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Recruiting NCT05140889

NCT05140889 Integrating Deep Learning CT-scan Model, Biological and Clinical Variables to Predict Severity of Asthma in Children

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Clinical Trial Summary
NCT ID NCT05140889
Status Recruiting
Phase
Sponsor Fondazione IRCCS Policlinico San Matteo di Pavia
Condition Asthma in Children
Study Type OBSERVATIONAL
Enrollment 25 participants
Start Date 2021-01-20
Primary Completion 2026-06-30

Eligibility & Interventions

Sex All sexes
Min Age 6 Years
Max Age 17 Years
Study Type OBSERVATIONAL

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 25 participants in total. It began in 2021-01-20 with a primary completion date of 2026-06-30.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief Summary

Artificial intelligence (AI) offers substantial opportunities for healthcare, supporting better diagnosis, treatment, prevention and personalized care. Analysis of health images is one of the most promising fields for applying AI in healthcare, contributing to better prediction, diagnosis and treatment of diseases. Deep learning (DL) is currently one of the most powerful machine learning techniques. DL algorithms are able to learn from raw (or with little pre-processing) input data and build by themselves sophisticated abstract feature representations (useful patterns) that enable very accurate task decision making. Recently, DL has shown promising results in assisting lung disease analysis using computed tomography (CT) images. Current severe asthma guidelines recommend high-resolution and multidetector CT as a tool for disease evaluation. CT scans contain prognostic information, as the presence of bronchial wall thickening, air trapping, bronchial luminal narrowing, and bronchiectasis are associated with longer disease duration and disease severity in adults. Only a small number of studies have reported chest CT findings in children with severe asthma, and their relationship to clinical and pathobiological parameters yielded inconsistent results. Thus, to which extent CT scans add prognostic information beyond what can be inferred from clinical and biological data is still unresolved in children. The project is expected to build an DL-severity score to prognoses severe evolution for children with asthma, using a DL model to capture CT scan prognosis information.

Eligibility Criteria

Inclusion Criteria: * age 6-17 years * confirmed diagnosis of severe asthma according to ERS/ATS guidelines Exclusion Criteria: * other diseases that may mimic asthma according to ERS/ATS guidelines (i.e., cystic fibrosis, primary ciliary dyskinesia, tracheobronchomalacia, etc)

Contact & Investigator

Central Contact

Amelia Licari, MD

✉ a.licari@smatteo.pv.it

📞 +39(0)382502629

Principal Investigator

Amelia Licari, MD

PRINCIPAL INVESTIGATOR

IRCCS Policlinico San Matteo

Frequently Asked Questions

Who can join the NCT05140889 clinical trial?

This trial is open to participants of all sexes, aged 6 Years or older, up to 17 Years, studying Asthma in Children. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT05140889 currently recruiting?

Yes, NCT05140889 is actively recruiting participants. Contact the research team at a.licari@smatteo.pv.it for enrollment information.

Where is the NCT05140889 trial being conducted?

This trial is being conducted at Pavia, Italy.

Who is sponsoring the NCT05140889 clinical trial?

NCT05140889 is sponsored by Fondazione IRCCS Policlinico San Matteo di Pavia. The principal investigator is Amelia Licari, MD at IRCCS Policlinico San Matteo. The trial plans to enroll 25 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: April 2026  ·  Data Methodology