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Abstract #1305

Development and Validation of an MRI-Based Predictive Model for Preoperative Extrathyroidal Extension in Papillary Thyroid Carcinoma

Biaoling Chen1, Yining Song2, Hao Wang1, Lang Tang3, Xiaoli Xie4, Anwei Mao5, Pu-Yeh Wu6, Qiaohui Chen1, and Bin Song1
1Department of Radiology, Minhang Hospital, Fudan University, Shanghai, China, 2Shanghai Medical College, Fudan University, Shanghai, China, 3Department of Ultrasound, Minhang Hospital, Fudan University, Shanghai, China, 4Department of Pathology, Minhang Hospital, Fudan University, Shanghai, China, 5Department of General Surgery, Minhang Hospital, Fudan University, Shanghai, China, 6GE Healthcare, Beijing, China

Synopsis

Keywords: Diagnosis/Prediction, Diagnosis/Prediction

Motivation: Papillary thyroid carcinoma (PTC) recurrence is common, and extrathyroidal extension (ETE) is a critical prognostic factor affecting treatment.

Goal(s): This study aimed to develop and validate a predictive model for preoperative ETE in PTC patients using MRI features.

Approach: We analyzed 140 confirmed PTC cases. MRI features were evaluated along with clinical data. We identified independent predictors of ETE and developed a predictive nomogram. Predictive performance was assessed.

Results: Age, protrude_value, and ADC_Best_rate independently predicted ETE, with the nomogram showing high accuracy and utility across cohorts, MRI systems, and genders, performing better in males.

Impact: Our nomogram model, incorporating age, protrude_value, and ADC_Best_rate, effectively predicted preoperative ETE in PTC patients, thereby aiding surgeons in optimizing therapeutic decision-making. ADC_Best_rate demonstrated potential as a robust indicator in MRI functional imaging.

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Keywords