Diagnostic Accuracy of a Deep Learning-Based Software for Automated Multiparametric Echocardiographic Measurements (PANECHO)
27. juli 2026 oppdatert av: Centro Cardiologico Monzino
PANECHO: Diagnostic Accuracy of a Deep Learning-Based Artificial Intelligence Software Developed for Automated Multiparametric Echocardiographic Measurements From Echocardiographic Video Images: A Multicenter Study of the Italian Society of Echocardiography and Cardiovascular Imaging (SIECVI)
Transthoracic echocardiography is an essential imaging modality for the diagnosis and follow-up of cardiovascular diseases.
Comprehensive echocardiographic assessment requires multiple quantitative measurements of cardiac structure and function, which are time-consuming and highly dependent on operator expertise.
US2.AI (Us2.v1) is an artificial intelligence (deep learning)-based software designed to automatically analyze standard two-dimensional and Doppler echocardiographic DICOM video clips acquired from different ultrasound vendors.
The software provides automated measurements of cardiac morphology and function, including chamber dimensions and volumes, left and right ventricular systolic and diastolic function, myocardial strain, and Doppler-derived parameters, generating a comprehensive echocardiographic report based on current international guideline recommendations.
In addition, the software may assist in identifying echocardiographic features suggestive of several cardiovascular conditions, including heart failure, pulmonary hypertension, hypertrophic cardiomyopathy, cardiac amyloidosis, valvular heart disease, and ischemic cardiomyopathy.
Studieoversikt
Status
Rekruttering
Detaljert beskrivelse
This is a non profit, prospective, multicenter observational study aimed at evaluating the diagnostic accuracy of the US2.AI software by comparing its automated echocardiographic measurements with measurements performed by experienced echocardiographers, considered the reference standard.
The study will assess the agreement between automated and expert-derived measurements and determine the reliability of the software in routine clinical practice. Demonstrating high diagnostic accuracy may support the use of artificial intelligence to standardize echocardiographic measurements and facilitate comprehensive image analysis, particularly in settings where advanced analysis tools or highly experienced operators are not readily available.
Studietype
Observasjonsmessig
Registrering (Antatt)
1157
Kontakter og plasseringer
Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.
Studiekontakt
- Navn: Laura Fusini, MD
- Telefonnummer: +39 0258002909
- E-post: laura.fusini@cardiologicomonzino.it
Studiesteder
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Lombardy
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Milan, Lombardy, Italia, 20132
- Rekruttering
- Centro Cardiologico Monzino, IRCCS
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Ta kontakt med:
- Chiara Centenaro
- Telefonnummer: +39 0258002031
- E-post: chiara.centenaro@cardiologicomonzino.it
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Deltakelseskriterier
Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
- Voksen
- Eldre voksen
Tar imot friske frivillige
Nei
Prøvetakingsmetode
Ikke-sannsynlighetsprøve
Studiepopulasjon
Consecutive adult patients undergoing clinically indicated standard transthoracic echocardiography at seven high-volume echocardiography laboratories with experienced operators.
Beskrivelse
Inclusion Criteria:
- Adults aged 18 years or older.
- Undergoing clinically indicated standard transthoracic echocardiography.
- Adequate echocardiographic image quality for automated and expert analysis.
- Written informed consent provided prior to study participation.
Exclusion Criteria:
- Age <18 years.
- Frequent and/or complex cardiac arrhythmias during echocardiographic examination.
- Suboptimal echocardiographic images.
Studieplan
Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.
Hvordan er studiet utformet?
Designdetaljer
Kohorter og intervensjoner
Gruppe / Kohort |
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Prospective Cohort
Consecutive adult patients referred for clinically indicated standard transthoracic echocardiography at seven high-volume echocardiography laboratories will be enrolled.
Echocardiographic examinations will be performed according to routine clinical practice by experienced operators.
Standard two-dimensional, Doppler, and other clinically indicated measurements required for the diagnostic report will be obtained manually by expert echocardiographers and automatically by the artificial intelligence software (US2.AI).
No additional study-specific imaging procedures or follow-up visits are planned.
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Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
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Agreement between AI-derived and expert-derived echocardiographic measurements across predefined patient subgroups
Tidsramme: January 2027
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Comparison of the agreement between automated and expert-derived measurements in predefined subgroups, including participants with normal echocardiographic findings and those with specific cardiovascular diseases.
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January 2027
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Agreement between AI-derived and expert-derived echocardiographic measurements
Tidsramme: Jan 2027
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Agreement between automated echocardiographic measurements generated by the US2.AI software and manual measurements performed by experienced echocardiographers (reference standard) across standard two-dimensional, Doppler, and strain parameters.
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Jan 2027
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Time required for echocardiographic analysis
Tidsramme: January 2027
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Comparison of the time required to obtain a complete set of echocardiographic measurements using manual analysis by experienced echocardiographers versus automated analysis by the US2.AI software.
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January 2027
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Sekundære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
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Agreement between AI-assisted and expert final echocardiographic diagnoses
Tidsramme: January 2027
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Agreement between the final echocardiographic diagnosis suggested by the US2.AI software and the final diagnosis reported by the expert echocardiographer.
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January 2027
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Samarbeidspartnere og etterforskere
Det er her du vil finne personer og organisasjoner som er involvert i denne studien.
Sponsor
Studierekorddatoer
Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.
Studer hoveddatoer
Studiestart (Faktiske)
27. april 2026
Primær fullføring (Antatt)
31. januar 2027
Studiet fullført (Antatt)
31. januar 2027
Datoer for studieregistrering
Først innsendt
27. juli 2026
Først innsendt som oppfylte QC-kriteriene
27. juli 2026
Først lagt ut (Faktiske)
31. juli 2026
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
31. juli 2026
Siste oppdatering sendt inn som oppfylte QC-kriteriene
27. juli 2026
Sist bekreftet
1. juli 2026
Mer informasjon
Begreper knyttet til denne studien
Andre studie-ID-numre
- L2-309
Legemiddel- og utstyrsinformasjon, studiedokumenter
Studerer et amerikansk FDA-regulert medikamentprodukt
Nei
Studerer et amerikansk FDA-regulert enhetsprodukt
Nei
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