Retroperitoneal cysts, a rare surgical phenomenon, present diagnostic challenges due to their typically asymptomatic nature. A 62-year-old male presented with a 4-month history of abdominal distension and increased burping. Upon clinical examination, a soft, distended, nontender abdomen with a palpable mass extending from the epigastric region to 3 cm below the umbilicus was revealed. Imaging revealed a 14.6 cm × 15.8 cm × 16.4 cm nonenhancing retroperitoneal lesion, compressing the right ureter and causing mild right hydronephrosis. Multiple gall bladder calculi, an umbilical hernia, and lipomatous lesions associated with adrenal glands were also discovered. Laparoscopic retroperitoneal cystectomy, cholecystectomy, and umbilical hernia repair were performed. Intraoperatively, 150 ml ascitic fluid and 1200 ml cystic fluid were found. This case highlights the intricate clinical presentation of a retroperitoneal cyst, emphasizing the need for surgical exploration. Successful laparoscopic management contributes to the evolving understanding of optimal treatment strategies.

Head and neck tumor differential diagnosis and prognosis have always been a challenge for oral pathologists due to their similarities and complexity. Artificial intelligence novel applications can function as an auxiliary tool for the objective interpretation of histomorphological digital slides. In this review, we present digital histopathological image analysis applications in oral squamous cell carcinoma. A literature search was performed in PubMed MEDLINE with the following keywords: \"artificial intelligence\" OR \"deep learning\" OR \"machine learning\" AND \"oral squamous cell carcinoma\". Artificial intelligence has proven to be a helpful tool in histopathological image analysis of tumors and other lesions, even though it is necessary to continue researching in this area, mainly for clinical validation.