Liver Surgery

Hepatocellular carcinoma (HCC) is a high-mortality global malignancy with a heavy disease burden in China. Although curative surgical resection improves survival for early-stage HCC patients, the 5-year postoperative recurrence rate remains as high as 50%-70%. Postoperative adjuvant TACE and systemic TKIs are standard treatments for high-risk HCC, yet both therapies have prominent drawbacks, including limited response rates, unavoidable toxicities, and inconsistent clinical benefits. Current treatment decisions rely on conventional clinical and pathological features without precise biomarkers, leading to inadequate individualized therapy and wasted medical resources. Tumor immune microenvironment and multimodal imaging-pathological features critically determine HCC treatment sensitivity. Artificial intelligence and deep learning based on preoperative radiomics and postoperative H\&E whole-slide imaging (WSI) can capture hidden tumor biological characteristics and predict therapeutic responses. However, no validated multimodal AI model is available for predicting postoperative TACE and TKI treatment outcomes in HCC, lacking large-scale multicenter prospective evidence. This study aims to construct and validate a multimodal deep learning model integrating preoperative contrast-enhanced CT/MRI, postoperative WSI, pathological reports, and clinical data, to precisely identify HCC patients sensitive to postoperative adjuvant TACE or TKI therapy and optimize individualized treatment strategies. This is a hybrid retrospective-training and prospective observational multicenter study with no clinical intervention. A total of 10,000 retrospective HCC surgical patients will be enrolled to develop an AI classification model for predicting responses to four postoperative treatment strategies: surgery alone, surgery plus TACE, surgery plus TACE combined with systemic therapy, and surgery plus exclusive systemic therapy. Subsequently, 1,000 eligible postoperative HCC patients will be prospectively and consecutively enrolled from 10-15 centers. The AI model will generate adjuvant therapy predictions without interfering with real clinical decisions. Patients will be divided into prediction-consistent and prediction-inconsistent cohorts based on the match between model predictions and actual treatments. Long-term follow-up will be performed to compare prognostic outcomes and validate the model's real-world performance and stability. Key inclusion criteria: histopathologically confirmed HCC; aged 18-75 years; received R0 curative resection; available qualified H\&E-stained FFPE slides for digital scanning; complete clinical, pathological and follow-up data; high-quality preoperative contrast-enhanced CT/MRI images eligible for AI analysis. Key exclusion criteria: prior preoperative anti-tumor therapy with unavailable baseline data; concurrent other primary malignancies; non-R0 resection; unqualified pathological slides or imaging data; severe missing clinical or follow-up information.

The study aims to improve preoperative evaluation of liver resection volume in patients undergoing major hepatectomies. Accurate prediction of the planned resection and the future liver remnant (FLR) is critical to minimize the risk of postoperative liver failure, which is associated with increased morbidity and mortality. Conventional imaging-based volumetry may have limited accuracy. This study investigates the use of individualized 3D liver models combined to enhance visualization and volumetric analysis of liver anatomy and resection boundaries. Patients are recruited in the liver outpatient clinic and, upon consent, preoperative 3D models are created using Medics 3D. During surgery, the planned resection is guided by the individualized 3D models. Postoperatively, the resected specimen undergoes CT-based volumetry to compare the predicted resection volume from the 3D model with the actual volume. Routine postoperative follow-up is conducted. The study aims to optimize surgical planning, enhance the accuracy of future liver remnant prediction.

* Background: Postoperative pulmonary complications (PPCs) are the most common complications after major upper abdominal surgery. PPCs include respiratory infections, severe atelectasis, pleural effusion, bronchospasm, aspiration pneumonitis, pneumothorax, exacerbation of chronic pulmonary condition, and respiratory failure. Although PPC rates are higher after open liver surgery, PPCs still occur in approximately 12-13% of patients undergoing laparoscopic liver surgery. Preoperative respiratory physiotherapy education reduces PPCs after open major abdominal surgery and after laparoscopic colorectal surgery. The aim of this study is to investigate the impact of enhanced perioperative pulmonary physiotherapy on the incidence of PPCs after laparoscopic liver surgery. * Methods: A prospective, multicentre, single-blinded, randomized controlled trial will be conducted according to the study protocol at participating centers. A total of 326 patients scheduled for laparoscopic liver surgery will be randomized at a 1:1 ratio into intervention group or standard Enhanced Recovery After Surgery (ERAS) -based perioperative education group. Surgeons/ researchers are blinded to the patient allocation. Patients in the intervention group receive preoperative breathing education in a single session and an educational video to guide pulmonary training at home. Pulmonary training lasts for 7 days prior to surgery and for 7 days postoperatively. The training includes deep breathing, and coughing, pursed lip breathing and positive expiratory pressure (PEP) therapy. Patients receive instructions for conducting exercises along with an individual risk assessment at a preoperative ambulatory visit. The exercise session (10min) is to be performed two times daily for total of 14 days. The control group receives standard perioperative breathing education. Primary outcome is the rate of postoperative pulmonary complications within 14 days of operation. Secondary outcomes include 90-day mortality, Clavien-Dindo classified complications, length of hospital stay, intensive care unit (ICU) stay, and hospital costs. * Discussion: Little effort is currently put into preventing pulmonary complications after surgery, although PPCs aggravate considerable morbidity and costs to health care system. ERAS Society protocols concentrate mainly on optimizing postoperative recovery. Laparoscopic techniques as such and frequent manipulation of the diaphragm during liver surgery provoke PPCs at a considerable rate. Aim of the study is to present a short-and-easy perioperative pulmonary physiotherapy initiative and evaluate its impact on PPC rate and PPCs ramifications, including direct costs, after laparoscopic liver surgery.

Minimally invasive techniques in liver surgery gain popularity as they facilitate postoperative recovery while achieving comparable oncologic outcomes to the open approach. No consensus on the application of pneumoperitoneum pressure in minimal invasive liver resections (MILR) has been reached yet, as prospective clinical studies are scarce. The positive pressure of the CO2 pneumoperitoneum reduces intraoperative blood loss during MILR alongside the development of new transection devices and advancements in inflow control. Low-pressure pneumoperitoneum on the other hand has been shown to decrease postoperative pain scores and analgesic consumption in comparison to standard pneumoperitoneum, and international guidelines recommend the application of "the lowest intra-abdominal pressure allowing adequate exposure of the operative field rather than a routine pressure". Nevertheless, evidence for the application of low-pressure pneumoperitoneum is only moderate to low, requiring additional studies to better define its safety. To address this oxymoron, the investigators conduct a randomized non-inferiority trial to investigate the effect of low in comparison to high-pressure pneumoperitoneum during the transection phase of major MILR on intraoperative blood loss while also evaluating the risk of embolic complications.

Database of patients who undergo hepatic surgery for: benign diseases, primary or secondary liver cancer at Institut Paoli-Calmettes