Publication:

Endoscopic thyroidectomy-axilla breast approach: the experience of 26 cases

Background Conventional thyroidectomy results in transverse scar formation on neck. These scars are uncomfortable and cosmetically unacceptable. Endoscopic thyroidectomy is widely accepted technique in specialized centers. The potential advantages of endoscopic technique include better cosmetic result, decreased hospital stay and better patient comfort. Author started performing endoscopic thyroidectomy at the centre to demonstrate the feasibility of operating thyroid gland endoscopically by axilla breast approach.

Methods Author performed 26 cases of endoscopic thyroidectomy by axilla breast approach from June 2014 to July 2017 in patients presenting with indication for surgical thyroid excision. Author did hemithyroidectomy in 19 patients, total thyroidectomy in 3 patients and near total thyroidectomy in 4 patients. All patients underwent endoscopic thyroidectomy by axilla breast approach by creating subplatysmal space with carbon dioxide insufflation at the pressure of 8 to 10mmHg. Results were compared with the recent studies with comparable number of patients.

Results Author did hemithyroidectomy in 19 patients, total thyroidectomy in 3 patients and near total thyroidectomy in 4 patients. Mean Operative time was 88.19 min. But last 6 cases were completed in 49.60±4.20 min. Thus, as experience increased we tend to complete procedure in progressively lesser time period. Mean blood loss in the series was 21.88ml. Mean Hospital stay was 2.88 days (range 2-5 days). Scar satisfaction on visual analogue scale after 3 months of operation was 9.11. Histopathological examination revealed adenomatous goitre in 24 cases and follicular adenoma in 2 cases.

Conclusions Endoscopic thyroidectomy via axilla breast approach is safe, feasible and minimally invasive surgical method for thyroid diseases, with good post-operative results. Surgeons having adequate training in endoscopic surgery can perform endoscopic thyroidectomy with short learning curve.