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.