Ejection Fraction: Significance, Normal Values, and Measurement

Key Takeaways

• Ejection fraction (EF) describes the proportion of blood ejected by the left ventricle per beat – measured as a percentage.
• Normal value: A normal cardiac ejection fraction is ≥ 50% (ESC classification threshold) – the typical physiological normal range is 55–65%.
• A reduced ejection fraction (≤ 40%) is the hallmark of HFrEF – heart failure with reduced ejection fraction.
• Echocardiography is the standard method for EF measurement; wireless handheld devices enable measurement directly at the bedside.
• AI-assisted tools such as Caption AI AutoEF calculate EF automatically – without manual delineation of the heart.

What Is Ejection Fraction? Definition and Clinical Significance

Ejection fraction – abbreviated EF or LVEF (left ventricular ejection fraction) – is the percentage of the end-diastolic volume that the left ventricle ejects into the systemic circulation with each heartbeat. It is the central measurement for assessing the systolic pumping function of the heart, the basis for treatment decisions, and an established prognostic marker.

Important: EF describes systolic function – i.e. pumping strength. A normal EF does not exclude heart failure. In HFpEF (heart failure with preserved ejection fraction), EF is normal but the heart fills poorly. More on this in the section on heart failure classification.

Measuring Ejection Fraction: An Overview of Methods

EF can be determined using various imaging modalities. Echocardiography is the clinical standard – non-invasive, radiation-free, and performable at the bedside. MRI provides the most precise volume measurements but is resource-intensive and expensive. Scintigraphy and CT are used in specific clinical situations.

Echocardiography: Standard Method for EF Measurement

In clinical practice, EF is measured echocardiographically. The standard method is the biplane Simpson’s method of discs. For this, the contour of the left ventricle is traced in two imaging planes: the apical four-chamber view (AP4) and the apical two-chamber view (AP2). Measurements are taken at end-diastole and end-systole. EF is derived from the calculated volumes.

The method is well validated but time-consuming and dependent on image quality and the examiner’s experience. With poor acoustic windows – such as in obesity or pulmonary hyperinflation – contrast agents or alternative imaging planes may be required.

EF Measurement in Point-of-Care Echocardiography (POCUS)

Bedside POCUS echocardiography has fundamentally changed EF diagnostics. Wireless ultrasound devices for cardiology such as the Vscan Air SL enable focused cardiac examinations without stationary console devices – in the emergency department, intensive care unit, or GP practice.

In POCUS echocardiography, EF is often estimated visually or measured using simplified methods. The image quality of modern handheld devices – thanks to SignalMax™ and XDclear™ technology – enables valid cardiac function assessments. PW Doppler and M-mode, both standard features of the Vscan Air SL, are available for additional functional evaluation.

Dr Guy Lloyd, Head of Echocardiography at Bart’s Heart Centre in London, captures the clinical potential: “I can make 90% of the diagnoses I need right at the bedside and treat the patient immediately.”

Normal Values for Ejection Fraction and Their Interpretation

A healthy left ventricle pumps more than half of its blood with each beat. Normal ejection fraction is physiologically 55–65%. According to ESC classification, the following thresholds apply: (ESC Guidelines 2021, European Heart Journal)

• ≥ 50%: Normal or preserved ejection fraction
• 41–49%: Mildly reduced ejection fraction
• ≤ 40%: Reduced ejection fraction

Values above 70–75% may indicate hypertrophic obstructive cardiomyopathy (HOCM) or other causes of hyperdynamic cardiac function and should be investigated.

The clinical context is decisive: an EF of 45% in an asymptomatic individual has a different significance than the same EF in a person with dyspnoea and elevated biomarkers. EF is a measurement – not a diagnosis.

Ejection Fraction in Heart Failure: Classification into HFrEF, HFmrEF, and HFpEF

Heart failure is not a single entity. The ESC guidelines classify it into three subtypes based on left ventricular ejection fraction – each with different pathophysiology, treatment, and prognosis. (ESC Guidelines 2021, European Heart Journal)

HFrEF: Heart Failure with Reduced EF (≤ 40%)

HFrEF (Heart Failure with Reduced Ejection Fraction) is the “classic” form of heart failure with impaired pumping function. The myocardium contracts less forcefully than normal – often following myocardial infarction, in dilated cardiomyopathy, or as a consequence of hypertension. The left ventricle is often enlarged and thin-walled.

HFrEF has the strongest evidence base for pharmacotherapy – four drug classes form the foundation of treatment according to ESC guidelines. Early diagnosis is critical, and bedside EF measurement can save time in achieving it.

HFmrEF: Mildly Reduced EF (41–49%)

HFmrEF (Heart Failure with Mildly Reduced Ejection Fraction) is a grey zone. Patients have mildly impaired pumping function but share clinical features with both other subtypes. The ESC introduced HFmrEF as a distinct category in 2021, as this group may benefit from treatments similar to those used in HFrEF.

HFpEF: Preserved EF Despite Heart Failure (≥ 50%)

In HFpEF (Heart Failure with Preserved Ejection Fraction), the heart pumps normally but fillspoorly. The ventricular wall is often thickened and stiff, impairing diastolic filling. Symptoms are the same as in HFrEF: dyspnoea, fatigue, fluid retention.

HFpEF is the most common form of heart failure in older patients and disproportionately affects women. Diagnosis is challenging, as a normal EF does not exclude heart failure. In addition to EF, elevated biomarkers (NT-proBNP) and structural cardiac changes – such as left atrial enlargement – are diagnostically decisive.

AI-Assisted EF Measurement: What Does Current Research Show?

Artificial intelligence is changing EF diagnostics. Automated algorithms detect the ventricular contour and calculate EF – without manual tracing. This makes the measurement less dependent on the examiner’s experience and saves time. This is particularly relevant for non-specialists who perform echocardiographic assessments infrequently.

For cardiologists such as Dr Martin Altersberger from Steyr, this represents a fundamental opportunity: “We want to find patients with relevant pathology – young or old – where an early diagnosis can truly make a difference.”

Caption Guidance™ and AutoEF: How Caption AI Supports Image Acquisition

Caption AI is an AI software from GE HealthCare, available on the Vscan Air SL with Caption AI. It consists of two components: Caption Guidance™ guides the user in real time through the steps for acquiring standardised echocardiography views. A quality indicator shows when image quality is sufficient for a valid assessment.

The second component is AutoEF: it automatically calculates left ventricular ejection fraction – from one or more standard views (PLAX, AP4, AP2) – without manual ventricular wall tracing. The more views acquired, the more precise the result. AutoEF also indicates whether the calculated value falls within the normal range – according to ASE and ACEP guidelines.

In a validated study with 99 patients, AutoEF demonstrated high agreement with reference values from experienced cardiologists: correlation coefficient r = 0.95, mean bias 1.0%, sensitivity 0.90, and specificity 0.92 for detecting EF ≤ 35%. (GE HealthCare AutoEFWhitepaper, peer-reviewed) These values were comparable to those of clinical users.

Vscan Air SL with Caption AI vs. Standard Echocardiography

The Vscan Air SL with Caption AI is not a substitute for comprehensive transthoracic echocardiography by specialist cardiologists. It is a tool for focused cardiac assessment at the point of care – particularly valuable where no echo laboratory is available or rapid decisions are required.

Caption AI broadens the range of users: GPs, internists, and emergency medicine teams can make valid EF assessments with AI support, without extensive echocardiography experience. Dr Nabila Laskar, Senior Cardiology Registrar at Bart’s Heart Centre in London, describes the systemic impact: “Emergency departments are relieved of pressure – this reduces the burden on our local hospitals.” More on the clinical application is shown in the webinar on AutoEF and Caption AI in early heart disease detection.

Causes of a Reduced Ejection Fraction

Impaired pumping function develops when the myocardium is chronically damaged or overloaded. The most common causes:

• Coronary artery disease and myocardial infarction: Scarred myocardium no longer contributes to pumping – one of the most common causes of reduced EF.
• Dilated cardiomyopathy: The myocardium is weakened and the ventricle enlarged – often genetically determined or following viral myocarditis.
• Arterial hypertension: Sustained high blood pressure chronically overloads the left ventricle.
• Valvular heart disease: Regurgitant or stenotic valves increase the cardiac workload.
• Toxic damage: Certain chemotherapy agents (e.g. anthracyclines), alcohol, or drugs can directly damage the myocardium.
• Tachycardia-induced cardiomyopathy: Sustained high heart rates exhaust the myocardium.

Can a Reduced Ejection Fraction Improve?

Yes – under certain conditions. A reduced EF is not necessarily irreversible. With treatment of the underlying cause – such as revascularisation following myocardial infarction, valve replacement, or optimised pharmacotherapy – EF can recover.

Karen Kelly, Advanced Nurse Practitioner and founder of HeartPath in Dublin, describes the daily reality with heart failure patients: “A handheld ultrasound is a genuine game-changer. It helps differentiate dyspnoea and identify pulmonary congestion in seconds – without waiting for X-ray or CT.”

This phenomenon is known as “reverse remodelling”: the myocardium adapts positively when the cause of overload is eliminated or heart failure is well managed. Patients who achieve an EF ≥ 50% under guideline-directed HFrEF therapy are classified as HFimpEF (Heart Failure with Improved Ejection Fraction) – a distinct entity introduced into the ESC guidelines in 2021. (ESC Guidelines 2021, European Heart Journal)

Regular EF monitoring is therefore relevant not only diagnostically, but also therapeutically. It shows whether treatment is working – and whether device implantation (e.g. ICD or CRT) remains indicated.

Frequently Asked Questions about Ejection Fraction

What Ejection Fraction Is Considered Normal?

According to ESC classification, a left ventricular ejection fraction of ≥ 50% is considered normal or preserved. The typical physiological normal range is 55–65%. Values between 41 and 49% are considered mildly reduced (HFmrEF), and values ≤ 40% as reduced (HFrEF). Values above 70–75% may indicate hypertrophic obstructive cardiomyopathy or other causes of hyperdynamic cardiac function.

What Does an Ejection Fraction Below 40% Mean?

An EF ≤ 40% defines HFrEF – heart failure with reduced pumping function. The heart pumps less than 40% of the blood from the left ventricle with each beat. Clinically, this manifests as dyspnoea, fatigue, and fluid retention. The diagnosis of HFrEF is the basis for guideline-directed therapy with four drug classes (ACE inhibitors/ARNI, beta-blockers, MRA, SGLT2 inhibitors).

What Is the Difference Between HFrEF and HFpEF?

In HFrEF, ejection fraction is reduced (≤ 40%) – the myocardium pumps too little blood. In HFpEF, EF is normal (≥ 50%), but the heart fills poorly because the ventricular wall is stiff. Both forms lead to the same symptoms – breathlessness, fatigue, oedema – but differ in pathophysiology, treatment, and prognosis. EF measurement is the first step in distinguishing between the two.

How Accurate Is Echocardiographic EF Measurement?

Echocardiographic EF measurement is the clinical standard method but has well-known limitations. Interobserver variability with the biplane Simpson’s method is typically ± 5–10%. (Akil et al., Clinical Physiology and Functional Imaging, 2025) Image quality, acoustic conditions, and examiner experience all influence the result. AI-assisted tools such as AutoEFreduce measurement dependency on examiner experience: in validated studies, AutoEFdemonstrated agreement with experienced cardiologists’ measurements of r = 0.95 – comparable to the interobserver variability of experienced echocardiographers.

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