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Post-operative pancreatic fistula is the most dreadful complication of pancreatic resections. Tissue perfusion is a recognized risk factor of fistula in gastrointestinal anastomosis, but has been poorly studied in case of pancreatic surgery. Organ perfusion can be estimated by several intraoperative optical imaging modalities, including exogenous fluorescence imaging with Indocyanine Green (ICG). A limitation of ICG fluorescence angiography is the lack of a quantitative analytic method. Our group has developed and validated a real-time computational imaging analysis of tissue perfusion, based on the slope of the time of fluorescence peak, defined fluorescence-based enhance reality (FLER). This consists in encoding tissue hemodynamics into a virtual perfusion cartography that is superimposed on intraoperative images in real time, in order to provide the perfusion information to surgeons. Another emerging technology is hyperspectral imaging (HSI), which combines a spectrometer and a camera. HSI obtains spectral tissue curves pixel by pixel in a wide wavelength range and can provide absolute values of concentration and/or oxygen saturation of hemoglobin. The aim of this study was to investigate the efficacy of both imaging modalities, FLER and HSI, to estimate pancreatic perfusion. Methods Twelve pigs were involved and randomly assigned to interventional group (n=6) and a control group (n =6). After a median laparotomy the pancreas was fully exposed. In the interventional group, under radiographic guidance, a segmental ischemia of the pancreas was induced by means of coil embolization in small splenic arterial branches, via a femoral artery approach. No ischemia was induced in the control group. HSI images were obtained using the TIVITA camera (Diaspective Vision, Germany). FLER was obtained after injecting 0.2 mg/kg of ICG and image processing using a dedicated software (ER PERFUSION, IRCAD, France). The augmented reality of color-coded images derived from both FLER and HSI were overlapped on the video image. Local capillary lactates (LCL) were sampled in different regions of interests (ROIs) of the pancreas. LCL were correlated to the absolute values provided by the imaging analyses (slope of time-to-peak and StO2, respectively for fluorescence and HSI). Results In all pigs from the interventional group, the segmental ischemic areas were successfully created. The mean slope was slower; the mean StO2 was lower; and mean LCL were lower in the ischemic zone than in the transition and vital zones. The scatter plot between the slope and StO2, the slope and LCL, and StO2 and LCL in all 12 pigs showed statistically significant correlation. In addition, LCL can be predicted from FLER and StO2. The prediction from HSI StO2 (median error: 0.67 mmol/L) is significantly more accurate than FLER (median error: 0.8 mmol/L) (P=0.02). Conclusions FLER and HSI, enable both to precisely quantify and visualize real-time perfusion of the pancreas in this porcine model of pancreas ischemia. HSI showed a greater accuracy in predicting the value of capillary local lactates when compared to quantitative exogenous fluorescence analysis.

Surgical planning in oncological liver surgery is based on the location of the 8 anatomical segments according to Couinaud's definition and tumors inside these structures. The detection of the boundaries between the segments is then the first step of the preoperative planning. The proposed method, devoted to binary images of livers segmented from CT-scans, has been designed to delineate these segments. It automatically detects a set of landmarks using a priori anatomical knowledge and differential geometry criteria. These landmarks are then used to position the Couinaud's segments. Validations performed on 7 clinical cases tend to prove that the method is reliable for most of these separation planes.

Laser ablation (LA) is a minimally invasive procedure based on light/tissue interaction aimed to induce a controlled tumor necrosis by increasing tissue temperature. Given the relationship between tissue damage and produced heat, LA needs a fine control of evolving thermal effects in order to evaluate and control procedure outcome. This study relies on biomedical optics principles for non-invasive diagnostic tools development, and presents a contactless approach based on hyperspectral imaging (HSI) to monitor thermal damage during in vivo porcine LA. By collecting relative pixel-by-pixel reflectance/absorbance of a wide range spectrum (500-1000nm), HSI can track molecular structure modifications caused by the thermoablative procedure. Indeed, these modifications alter tissue light scattering and absorption. In order to investigate tissue spectrum change by increasing temperature, HSI was collected at fixed maximum temperatures (37, 60, 70, 80, 90, 100, 110 °C) and immediately after LA (1, 2, 3, 4, and 5 minutes). Tissue spectral response for two tests was analyzed also relying on the ablated area considered. Regions of Interest of different dimensions (16, 77, and 170 pixels) were placed in the images after applying a motion correction. Obtained spectra show noticeable variations once a specific temperature threshold has been reached (80-100 °C). Specifically, the measured absorbance variation for selected wavelengths (630, 760, 960nm, for methemoglobin, deoxyhemoglobin, and water respectively) confirms tissue optical behavior dependence with its thermal state. This preliminary investigation discloses the potential of HSI measurement to characterize LA damage, encouraging future studies to standardize this novel technique.