Abstract
This study aimed to explore positron emission tomography-computed tomography (PET-CT) images based on support vector machine (SVM) algorithm for the classification of thyroid nodules (TN) and its evaluation value in postoperative injury rate (PPIR) of recurrent laryngeal nerve (RLN). The parameters of the SVM algorithm were optimized using the particle swarm optimization (PSO) algorithm. A total of 58 patients who were diagnosed with TN by PET/CT at a hospital were divided into a group with benign nodules (group B, 25 cases) and a group with malignant nodules (group M, 33 cases). The characteristics of the PET-CT images and difference in the max standardized uptake value (SUVmax) of PET-CT were analyzed. The PPIR of RLN was calculated. It was found that when the number of iterations was 19, the fitness and the classification accuracy of the SVM algorithm was 98.3% and 91.1%, respectively. When SUVmax = 4.56, its sensitivity and specificity were 81.33% and 76.18%, respectively. The SUVmax of group B was much lower ( P < 0.01 ). It indicated that the established method could realize higher classification accuracy on TN and was of great significance in the evaluation of the PPIR of RLN.
Highlights
thyroid nodules (TN) is a common endocrine system disease second only to diabetes. e incidence rate is relatively high in middle-aged and elderly women, ranking the fifth in female malignancies
Fitness and Accuracy of the support vector machine (SVM) Algorithm. e particle swarm optimization (PSO) algorithm was applied for optimizing the SVM parameters and analyzing the fitness of the optimization algorithm. e
Ese results showed that the positron emission tomography-computed tomography (PET-CT) image classification method established based on the SVM algorithm in this study could avoid the randomness of artificial selection and the error caused by subjectivity in the clinical operation, and it had a good effect on the classification of TN
Summary
TN is a common endocrine system disease second only to diabetes. e incidence rate is relatively high in middle-aged and elderly women, ranking the fifth in female malignancies. E pathogenesis of TN is still unclear It can be classified into two categories: benign and malignant. Differentiation of benign and malignant lesions is of great value for clinical diagnosis, treatment, and prognosis. With the continuous development of medical technology, PET-CT has been widely used in the diagnosis of malignant tumors, but there is still a lot of controversy in the differentiation of benign and malignant TN. The RLN injury is the most common and the most serious complication after the thyroid surgery. Many studies have shown that the PPIR of RLN in patients with benign TN is greatly lower than that of patients with malignant TN [4]
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