Using Artificial Intelligence for the Detection of Respiratory Diseases Associated With Pollution (SmartLungs)
Generating a picture at the city level, through geospatial and temporal grouping a lung diseases associated or exacerbated by pollution (COPD, AB and neoplasm pulmonary or pleural) and correlating this data with pollution data.
Development of an accurate and prognostic HRCT imaging diagnostic tool, computer assisted in the mentioned pathology, by generating an algorithm capable of to detect early the follow-up tomographic imaging lesions, as well as to evaluate objective their speed of evolution.
Validation of the proposed algorithm by comparison with medical diagnosis.
Study Overview
Status
Conditions
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
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Timis
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Timisoara, Timis, Romania
- "Victor Babes" University Hospital
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients must be diagnosed with COPD and/or asthma and/or pulmonary neoplasm and/or secondary pulmonary, pleural or mediastinal determinations, suspected or confirmed, according to ICD-10.
- Patients will be included regardless of the type of hospitalization, continuous or day.
- The existence of freely expressed consent, carried out according to Ethics standards professional (from the observation sheet).
For stage 2
- The use of HRCT images, in DICOM format, with a maximum cup thickness of 1.5 mm and with an average of 250 cups; no image acquisition errors;
- Imaging monitoring at a time interval;.
- Respiratory function evaluation data available: spirometry +/- the factor of gaseous diffusion (DLco);
Exclusion Criteria:
For both stages:
- Patients who do not have a stable real domicile (eg social cases) or are not from the Timis county
For stage 2
- Patients who do not have HRCT images available or cannot be followed.
- Patients who have insufficient quality HRCT images.
- Patients who have a history of lung surgery.
- Patients who have a history of allergies to contrast agents used in imaging HRCT.
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Correlation between lung diseases and pollution
Time Frame: December 2023 - December 2024
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Establishing the relationship between the incidence and exacerbation of lung diseases (COPD, acute bronchitis, and pulmonary or pleural neoplasms) and pollution levels through geospatial and temporal analysis at the city /county level
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December 2023 - December 2024
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Development of a diagnostic algorithm
Time Frame: September 2024 - March 2024
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Creating an accurate, computer-assisted HRCT imaging diagnostic tool designed to detect early tomographic lesions and evaluate the progression speed of these lesions in patients with the mentioned pathologies.
|
September 2024 - March 2024
|
Collaborators and Investigators
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- PostdocTrusculescu/11.2023
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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