{"id":"a4cc12ed4162","type":"article","url":"https://hartvaat.nl/2026/05/13/ai-echo-verslaat-ai-ecg-en-klinische-score-voor-diagnose-cardiale-amyloidose-aur/","title":"AI-Echo verslaat AI-ECG en klinische score voor diagnose cardiale amyloïdose (AUROC 0,93)","title_en":"","category":"hartfalen","category_label":"Hartfalen","professions":["cardioloog"],"tags":["cardiale-amyloidose","echocardiografie","esc-2026","supraventriculaire-tachycardie"],"journal":"Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography","doi":"10.1016/j.echo.2026.05.007","source_url":"https://doi.org/10.1016/j.echo.2026.05.007","authors":["Armin Garmany","Jose K James","Gregorio Tersalvi","Patricia Carey","Christopher G Scott","Will Hawkes","Ashley Akerman","Ross Upton","Angela Dispenzieri","Martha Grogan","Omar F AbouEzzeddine","Patricia A Pellikka"],"significance":7,"published":"2026-06-22","source_date":"2026-05-13","image":"","kennis":["https://hartvaat.nl/kennis/diagnostiek/cardiale-mri/","https://hartvaat.nl/kennis/diagnostiek/intravasculaire-echografie-ivus-oct/"],"congress":"esc-2026","summary_en":"Retrospective cohort study in 598 patients referred for cardiac scintigraphy for suspected transthyretin cardiac amyloidosis (ATTR-CA), comparing three risk models: the ATTR-CM clinical score, AI-ECG, and AI-Echo. Median age 76 years; 30% had confirmed ATTR-CA. AI-Echo performed best: AUROC 0.93 (95% CI 0.91-0.95) versus 0.79 for AI-ECG and 0.87 for the ATTR-CM score (p<0.001). Sensitivity/specificity were 86%/85% (AI-Echo), 80%/64% (AI-ECG), and 86%/69% (clinical score). At a threshold of 0.25, AI-Echo avoided the most unnecessary scintigraphies (45 per 100 referrals vs 24 for AI-ECG and 37 for ATTR-CM). AI-Echo appears the most valuable screening tool for ATTR-CA in high-risk populations and may prevent unnecessary nuclear imaging.","created":"2026-07-03T10:33:05Z","updated":"2026-08-10T11:07:51Z","licence":"Citeer vrij, met bronvermelding en een link naar hartvaat.nl (de url van het record). Samenvattingen zijn redactioneel werk van HartVaat; de oorspronkelijke publicaties blijven van hun uitgevers (doi). Geen medisch advies.","body_markdown":"Retrospectieve cohortstudie bij 598 patiënten verwezen voor cardiale scintigrafie voor verdenking transthyretine-cardiale amyloïdose (ATTR-CA), waarin drie risico-modellen werden vergeleken: de ATTR-CM klinische score, AI-ECG en AI-Echo. Mediane leeftijd 76 jaar; 30% had bewezen ATTR-CA. AI-Echo presteerde superieur: AUROC 0,93 (95%-BI 0,91-0,95) versus 0,79 voor AI-ECG en 0,87 voor ATTR-CM score (p<0,001). Sensitiviteit/specificiteit waren respectievelijk 86%/85% (AI-Echo), 80%/64% (AI-ECG) en 86%/69% (klinische score). Bij een drempel van 0,25 vermeed AI-Echo de meeste onnodige scintigrafieën (45 per 100 verwezen patiënten, tegenover 24 voor AI-ECG en 37 voor ATTR-CM). AI-Echo lijkt het meest waardevolle screeningsinstrument voor ATTR-CA in een hoog-risicopopulatie en kan onnodige nucleaire beeldvorming voorkomen.","abstract_original":"BACKGROUND: To improve screening for cardiac amyloidosis (CA), several models using artificial intelligence (AI) and conventional statistics have been developed. However, few data are available to compare the relative utility of these tools. In this study, models were compared to determine their potential roles in optimizing diagnostic algorithms. METHODS: In this retrospective cohort study at our tertiary medical center, patients referred for cardiac scintigraphy for detection of transthyretin CA (ATTR-CA) who had ECG and transthoracic echocardiography within 6 months along with clinical characteristics for risk score calculation were included. The performance of previously developed and validated clinical and AI risk models for ATTR-CA, including the transthyretin ATTR-CM clinical score and AI models applied to electrocardiography (AI-ECG) and echocardiography (AI-Echo) were compared in a population referred for cardiac scintigraphy. Previously defined thresholds were used for each model. As the ATTR-CM score was validated following exclusion of AL amyloidosis, 28 patients with AL amyloidosis were excluded. AL and ATTR-CA were defined per guideline criteria. RESULTS: Among 598 patients (median age 76 [67-82] years; 72.6% male), 181 (30%) had ATTR-CA. AI-Echo identified ATTR-CA with 86% sensitivity and 85% specificity, compared to 80% and 64% for AI-ECG, and 86% and 69% for the ATTR-CM score. AUROC was 0.93 (95% CI 0.91-0.95) for AI-Echo, 0.79 (0.76-0.83) for AI-ECG, and 0.87 (0.84-0.90) for ATTR-CM score, p < 0.001). In this cohort, use of AI-Echo could have avoided more unnecessary scintigraphy than AI-ECG or ATTR-CM score (45 vs 24 vs 37, per 100, respectively) at a threshold probability of 0.25 (one case of ATTR-CA per 4 referrals for scintigraphy). CONCLUSION: Within a high-risk population for cardiac amyloidosis, the AI-Echo model demonstrated superior diagnostic discrimination and clinical utility for identification of ATTR-CA compared with the AI-ECG model and the ATTR-CM clinical score."}