. Machine-learning classification of LV function showed similar accuracy to that by physicians in most views, with only 10% to 15% cases where it was less accurate. Protocol 2: the agreement with the reference values was excellent (intraclass correlation=0.84) with a minimal bias of 2.5±6.4%.

CONCLUSIONS

The new machine-learning algorithm allows accurate automated evaluation of LV function from echocardiographic views commonly used in the POC setting. This approach will enable more POC personnel to accurately assess LV function.

Perioperative echocardiography-guided hemodynamic therapy in high-risk patients: a practical expert approach of hemodynamically focused echocardiography

The number of high-risk patients undergoing surgery is growing. To maintain adequate hemodynamic functioning as well as oxygen delivery to the vital organs (DO2) amongst this patient population, a rapid assessment of cardiac functioning is essential for the anesthesiologist. Pinpointing any underlying cardiovascular pathophysiology can be decisive to guide interventions in the intraoperative setting. Various techniques are available to monitor the hemodynamic status of the patient, however due to intrinsic limitations, many of these methods may not be able to directly identify the underlying cause of cardiovascular impairment. Hemodynamic focused echocardiography, as a rapid diagnostic method, offers an excellent opportunity to examine signs of filling impairment, cardiac preload, myocardial contractility and the function of the heart valves. We thus propose a 6-step-echocardiographic approach to assess high-risk patients in order to improve and maintain perioperative DO2. The summary of all echocardiographic based findings allows a differentiated assessment of the patient's cardiovascular function and can thus help guide a (patho)physiological-orientated and individualized hemodynamic therapy.

[Perioperative optimization using hemodynamically focused echocardiography in high-risk patients-A practice guide]

BACKGROUND

The number of high-risk patients undergoing surgery is steadily increasing. In order to maintain and, if necessary, optimize perioperative hemodynamics as well as the oxygen supply to the organs (DO₂) in this patient population, a timely assessment of cardiac function and the underlying pathophysiological causes of hemodynamic instability is essential for the anesthesiologist. A variety of hemodynamic monitoring procedures are available for this purpose; however, due to method-immanent limitations they are often not able to directly identify the underlying cause of cardiovascular impairment.

OBJECTIVE

To present a stepwise algorithm for a perioperative echocardiography-based hemodynamic optimization in noncardiac surgery high-risk patients. In this context, echocardiography on demand according to international guidelines can be performed under certain conditions (hemodynamic instability, nonresponse to hemodynamic treatment) as well as in the context of a planned intraoperative procedure, mostly as a transesophageal echocardiography.

METHODS AND RESULTS

Hemodynamically focused echocardiography as a rapidly available bedside method, enables the timely diagnosis and assessment of cardiac filling obstructions, volume status and volume response, right and left heart function, and the function of the heart valves.

CONCLUSION

Integrating all echocardiographic findings in a differentiated assessment of the patient's cardiovascular function enables a (patho)physiologically oriented and individualized hemodynamic treatment.