Add like
Add dislike
Add to saved papers

An Automatable Method for Determining Adequacy of Thyroid Fine-Needle Aspiration Samples.

CONTEXT.—: Thyroid nodules are a common clinical problem. Cytologic evaluation via fine-needle aspiration is often employed in the diagnostic workup, and rapid on-site assessment of adequacy can help ensure an adequate sample is obtained. However, rapid on-site assessment of adequacy only examines part of the sample, a part that may not then be available for ancillary testing. Moreover, the procedure is time-consuming and poorly reimbursed.

OBJECTIVE.—: To develop an automatable fluorescence-based image analysis system for assessing the adequacy of thyroid fine-needle aspirations that uses the entire aspirated sample.

DESIGN.—: There were 12 previously diagnosed cases that served as a training set, and 11 cases were used for validation of an image analysis algorithm. The samples were fluorescently stained and imaged using a fluorescent microscope. The images were assessed for adequacy by an image analysis algorithm. Following image analysis, a ThinPrep slide was prepared and blindly scored by a cytopathologist. The standard and computer-derived results were then compared.

RESULTS.—: The algorithm was optimized using the 12 cases in the training set and then applied to the 11 test cases. A total of 8 of 8 adequate samples in the test group were correctly scored as adequate, and 2 of 3 cases that were inadequate were correctly scored as inadequate by the algorithm. One case was erroneously designated as not adequate by the algorithm.

CONCLUSIONS.—: Our results demonstrate the feasibility of automating thyroid adequacy assessment using a fluorescent labeling technique followed by computer image analysis.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app