This study is being conducted to collect image data and relevant clinical data from medical records of patients with suspicion of lung consolidation or pleural effusion. The information will be used to test the performance of Artificial Intelligence (AI) in identification of features associated with the above lung conditions.
This is a prospective, observational, multi-center, post-market clinical study. Enrollment will continue (up to a maximum of 500 adult subjects and up to 300 pediatric subjects) until diagnostic LUS exams are acquired for each of the following groups: Approximately 500 Adult subjects targeting: * Approximately 175 exams from patients positive for lung consolidation * Approximately 175 exams from patients positive for pleural effusion * Approximately 150 exams from patients negative for both conditions Approximately 300 pediatric subjects targeting: * Approximately 150 exams from patients positive for lung consolidation * Approximately 150 exams from patients negative for lung consolidation
Study Type
OBSERVATIONAL
Enrollment
554
Ultrasound scan of subjects in up to 14 lung zones
Arizona Emergency Medical Research Center
Tucson, Arizona, United States
University of Colorado Hospital
Aurora, Colorado, United States
Yale School of Medicine
New Haven, Connecticut, United States
Beth Israel Deaconess Medical Center
Boston, Massachusetts, United States
The study data will be used to support future performance assessments for Artificial Intelligence based algorithms as described by FDA guidance for Computer Assisted Detection and Diagnostic Devices
Time frame: Discharge up to 30 days (Single visit)
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Prisma Health Greenville Memorial Hospital
Greenville, South Carolina, United States