Artificial Intelligence Interpretation of the Electrocardiogram: A State-of-the-Art Review.

PURPOSE OF REVIEW: Artificial intelligence (AI) is transforming electrocardiography (ECG) interpretation. AI diagnostics can reach beyond human capabilities, facilitate automated access to nuanced ECG interpretation, and expand the scope of cardiovascular screening in the population. AI can be applied to the standard 12-lead resting ECG and single-lead ECGs in external monitors, implantable devices, and direct-to-consumer smart devices. We summarize the current state of the literature on AI-ECG. RECENT FINDINGS: Rhythm classification was the first application of AI-ECG. Subsequently, AI-ECG models have been developed for screening structural heart disease including hypertrophic cardiomyopathy, cardiac amyloidosis, aortic stenosis, pulmonary hypertension, and left ventricular systolic dysfunction. Further, AI models can predict future events like development of systolic heart failure and atrial fibrillation. AI-ECG exhibits potential in acute cardiac events and non-cardiac applications, including acute pulmonary embolism, electrolyte abnormalities, monitoring drugs therapy, sleep apnea, and predicting all-cause mortality. Many AI models in the domain of cardiac monitors and smart watches have received Food and Drug Administration (FDA) clearance for rhythm classification, while others for identification of cardiac amyloidosis, pulmonary hypertension and left ventricular dysfunction have received breakthrough device designation. As AI-ECG models continue to be developed, in addition to regulatory oversight and monetization challenges, thoughtful clinical implementation to streamline workflows, avoiding information overload and overwhelming of healthcare systems with false positive results is necessary. Research to demonstrate and validate improvement in healthcare efficiency and improved patient outcomes would be required before widespread adoption of any AI-ECG model.

History of contrast enhanced ultrasound (CEUS).

The 50th year of the European Federation of Societies in Ultrasound in Medicine and Biology (EFSUMB) has been celebrated 2022 publishing articles on the history of US. Contrast enhanced ultrasound (CEUS) allows to visualize blood flow and tissue perfusion. CEUS has proven to be safe without risk of nephrotoxicity. The availability of a contrast agent (tracer) for ultrasound imaging allows for the first time a dynamic assessment of tissue perfusion (blood flow and wash-in/wash-out pattern) which is an essential part for the detection and characterisation of pathological tissue and abnormal organ function. It was an outstanding achievement of academic centers in close cooperation with EFSUMB to investigate and validate the clinical potential of this new technology for the diagnosis and monitoring of various diseases and to develop clinical guidelines based on an in-depth assessment of the existing scientific publications. An important part of the implementation of CEUS in clinical practice was the development of contrast-specific imaging modes on the ultrasound scanners (in close cooperation with the machine manufacturers), the optimization of the machine setups for contrast imaging and the education provided to clinical users in form of workshops, webinars, textbooks and scientific congresses.

Detección y caracterización de lesionesfocales hepáticas con contraste ecográficoen la fase tardía mediante la técnica ADI.Estudio preliminar / Detection and characterization of focal hepatic lesions using contrast-enhanced ultrasound imaging in late phase with ADI Mode. Preliminary study

Objetivo: La técnica ecográfica ADI (agent diagnostic imaging) permite la detección de microburbujas de contraste que se depositan en el parénquima hepático en la fase tardía una vez transcurrida la fase vascular. El objetivo del estudio ha sido evaluar la utilidad de esta técnica en la detección y caracterización de lesiones focales hepáticas. Material y métodos: A 17 pacientes a los que se realizó TC helicoidal por sospecha clínica de metástasis o recidiva tumoral (n = 12) o para estudio de una lesión focal hepática (n = 5), se les realizó ecografía con técnica ADI tras la administración del contraste ecográfico Levovist (SHU 508). Se han comparado los hallazgos obtenidos con la técnica ecográfica ADI con los obtenidos en la ecografía basal y con la TC helicoidal. Resultados: La técnica ADI detectó el 100 por ciento de lesiones focales detectadas por TC. En dos pacientes la ecografía detectó una lesión de 1 cm no detectada en la TC. Comparativamente con la TC, la ecografía basal clasificó las lesiones correctamente como malignas o benignas en el 71,4 por ciento de los casos (10/14 lesiones) mientras que la técnica ADI lo hizo en el 92,8 por ciento (13/14 lesiones), lo que implica un incremento del 21,4 por ciento en el rendimiento diagnóstico con respecto a la ecografía basal. Conclusiones: La técnica ADI en la fase tardia es útil en la diferenciación entre malignidad y benignidad de lesiones focales hepáticas permitiendo incrementar el rendimiento diagnóstico de la ecografía basal (AU)