Ignite Creation Date:
2024-10-26 @ 3:39 PM
Last Modification Date:
2024-10-26 @ 3:39 PM
Study NCT ID:
NCT06576232
Status:
COMPLETED
Last Update Posted:
None
First Post:
2024-08-23
Brief Title:
Standalone Observational Study Assessing the Performance of an AIML Tech-based SaMD on Chest LDCT Images REALITY
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Multinational Multicenter Retrospective Study to Evaluate an AIML Technology-Based End-to-End CADeCADx SaMD Which Allows Detection Localization and Characterization of Pulmonary Nodules REALITY
Status:
COMPLETED
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
REALITY
Brief Summary:
This is a Multinational Multicenter retrospective study for the evaluation of the standalone efficacy and safety of an Artificial IntelligenceMachine Learning AIML technology-based end-to-end Computer assisted DetectionComputer Assisted Diagnosis CADeCADx Software as a Medical Device SaMD developed to detect localize and characterize malignant and suspicious for lung cancer nodules on Low Dose Computed Tomography LDCT scans taken as part of a Lung Cancer Screening LCS program
LDCT Digital Imaging and Communications in Medicine DICOM images of patients who underwent lung cancer screening were selected and included into the study Selected scans will then be analyzed by the CADeCADx SaMD and compared to radiologist generated reference standards including lesions localization and lesion cancer diagnosis
Figures of merit at patient level and lesion level detection and diagnostic efficacy will be calculated as well as sub-class analysis to ensure algorithm performance generalizability
LDCT Digital Imaging and Communications in Medicine DICOM images of patients who underwent lung cancer screening were selected and included into the study Selected scans will then be analyzed by the CADeCADx SaMD and compared to radiologist generated reference standards including lesions localization and lesion cancer diagnosis
Figures of merit at patient level and lesion level detection and diagnostic efficacy will be calculated as well as sub-class analysis to ensure algorithm performance generalizability
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None