Ultrasound Image under Artificial Intelligence Algorithm in Thoracoscopic Surgery for Papillary Thyroid Carcinoma

Abstract

This study aimed to investigate the therapeutic effect of thoracoscopic thyroidectomy guided by an ultrasound image based on an artificial intelligence algorithm on papillary thyroid carcinoma. Patients diagnosed with papillary thyroid carcinoma by imaging examination or needle biopsy in hospital were selected. The subjects were randomly divided into the experimental group and the control group. In the experimental group, 94 patients underwent conventional thoracoscopic thyroid tumor resection. In the control group, 119 patients underwent thoracoscopic thyroidectomy under ultrasonic guidance based on an intelligent algorithm. The adoption effect of ultrasound imaging based on the least variance algorithm in thoracoscopic papillary thyroid carcinoma surgery was evaluated by comparing the differences between the two groups of patients after laparoscopic thyroidectomy. The results showed that the ultrasonic imaging resolution and sound-absorbing spot imaging effect based on an artificial intelligence algorithm were superior to those of conventional ultrasonic imaging. Compared with the control group, the average duration of surgery in the experimental group was reduced and the intraoperative blood loss, postoperative cumulative drainage volume, postoperative drainage tube duration, hospital stay, and pain evaluation were dramatically better (P<0.05). It was confirmed that ultrasound-guided endoscopic thyroid surgery based on the least variance algorithm had better results than conventional surgery and showed the same safety as traditional surgery, which was of clinical promotion value. However, some evaluations were influenced by subjective judgment, and the accuracy of data conclusions needed to be further studied.