Complete mesocolic excision (CME), which involves the adequate resection of the tumor-bearing colonic segment with “en bloc” removal of its mesocolon along embryological fascial planes is associated with superior oncological outcomes. However, CME presents a higher complication rate compared to non-CME resections due to a higher risk of vascular injury. Hyperspectral imaging (HSI) is a contrast-free optical imaging technology, which facilitates the quantitative imaging of physiological tissue parameters and the visualization of anatomical structures. This study evaluates the accuracy of HSI combined with deep learning (DL) to differentiate the colon and its mesenteric tissue from retroperitoneal tissue. In an animal study including 20 pig models, intraoperative hyperspectral images of the sigmoid colon, sigmoid mesentery, and retroperitoneum were recorded. A convolutional neural network (CNN) was trained to distinguish the two tissue classes using HSI data, validated with a leave-one-out cross-validation process. The overall recognition sensitivity of the tissues to be preserved (retroperitoneum) and the tissues to be resected (colon and mesentery) was 79.0 ± 21.0% and 86.0 ± 16.0%, respectively. Automatic classification based on HSI and CNNs is a promising tool to automatically, non-invasively, and objectively differentiate the colon and its mesentery from retroperitoneal tissue.

Ischemia-reperfusion injury during major hepatic resections is associated with high rates of post-operative complications and liver failure. Real-time intra-operative detection of liver dysfunction could provide great insight into clinical outcomes. In the present study, we demonstrate the intra-operative application of a novel optical technology, hyperspectral imaging (HSI), to predict short-term post-operative outcomes after major hepatectomy. We considered fifteen consecutive patients undergoing major hepatic resection for malignant liver lesions from January 2020 to June 2021. HSI measures included tissue water index (TWI), organ hemoglobin index (OHI), tissue oxygenation (StO₂%), and near infrared (NIR). Pre-operative, intra-operative, and post-operative serum and clinical outcomes were collected. NIR values were higher in unhealthy liver tissue (p = 0.003). StO₂% negatively correlated with post-operative serum ALT values (r = −0.602), while ΔStO₂% positively correlated with ALP (r = 0.594). TWI significantly correlated with post-operative reintervention and OHI with post-operative sepsis and liver failure. In conclusion, the HSI imaging system is accurate and precise in translating from pre-clinical to human studies in this first clinical trial. HSI indices are related to serum and outcome metrics. Further experimental and clinical studies are necessary to determine clinical value of this technology.

Anastomotic leakage (AL) is a serious complication occurring after esophagectomy. The current knowledge suggests that inadequate intraoperative perfusion in the anastomotic site contributes to an increase in the AL rate. Presently, clinical estimation undertaken by surgeons is not accurate and new technology is necessary to improve the intraoperative assessment of tissue oxygenation. In the present study, we demonstrate the application of a novel optical technology, namely Single Snapshot imaging of Optical Properties (SSOP), used to quantify StO₂% in an open surgery experimental gastric conduit (GC) model. After the creation of a gastric conduit, local StO₂% was measured with a preclinical SSOP system for 60 min in the antrum (ROI-A), corpus (ROI-C), and fundus (ROI-F). The removed region (ROI-R) acted as ischemic control. ROI-R had statistically significant lower StO₂% when compared to all other ROIs at T15, T30, T45, and T60 (p < 0.0001). Local capillary lactates (LCLs) and StO₂% correlation was statistically significant (R = −0.8439, 95% CI −0.9367 to −0.6407, p < 0.0001). Finally, SSOP could discriminate resected from perfused regions and ROI-A from ROI-F (the future anastomotic site). In conclusion, SSOP could well be a suitable technology to assess intraoperative perfusion of GC, providing consistent StO₂% quantification and ROIs discrimination.

The remarkable capacity of regeneration of the liver is well known, although the involved mechanisms are far from being understood. Furthermore, limits concerning the residual functional mass of the liver remain critical in both fields of hepatic resection and transplantation. The aim of the present study was to review the surgical experiments regarding liver regeneration in pigs to promote experimental methodological standardization. The Pubmed, Medline, Scopus, and Cochrane Library databases were searched. Studies evaluating liver regeneration through surgical experiments performed on pigs were included. A total of 139 titles were screened, and 41 articles were included in the study, with 689 pigs in total. A total of 29 studies (71% of all) had a survival design, with an average study duration of 13 days. Overall, 36 studies (88%) considered partial hepatectomy, of which four were an associating liver partition and portal vein ligation for staged hepatectomy (ALPPS). Remnant liver volume ranged from 10% to 60%. Only 2 studies considered a hepatotoxic pre-treatment, while 25 studies evaluated additional liver procedures, such as stem cell application, ischemia/reperfusion injury, portal vein modulation, liver scaffold application, bio-artificial, and pharmacological liver treatment. Only nine authors analysed how cytokines and growth factors changed in response to liver resection. The most used imaging system to evaluate liver volume was CT-scan volumetry, even if performed only by nine authors. The pig represents one of the best animal models for the study of liver regeneration. However, it remains a mostly unexplored field due to the lack of experiments reproducing the chronic pathological aspects of the liver and the heterogeneity of existing studies.