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Abstract #2886

Based on ADC histogram for distinguishing benign and malignant thyroid nodules: A small FNA-indeterminate cohort exploratory investigation

Xinying Ren1, Huang Junhao1, Ren Huanhuan1, Liu Daihong1, and Huang Weiting2
1Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China, 2Lanzhou University, Lanzhou, China

Synopsis

Keywords: Cancer, Diagnosis/Prediction

Motivation: In clinical practice, there are still some patients with uncertain FNA results and difficult to decide on the next treatment plan

Goal(s): Use routine MRI sequences and simple model to supplement ultrasound TIRADS standards results assist clinicians in preoperative decision-making

Approach: The ADC images histogram features combined with MRI morphological features to construct a regression model to determine the benign and malignant thyroid nodules. The results were compared with TIRADS standards

Results: The ADC-morphological feature model had great diagnostic performance in distinguishing Identifying the benign or malignant thyroid nodules (AUC 0.91).It shown higher specificity (84.2%) than that of the TIRADS (61.90%)

Impact: The prediction model based on ADC and morphological features shows a higher specificity than ultrasound TIRADS standards. ADC parameter histogram features can evaluate the benign and malignant nodules, especially nodules with uncertain FNA, assist clinicians in reducing unnecessary biopsy rates.

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