Appendiceal mucocele is a rare cause of acute abdomen. Mucinous appendiceal neoplasms represent 0.2–0.7% of all appendix specimens. The aim of this study is to report a case of a mucinous appendiceal neoplasm presented as acute appendicitis, discussing the clinical and surgical approach in the emergency setting. A 72-year-old female patient was admitted to the emergency department with a clinical examination indicative of acute abdomen. The patient underwent abdominal computed tomography scan which revealed a cystic lesion in the right iliac fossa measuring 8.3 × 5.2 × 4.1 cm, with calcified walls, and a mean density indicative of high protein content. The patient was taken to the operating room and a right hemicolectomy was performed. The postoperative course was unremarkable. The histopathological examination revealed a low-grade mucinous appendiceal neoplasm with negative regional lymph nodes. Ultrasound and CT are useful in diagnosing appendiceal mucocele and synchronous cancers in the emergency setting. The initial operation should include appendectomy and resection of the appendicular mesenteric fat along with any fluid collection for cytologic examination. During urgent appendectomy it is important to consider every mucocele as malignant in order to avoid iatrogenic perforation causing pseudomyxoma peritonei. Although laparotomy is recommended, the laparoscopic approach is not contraindicated.

Totally laparoscopic management of gallstone ileus could be safe and effective with suggested benefits for the elderly patients.

Laparoscopy is an established method for the treatment of numerous surgical conditions. Natural orifice transluminal endoscopic surgery (NOTES) is a novel surgical technique that uses the natural orifices of the human body as entrances to the abdominal cavity. An alternative concept of minimally invasive approach to the abdominal cavity is to insert all the laparoscopic instruments through ports using a single small incision on the abdominal wall. A suggested name for this technique is laparoendoscopic single-site surgery (LESS). Considering the technical difficulties in NOTES and LESS and the progress in informatics and robotics, the use of robots seems ideal. The aim of this study is to investigate if there is at present, a realistic possibility of using miniature robots in NOTES or LESS in daily clinical practice. An up-to-date review on in vivo surgical miniature robots is made. A Web-based research of the English literature up to March 2013 using PubMed, Scopus, and Google Scholar as search engines was performed. The development of in vivo miniature robots for use in NOTES or LESS is a reality with great advancements, potential advantages, and possible application in minimally invasive surgery in the future. However, true totally NOTES or LESS procedures on humans using miniature robots either solely or as assistance, remain a dream at present.

We developed a medical image segmentation and preoperative planning application which implements a semiautomatic and a hybrid semiautomatic liver segmentation algorithm. The aim of this study was to evaluate the feasibility of computer-assisted liver tumor surgery using these algorithms which are based on thresholding by pixel intensity value from initial seed points. A random sample of 12 patients undergoing elective high-risk hepatectomies at our institution was prospectively selected to undergo computer-assisted surgery using our algorithms (June 2013-July 2014). Quantitative and qualitative evaluation was performed. The average computer analysis time (segmentation, resection planning, volumetry, visualization) was 45 min/dataset. The runtime for the semiautomatic algorithm was <0.2 s/slice. Liver volumetric segmentation using the hybrid method was achieved in 12.9 s/dataset (SD ± 6.14). Mean similarity index was 96.2 % (SD ± 1.6). The future liver remnant volume calculated by the application showed a correlation of 0.99 to that calculated using manual boundary tracing. The 3D liver models and the virtual liver resections had an acceptable coincidence with the real intraoperative findings. The patient-specific 3D models produced using our semiautomatic and hybrid semiautomatic segmentation algorithms proved to be accurate for the preoperative planning in liver tumor surgery and effectively enhanced the intraoperative medical image guidance.

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