Echocardiography is an invaluable tool for the early detection and diagnosis of cardiac amyloidosis, a challenging and often underdiagnosed condition. Its advantages include accessibility, cost-effectiveness, ease of use, and the absence of radiation or radioactive tracers, making it superior to other imaging modalities. This chapter will demonstrate the crucial role of sonographers in identifying early signs of amyloidosis during routine echocardiographic examinations. By utilizing advanced technologies, particularly global longitudinal strain (GLS), sonographers can significantly enhance diagnostic accuracy by remaining vigilant for well-known echocardiographic markers that indicate amyloidosis. In recent years, artificial intelligence (AI)-based technologies have been introduced in echocardiography, significantly improving diagnostic capabilities. Recently, these AI technologies have advanced further with the introduction of new tools that enable automatic strain imaging within seconds after acquiring standard cardiac views. These advancements provide immediate automatic measurements of GLS, along with regional strain patterns characteristic of amyloidosis, such as apical sparing. Additionally, automatic measurements of left ventricular ejection fraction (EF) are obtained, and the recent development of regional assessments providing the Segmental Score Index further enhances diagnostic capabilities. The integration of these AI-based technologies in the echocardiographic assessment of cardiac function helps differentiate between cardiomyopathies, and aids in diagnosing amyloidosis. This chapter will demonstrate how simple, recognizable signs—further elucidated through case studies involving AL and ATTR amyloidosis—can guide sonographers to continue evaluating additional features, including the characteristic Bull’s Eye pattern on GLS imaging. This pattern, known for its apical sparing contrasted with reduced strain in the basal segments, presents a hallmark appearance reminiscent of a “cherry on top” and is suggestive of amyloid infiltration. By recognizing these patterns, sonographers can effectively alert the interpreting physician, prompting a more thorough assessment of the patient’s clinical history and potential recommendation for further testing to confirm or rule out cardiac amyloidosis, a diagnosis that may otherwise be missed. Early diagnosis is critical for patients, as cardiac amyloidosis is a fatal disease with a significantly shortened lifespan if not treated promptly. Sonographers are often the first to encounter these patients, and through careful echocardiographic evaluation, can raise suspicion of the disease. By increasing awareness of the dangers associated with this condition and recognizing our profound ability to contribute to its diagnosis, sonographers can play a pivotal role in improving diagnosis and treatment of this illness.

Echocardiography in Cardiac Amyloidosis for the Sonographer

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发表日期：

2025年

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Mali Mor,
David Leibowitz

摘要

Echocardiography is an invaluable tool for the early detection and diagnosis of cardiac amyloidosis, a challenging and often underdiagnosed condition. Its advantages include accessibility, cost-effectiveness, ease of use, and the absence of radiation or radioactive tracers, making it superior to other imaging modalities. This chapter will demonstrate the crucial role of sonographers in identifying early signs of amyloidosis during routine echocardiographic examinations. By utilizing advanced technologies, particularly global longitudinal strain (GLS), sonographers can significantly enhance diagnostic accuracy by remaining vigilant for well-known echocardiographic markers that indicate amyloidosis. In recent years, artificial intelligence (AI)-based technologies have been introduced in echocardiography, significantly improving diagnostic capabilities. Recently, these AI technologies have advanced further with the introduction of new tools that enable automatic strain imaging within seconds after acquiring standard cardiac views. These advancements provide immediate automatic measurements of GLS, along with regional strain patterns characteristic of amyloidosis, such as apical sparing. Additionally, automatic measurements of left ventricular ejection fraction (EF) are obtained, and the recent development of regional assessments providing the Segmental Score Index further enhances diagnostic capabilities. The integration of these AI-based technologies in the echocardiographic assessment of cardiac function helps differentiate between cardiomyopathies, and aids in diagnosing amyloidosis. This chapter will demonstrate how simple, recognizable signs—further elucidated through case studies involving AL and ATTR amyloidosis—can guide sonographers to continue evaluating additional features, including the characteristic Bull’s Eye pattern on GLS imaging. This pattern, known for its apical sparing contrasted with reduced strain in the basal segments, presents a hallmark appearance reminiscent of a “cherry on top” and is suggestive of amyloid infiltration. By recognizing these patterns, sonographers can effectively alert the interpreting physician, prompting a more thorough assessment of the patient’s clinical history and potential recommendation for further testing to confirm or rule out cardiac amyloidosis, a diagnosis that may otherwise be missed. Early diagnosis is critical for patients, as cardiac amyloidosis is a fatal disease with a significantly shortened lifespan if not treated promptly. Sonographers are often the first to encounter these patients, and through careful echocardiographic evaluation, can raise suspicion of the disease. By increasing awareness of the dangers associated with this condition and recognizing our profound ability to contribute to its diagnosis, sonographers can play a pivotal role in improving diagnosis and treatment of this illness.