Design and Evaluation of Mobile X-ray for Rapid and Accurate Diagnosis of Thoracic Disease
NCT ID: NCT02391896
Last Updated: 2018-10-25
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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TERMINATED
NA
34 participants
INTERVENTIONAL
2015-03-31
2016-12-31
Brief Summary
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Detailed Description
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The investigators group is experienced in investigating DE for lung nodule detection, this theoretical framework was instrumental in optimizing a clinical prototype for high-performance DE chest X-ray. It identified optimal DE image acquisition and decomposition techniques, and validated the approach in comparison to human observer performance. The analysis further demonstrated that - given a high-performance flat plate detector, optimal acquisition and decomposition - DE chest X-ray is possible at the same dose as conventional computer radiography (CR) and digital radiography (DR) chest X-ray, while significantly improving conspicuity of subtle lung nodules by the reduction of overlying background noise. The DE work undertaken by our group is unique in terms of providing a clear theoretical framework for optimizing a clinical prototype for best performance in terms of image quality and patient exposure to ionizing radiation.
Conditions
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Study Design
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RANDOMIZED
SINGLE_GROUP
DIAGNOSTIC
SINGLE
Study Groups
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Digital Tomosynthesis
Patient will get tomosynthesis scan
Dual energy and tomosynthesis xray
Dual energy
Patient will get dual energy scan
Dual energy and tomosynthesis xray
Interventions
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Dual energy and tomosynthesis xray
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
19 Years
ALL
No
Sponsors
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Carestream Health, Inc.
INDUSTRY
University Health Network, Toronto
OTHER
Responsible Party
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Principal Investigators
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Narinder Paul, MD
Role: PRINCIPAL_INVESTIGATOR
UHN
Locations
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Toronto General Hospital, Department of Medical Imaging
Toronto, Ontario, Canada
Countries
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Other Identifiers
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14-7549-CE
Identifier Type: -
Identifier Source: org_study_id
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