The Feasibility of Florbetapir Quantitation in Europe

Study Overview
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Brief Summary
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This study will evaluate whether the addition of quantitation as an adjunct to visual interpretations significantly improves the accuracy of Amyvid scan interpretation.

Official Title
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A Study to Evaluate the Improvement in Reader Accuracy When Using a Read Method That Incorporates Commercially Available Quantitative Analysis Software as an Adjunct to the Clinical Visual Interpretation of Amyvid Brain Scans

Conditions
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Alzheimer's Disease

Intervention / Treatment
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* Drug: Florbetapir (18F)


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Readers have undergone Amyvid reader training Readers have not more than minimal experience with quantitation of amyloid PET scans Exclusion Criteria: Readers have previously been trained to quantitate amyloid PET scans
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Intervention Model: Single Group Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Physician Readers<br>Physician readers will interpret Amyvid scans using qualitative analysis followed by the use of quantitation. No subjects will be exposed to Florbetapir(18F) as part of this study. | Drug: Florbetapir (18F)<br>* No Florbetapir (18F) will be administered in this study.<br>* Other names: 18F-AV-45;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in Reader Accuracy After Application of Quantitation Software | Evaluate whether the use of quantitation software improves florbetapir (18F) scan interpretation by using the net reclassification index (NRI). The NRI is a prospective measure that quantifies the correctness of upward and downward reclassification or movement of predicted probabilities as a result of adding a new marker. NRI Values >0 indicate an improvement in scan interpretation accuracy and values <0 indicate a decline in scan interpretation accuracy after application of quantitation software. NRI = [P(up,event)-P(down,event)]-[P(up,nonevent)-P(down,nonevent)] Where P(up,event) = # events up/# events P(down,event) = # events down/# events P(up,nonevent) = # nonevents up/# nonevents P(down,nonevent) = # nonevents down/# nonevents and events: true positive case nonevents: true negative case up: scan change from negative to positive down: scan change from positive to negative Only the 46 scans with autopsy from A16 are used for this outcome measure. | Scan acquired 50-60 minutes post injection | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in Scan Interpretation Reliability After Application of Quantitation Software | Evaluate whether the use of quantitation software improves florbetapir (18F) scan interpretation by using the net reclassification index (NRI). The NRI is a prospective measure that quantifies the correctness of upward and downward reclassification or movement of predicted probabilities as a result of adding a new marker. NRI Values >0 indicate an improvement in scan interpretation accuracy and values <0 indicate a decline in scan interpretation accuracy after application of quantitation software. NRI = [P(up,event)-P(down,event)]-[P(up,nonevent)-P(down,nonevent)] Where P(up,event) = # events up/# events P(down,event) = # events down/# events P(up,nonevent) = # nonevents up/# nonevents P(down,nonevent) = # nonevents down/# nonevents and events: true positive case nonevents: true negative case up: scan change from negative to positive down: scan change from positive to negative Only the 46 scans with autopsy from A16 are used for this outcome measure. | Scan acquired 50-60 minutes post injection |