1,721,272 research outputs found
The role of three-dimensional imaging reconstruction in complex mininvasive liver resections
No full textBackground: Parenchyma-saving liver surgery, calculation of the future liver remnant (FLR) and surgical technique improve minimally invasive liver surgery (MILS). 3D rendering (3DR) allows surgical planning, ameliorating intraoperative lesions identification and their relationship with vasculo-biliary structures. Methods: Between November 2019 and July 2021, 246 liver resections were carried out. Patients eligible for a preoperative 3DR (lesion multifocality or large dimensions; proximity, encasement, or invasion of critical vasculo-biliary structures; patients with increased surgical risk; planning of parenchyma-sparing resections; and substantial vasculo-biliary variations) underwent a 0.5 or 1 mm-thick tri-phasic abdominal CT scan at our Centre. Preoperative 3DR was performed in 82 (33.3%) cases, which were compared to 106 non-3DR patients through a propensity score matching (PSM) analysis for age, gender, ASA score, BMI, indication, neoadjuvant chemotherapy, previous abdominal surgery, previous hepatectomies, type of surgery, postero-superior segments, number and total size of the lesions (≥ 5 cm). Results: Amongst all 82 3DR, 28 patients (37.0%) underwent preoperative changes of the original surgical plan: 14 concerned surgical access, anatomic variations, middle hepatic vein management, and preservation/resection of liver portions; 9 patients were excluded from surgical treatment (due to disease extension, FLR insufficiency, and/or patients with high surgical risk), and 5 received a new surgical indication. 3DR patients underwent a laparoscopic (54.8%), open (34.2%), or robotic approach (11%). Nodules ≥ 5 cm were more common in 3DR group (69.4% vs. 38.7%, p = 0.003) but no differences in the number of repeat hepatectomy (p = 0.109), type of resection (p = 0.162), number of PS resections (p = 0.118), and number of nodules (p = 0.131) was found. After PSM analysis, we identified 32 cases in each group. The conversion rate (12.5% vs. 18.7%, p = 0.731) and blood loss (450 cc vs. 425 cc, p = 0.568) were similar. Blood transfusion (31.3% vs. 43.8%, p = 0.439), R1 vascular (12.5% vs. 31.3%, p = 0.129), incidence of Clavien-Dindo complications ≥ 3 (3.1% vs. 12.5%, p = 0.355), and length of stay (4.5 vs. 5 days, p = 0.545) resulted slightly improved in the 3DR group, although statistically not significant. Operative time (450 min vs. 425 min, p = 0.013) was significantly increased in 3DR group. Conclusions: 3DR in MILS has the potential to improve perioperative parameters, refine surgical strategy and allow a safe intraoperative change in surgical strategy leading to a more conservative approach while removing more liver lesions
Multimodal treatment of hepatocellular carcinoma on cirrhosis: an update
No full textAbstract
Hepatocellular carcinoma (HCC) is the most frequent primary liver tumor, and overall, it is one of the most frequent cancers. The association of HCC with chronic liver disease, and cirrhosis in particular, is well known, making treatment complex and challenging. The treatment of HCC must take into account the presence and stage of chronic liver disease, with the aim of preserving hepatic function that is often already impaired, the stage of HCC and the clinical condition of the patient. The different treatment options include surgical resection, transplantation, local ablation, chemoembolization, radioembolization and molecular targeted therapies; these treatments can be combined in various ways to achieve different goals. Ideally, liver transplantation is best treatment for early stage HCC on cirrhosis because it removes both the tumor and the chronic disease that produced it; however, the application of this powerful tool is limited by the scarcity of donors. Downstaging and bridging are different strategies for the management of HCC patients who will undergo liver transplantation. Several professionals, including gastroenterologists, radiologists and surgeons, are involved in the choice of the most appropriate treatment for a single case, and a multidisciplinary approach is necessary to optimize the outcome. The purpose of this review is to provide a comprehensive description of the current treatment options for patients with HCC by analyzing the advantages, disadvantages and rationale for their use
Robotic liver resection of caudate lobe with 3-D rendering and intraoperative ICG-fluorescence for giant hemangioma
No full textEffectiveness of remdesivir in patients with COVID-19 under mechanical ventilation in an Italian ICU-authors' response
No full textASO Author Reflections: Major Hepatectomies: Does Robotic Assistance Increase the Feasibility of the Minimally Invasive Approach?
No full textRobotic versus laparoscopic surgery for spleen-preserving distal pancreatectomies: Systematic review and meta-analysis
No full textBackground: When oncologically feasible, avoiding unnecessary splenectomies prevents patients who are undergoing distal pancreatectomy (DP) from facing significant thromboembolic and infective risks. Methods: A systematic search of MEDLINE, Embase, and Web Of Science identified 11 studies reporting outcomes of 323 patients undergoing intended spleen-preserving minimally invasive robotic DP (SP-RADP) and 362 laparoscopic DP (SP-LADP) in order to compare the spleen preservation rates of the two techniques. The risk of bias was evaluated according to the Newcastle–Ottawa Scale. Results: SP-RADP showed superior results over the laparoscopic approach, with an inferior spleen preservation failure risk difference (RD) of 0.24 (95% CI 0.15, 0.33), reduced open conversion rate (RD of −0.05 (95% CI −0.09, −0.01)), reduced blood loss (mean difference of −138 mL (95% CI −205, −71)), and mean difference in hospital length of stay of −1.5 days (95% CI −2.8, −0.2), with similar operative time, clinically relevant postoperative pancreatic fistula (ISGPS grade B/C), and Clavien–Dindo grade ≥3 postoperative complications. Conclusion: Both SP-RADP and SP-LADP proved to be safe and effective procedures, with minimal perioperative mortality and low postoperative morbidity. The robotic approach proved to be superior to the laparoscopic approach in terms of spleen preservation rate, intraoperative blood loss, and hospital length of stay
Artificial intelligence in the diagnosis and management of colorectal cancer liver metastases
No full textColorectal cancer (CRC) is the third most common malignancy worldwide, with approximately 50% of patients developing colorectal cancer liver metastasis (CRLM) during the follow-up period. Management of CRLM is best achieved via a multidisciplinary approach and the diagnostic and therapeutic decision-making process is complex. In order to optimize patients’ survival and quality of life, there are several unsolved challenges which must be overcome. These primarily include a timely diagnosis and the identification of reliable prognostic factors. Furthermore, to allow optimal treatment options, a precision-medicine, personalized approach is required. The widespread digitalization of healthcare generates a vast amount of data and together with accessible high-performance computing, artificial intelligence (AI) technologies can be applied. By increasing diagnostic accuracy, reducing timings and costs, the application of AI could help mitigate the current shortcomings in CRLM management. In this review we explore the available evidence of the possible role of AI in all phases of the CRLM natural history. Radiomics analysis and convolutional neural networks (CNN) which combine computed tomography (CT) images with clinical data have been developed to predict CRLM development in CRC patients. AI models have also proven themselves to perform similarly or better than expert radiologists in detecting CRLM on CT and magnetic resonance scans or identifying them from the noninvasive analysis of patients’ exhaled air. The application of AI and machine learning (ML) in diagnosing CRLM has also been extended to histopathological examination in order to rapidly and accurately identify CRLM tissue and its different histopathological growth patterns. ML and CNN have shown good accuracy in predicting response to chemotherapy, early local tumor progression after ablation treatment, and patient survival after surgical treatment or chemotherapy. Despite the initial enthusiasm and the accumulating evidence, AI technologies’ role in healthcare and CRLM management is not yet fully established. Its limitations mainly concern safety and the lack of regulation and ethical considerations. AI is unlikely to fully replace any human role but could be actively integrated to facilitate physicians in their everyday practice. Moving towards a personalized and evidence-based patient approach and management, further larger, prospective and rigorous studies evaluating AI technologies in patients at risk or affected by CRLM are needed
The democratizing effects of robotic surgery: Nine HPB manoeuvres exactly reproduced by the da vinci system
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