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Neuroradiology

E3109. Innovating TIRADS v2017: A Practical and Novel Guide for Structural Template Reporting

Chua S,  Xu K,  Matta E,  Chandrasekhar C. The University of Texas Health Science Center at Houston, Houston, TX

Address correspondence to S. Chua (Steven.S.Chua@uth.tmc.edu)

Background Information: Thyroid ultrasound offers a fast and effective means of evaluating thyroid nodules. However, we are often faced with the conundrum of tedious description and management of fine-needle aspiration (FNA) of these nodules, many of which tend to be benign, and if malignant, tend to be slow growing. To obviate the need for unnecessary thyroid FNAs, the thyroid imaging and reporting system (TIRADS) was developed by the American College of Radiology (ACR) and is more widely accepted. Here, we present a novel means of reporting thyroid nodules using an optimized and streamlined template for reporting to achieve this goal.

Educational Goals/Teaching Points: Participants will comprehend the key suspicious sonographic features of TIRADS applied to the reporting of thyroid nodules. We illustrate key morphological features of benign versus malignant nodules. We develop an innovative structural reporting template for thyroid nodules, which allows the user to semiautomate and score the TIRADS features to risk-stratify the nodules.

Key Anatomic/Physiologic Issues and Imaging Findings/Techniques: Key issues include recognizing the key suspicious sonographic features of nodules used for scoring in TIRADS, which include composition, echogenicity, shape, margin and echogenic foci; delineating the salient morphologic features of worrisome nodules; and incorporating these key features into a structured template to optimize nodule characterization.

Conclusion: Using TIRADS, we can stratify thyroid nodules based on a scoring system to determine their malignant and suspicious sonographic features to determine the need for FNA versus follow-up. Nodules are selected based on suspicious features like size, solid nature, and echogenic foci. Next, we apply a semiautomated novel template to risk-stratify these nodules under TIRADS, whereby each morphological characteristic is examined, and the user can select a specific parameter under the morphological characteristic to arrive at an aggregated TIRADS score. Based on the TIRADS score, we can apply built-in ACR recommendations to render disposition of that nodule. We strongly believe our template system offers an accurate and efficient means of reporting thyroid nodules to offer the best benefit for the patient by obviating the need for unnecessary FNAs by appropriately risk-stratifying the thyroid nodules.