Minimally invasive video-assisted thyroid surgery: how can we improve the learning curve?

Objective. Minimally invasive video-assisted thyroidectomy (MIVAT) is a technically demanding procedure and requires a surgical team skilled in both endocrine and endoscopic surgery. A time consuming learning and training period is mandatory at the beginning of the experience. The aim of our report is to focus some aspects of the learning curve of the surgeon who practices video-assisted thyroid procedures for the first time, through the analysis of our preliminary series of 36 cases. Patients and methods. From September 2004 to April 2005 we selected 36 patients for minimally invasive video-assisted surgery of the thyroid. The patients were considered eligible if they presented with a nodule not exceeding 35mm in maximum diameter; total thyroid volume within normal range; absence of biochemical and echographic signs of thyroiditis. We analyzed surgical results, conversion rate, operating time, post-operative complications, hospital stay, cosmetic outcome of the series. Results. We performed 36 total thyroidectomy. The procedure was successfully carried out in 33/36 cases. Post-operative complications included 3 transient recurrent nerve palsies and 2 transient hypocalcemias; no definitive hypoparathyroidism was registered. All patients were discharged 2 days after operation. The cosmetic result was considered excellent by most patients. Conclusions. Advances in skills and technology have enabled surgeons to reproduce most open surgical techniques with video-assistance or laparoscopically. Training is essential to acquire any new surgical technique and it should be organized in detail to exploit it completely.

A Study of the State of the Art of Process Planning for Additive Manufacturing

In the manufacturing industry the term Process Planning (PP) is concerned with determining the sequence of individual manufacturing operations needed to produce a given part or product with a certain machine. In this technical report we propose a preliminary analysis of scientific literature on the topic of process planning for Additive Manufacturing (AM) technologies (i.e. 3D printing). We observe that the process planning for additive manufacturing processes consists of a small set of standard operations (repairing, orientation, supports, slicing and toolpath generation). We analyze each of them in order to emphasize the most critical aspects of the current pipeline as well as highlight the future challenges for this emerging manufacturing technology.