Artificial Intelligence in Clinical Echocardiography: Many Expectations, but Deep Uncertainties for Defining Strategies to Overcome Difficulties and Obstacles: Authors’ Reply

Tseng, Andrew; Lopez‐Jimenez, Francisco; Pellikka, Patricia A.

doi:10.1016/j.echo.2022.09.009

Cited by 1 publication

(6 citation statements)

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“…5 However, AI-enhanced software improvement and contribution might be helpful in the next future. [5][6][7][8]…”

Section: Discussionmentioning

confidence: 99%

“…In the absence of applicability in a larger clinical context, the risk of making the echocardiography progress limited to research laboratories increases 5 . However, AI‐enhanced software improvement and contribution might be helpful in the next future 5–8 …”

Section: Discussionmentioning

confidence: 99%

“…3 Moreover, artificial intelligence (AI)-assisted echocardiography may represent another tool in order to improve the reproducibility. [5][6][7] Interestingly, European Society of Cardiology guidelines classification of heart failure (HF) is based on EF for defining the three groups with preserved, mildly reduced, or reduced EF. 4 In the field of HF, EF is currently used to select specific populations under study in clinical practice, and follow the clinical course trajectory of individual subjects as well, who can change their EF overtime.…”

Section: Efmentioning

confidence: 99%

“…Optimizing image quality and frame rate is crucial 3 . Averaged GLS measurements should be made in standard apical long‐axis 4C, three‐chamber (3C), and 2C views, 2,3 and generally calculated using midwall deformation, 3 also with AI‐enhanced software if available/feasible 5–7 . 3D ST could eliminate the problem of through‐plane myocardial motion, inherent characteristic of 2D imaging, taking into account that 3D strain is currently limited by low frame rates 3 .…”

Section: From Pathophysiological Considerations To Clinical Applicati...mentioning

confidence: 99%

“…If available, 3‐dimensional (3D)‐based LV EF evaluation may be accurate and reproducible, in the presence of good ultrasound window, taking into account the lower temporal resolution as well 3 . Moreover, artificial intelligence (AI)‐assisted echocardiography may represent another tool in order to improve the reproducibility 5–7 …”

Section: From Pathophysiological Considerations To Clinical Applicati...mentioning

confidence: 99%

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From ejection fraction, to myocardial strain, and myocardial work in echocardiography: Clinical impact and controversies

Dell'Angela,

Nicolosi

2024

Echocardiography

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Enhancing an echocardiographic tool, aimed to detect even subtle left ventricular (LV) systolic function abnormalities, capable of obtaining both early diagnosis and risk prediction of heart disease, represents an ambitious, attractive, and arduous purpose in the modern era of cardiovascular imaging. Ideally, that tool should be simple, reliable, and reproducible, in order to be concretely applied in routine clinical practice. Importantly, that technique should be physiologically plausible and useful both at the population‐level, as well as in the individual subject. For a long time, LV ejection fraction (EF) has been considered the first‐line parameter for assessing LV global systolic function, strictly related to the prognosis, at least in some settings. However, LV EF limitations are well‐known, even though frequently overemphasized, including its load‐dependency. Therefore, myocardial strain techniques have been proposed, deemed able to disclose even subtle early LV function anomalies. Nevertheless, many disadvantages of myocardial strain have been reported as well. More recently, myocardial work (MW) analysis has been introduced as a new echocardiographic tool for the evaluation of LV global systolic function, attempting to overcome EF and strain disadvantages. However, MW has shown many limits as well. Notwithstanding, LV EF still remains a landmark functional classification marker for heart failure and cardiac oncology, allowing reliable fast reassessment of LV function changes during patient management, in order to guide treatment in individual cases as well. Notably, global longitudinal strain and MW parameters seem to show better meaningful results at the population‐level, but controversial clinical impact, major limitations, wide cut‐offs spread and overlap, when the single value needs to be applied to the single case. Taking into account the recent literature‐based evidence, the scope of the present narrative critical review is trying to delineate the different types of information given by the described LV global systolic function parameters, both at the population‐level and in the individual case, in order to trace a comparative analysis of advantages and limitations in clinical practice.

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“…5 However, AI-enhanced software improvement and contribution might be helpful in the next future. [5][6][7][8]…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Efmentioning

confidence: 99%

Section: From Pathophysiological Considerations To Clinical Applicati...mentioning

confidence: 99%

Section: From Pathophysiological Considerations To Clinical Applicati...mentioning

confidence: 99%

See 3 more Smart Citations

From ejection fraction, to myocardial strain, and myocardial work in echocardiography: Clinical impact and controversies

Dell'Angela,

Nicolosi

2024

Echocardiography

View full text Add to dashboard Cite

show abstract

Artificial Intelligence in Clinical Echocardiography: Many Expectations, but Deep Uncertainties for Defining Strategies to Overcome Difficulties and Obstacles: Authors’ Reply

Cited by 1 publication

References 4 publications

From ejection fraction, to myocardial strain, and myocardial work in echocardiography: Clinical impact and controversies

From ejection fraction, to myocardial strain, and myocardial work in echocardiography: Clinical impact and controversies

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