The investigators have previously proposed a prediction model for difficult transoral and submental thyroidectomy through a retrospective study. In order to better promote transoral and submental endoscopic approach for thyroid surgery and to set up an appropriate training course, the investigators aim to renovate and validate the prediction model through a prospective study.

Male sex, age, BMI, neck length and certain thyroid disease such as thyroiditis and hyperthyroidism have been long cited as indicators of a difficult thyroidectomy. The investiagtors hypothesized that neck extension was critical to the exposure and visualization of the surgical field in the endoscopic thyroidectomy. Therefore, several measurements were innovatedly integrated into the prediction model, including neck circumference, thyromental distance, sternomental distance, ratio of height-to-thyromental distance, ratio of height-to-sternomental distance.

Inclusion Criteria:

• Clinical diagnosis of differentiated thyroid cancer with a maximum diameter not exceeding 4 cm
• Clinical diagnosis of benign thyroid nodule with a maximum diameter not exceeding 6 cm
• Absence of suspicious lateral lymph nodes or distant metastases

Exclusion Criteria:

• Participants with fusion or fixation of lymph nodes in the neck
• Participants with history of neck surgery or radiation
• Participants with vocal fold fixation by preoperative fibrolaryngoscope
• Participants with preoperative examination suggestive of extrathyroidal invasion
• Participants with a significantly restricted neck and/or jaw

Patients with FNA proven differentiated thyroid cancer, were willing to undergo thyroidectomy and central lymph node dissection via transoral and submental approach. Patients were well informed about the transoral and submental approach and were aware of the potential benefits and risks. Patient consented for us to use perioperative data.

Data are available on request due to privacy or other restrictions. The data that support the findings of this study are available on request from Ling Zhan. The data are not publicly available due to them containing information that could compromise research participant privacy.