Pattern recognition of benign nodules at ultrasound of the thyroid: which nodules can be left alone?
OBJECTIVE
The purpose of this study was to evaluate morphologic features predictive of benign thyroid nodules.


METHODS
From a registry of the records of 1,232 fine-needle aspiration biopsies performed jointly by the cytology and radiology departments at a single institution between 2005 and 2007, the cases of 650 patients were identified for whom both a pathology report and ultrasound images were available. From the alphabetized list generated, the first 500 nodules were reviewed. We analyzed the accuracy of individual sonographic features and of 10 discrete recognizable morphologic patterns in the prediction of benign histologic findings.


RESULTS
We found that grouping of thyroid nodules into reproducible patterns of morphology, or pattern recognition, rather than analysis of individual sonographic features, was extremely accurate in the identification of benign nodules. Four specific patterns were identified: spongiform configuration, cyst with colloid clot, giraffe pattern, and diffuse hyperechogenicity, which had a 100% specificity for benignity. In our series, identification of nodules with one of these four patterns could have obviated more than 60% of thyroid biopsies.


CONCLUSIONS
Recognition of specific morphologic patterns is an accurate method of identifying benign thyroid nodules that do not require cytologic evaluation. Use of this approach may substantially decrease the number of unnecessary biopsy procedures.
Bonavita
John A
JA
Department of Radiology, Langone Medical Center, New York University School of Medicine, 550 First Ave., New York, NY 10016, USA. john.bonavita@nyumc.org
Mayo
Jason
J
Babb
James
J
Bennett
Genevieve
G
Oweity
Thaira
T
Macari
Michael
M
Yee
Joseph
J
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016606:Thyroid Nodule / Q000000981:diagnostic imaging*; D014463:Ultrasonography; D055815:Young Adult