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Background/Objectives : The aim of our study is to evaluate the feasibility and efficacy of the rendezvous technique for the treatment of iatrogenic ureteral injuries. Methods : From 2014 to 2019, 29 patients treated with the rendezvous technique for mono- or bilateral iatrogenic ureteral injuries were enrolled in this retrospective study. All the leaks were previously assessed by CT-urography and antegrade pyelography. Ureteral continuity was restored by performing the rendezvous technique, combining antegrade trans-nephrostomic access and a retrograde trans-cystostomic approach. A double J stent was antegradely inserted, and a nephrostomy tube was kept in place at the end of the procedure. A post-procedure CT-urography and a 30-day nephrostogram follow-up were performed. In the absence of a contrast leak, the nephrostomy tube was removed. Patient follow-up was set with CT-urography at 3, 6, and 12 months and stent substitution every 4 months. The CT-urography was performed to confirm the restored integrity of the ureter before stent removal. Results : The rendezvous technique was successful in all cases with the resolution of the ureteral leak. No major complications were observed. In all the patients, the nephrostomy tube was removed after 30 days. After performing CT-urography, the stent was removed permanently after 12 months. Only three cases showed local post-treatment stenosis treated with surgical ureteral reimplantation. Conclusions : The rendezvous technique is a safe and effective minimally invasive procedure that can be used to restore the continuity of the ureter, avoiding open surgery and providing valuable support for the management of complications after gynecological surgery.

Background : Acute liver injury occurs most frequently due to trauma, but it can also occur because of sepsis or drug-induced injury. This review aims to analyze artificial intelligence (AI)'s ability to detect and quantify liver injured areas in adults and pediatric patients. Methods : A literature analysis was performed on the PubMed Dataset. We selected original articles published from 2018 to 2023 and cohorts with ≥10 adults or pediatric patients. Results : Six studies counting 564 patients were collected, including 170 (30%) children and 394 adults. Four (66%) articles reported AI application after liver trauma, one (17%) after sepsis, and one (17%) due to chemotherapy. In five (83%) studies, Computed Tomography was performed, while in one (17%), FAST-UltraSound was performed. The studies reported a high diagnostic performance; in particular, three studies reported a specificity rate > 80%. Conclusions : Radiomics models seem reliable and applicable to clinical practice in patients affected by acute liver injury. Further studies are required to achieve larger validation cohorts.

Background: Pancreatic ductal adenocarcinoma (PDAC) is the seventh leading cause of cancer-related deaths worldwide. Surgical resection is the main driver to improving survival in resectable tumors, while neoadjuvant treatment based on chemotherapy (and radiotherapy) is the best option-treatment for a non-primally resectable disease. CT-based imaging has a central role in detecting, staging, and managing PDAC. As several authors have proposed radiomics for risk stratification in patients undergoing surgery for PADC, in this narrative review, we have explored the actual fields of interest of radiomics tools in PDAC built on pre-surgical imaging and clinical variables, to obtain more objective and reliable predictors., Methods: The PubMed database was searched for papers published in the English language no earlier than January 2018., Results: We found 301 studies, and 11 satisfied our research criteria. Of those included, four were on resectability status prediction, three on preoperative pancreatic fistula (POPF) prediction, and four on survival prediction. Most of the studies were retrospective., Conclusions: It is possible to conclude that many performing models have been developed to get predictive information in pre-surgical evaluation. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.