The galea fascia flap in orbital reconstruction: innovative harvest technique.

AIM: To report the treatment of a recurrent adenoid-cystic carcinoma of the lacrimal gland required orbital exenteration with an en bloc resection of the lateral orbital rim and wall and an anterior portion of the temporal muscle. Reconstruction was planned with both the objectives of a shortened healing time for faster epithetic reconstruction and no visible scars. METHOD: After a cranially extended temporal approach, the dissection of the superficial galea layer was connected with the subcutaneous dissection of the upper and lower eyelid after subciliary incisions. RESULTS: Ample exposure of the temporal, frontal and orbital region was obtained, facilitating the orbital exenteration with en bloc resection of the lateral orbital rim and wall and the anterior portion of the temporal muscle. The epithelialization of the eye socket covered with the galea fascia flap was accelerated, providing faster epithetic reconstruction, without visible scars. CONCLUSIONS: Healing time is accelerated, providing faster epithetic rehabilitation without visible scars, which is important in the postoperative rehabilitation ladder after eye exenteration for both patient and surgeon. Further more ablative surgery within this region gets safer and easier due to the ample exposure of this innovative surgical technique. Further evaluation of the effectiveness and safety of this new approach is advisable.     

CT appearances of hydatid disease at various locations

Hydatid disease has characteristic imaging features on CT, which allow accurate preoperative diagnosis in most cases. However, when it occurs at unusual locations the diagnosis is often difficult, especially as the imaging appearance varies at different sites. In this article we have presented a pictorial review of the CT features of disease due to Echinococcus granulosus at various sites in the human body.     

Bayesian estimation of a random effects heteroscedastic probit model

Summary Bayesian analysis is given of a random effects binary probit model that allows for heteroscedasticity. Real and simulated examples illustrate the approach and show that ignoring heteroscedasticity when it exists may lead to biased estimates and poor prediction. The computation is carried out by an efficient Markov chain Monte Carlo sampling scheme that generates the parameters in blocks. We use the Bayes factor, cross‐validation of the predictive density, the deviance information criterion and Receiver Operating Characteristic (ROC) curves for model comparison.