We aimed to fuse the concept of fluorescence videography with augmented reality (AR) to guide intestinal resection and assess vascular supply at the future anastomotic site.

AR is the process of superimposing virtual images of a patient onto real-time intraoperative images to enhance visual perception. Virtual images are created from preoperative DICOM images (CT-scan, Nuclear Magnetic Resonance or US) by 3D software manipulation in order to obtain a virtual clone of the patient [10–12].

In our method of assessment of bowel vascular supply, FLuorescence-based Enhanced Reality (FLER), virtual images of bowel perfusion (virtual vascular cartography) are generated from intraoperative live images based on fluorescence signals of indocyanine green.

To push the concept of fluorescence-guided evaluation of the future anastomotic site forward, our Research and Development department developed a dedicated image analyzer software (ER-PERFUSION, IRCAD, France) to obtain FLER [13].

FLER is a fluorescence videography system integrating a near-infrared endoscope (D-Light P, Karl Storz^®, Tuttlingen, Germany) able to detect the fluorescence signal emitted by indocyanine green (ICG) and the ER-PERFUSION software, which can generate a virtual perfusion cartography based on fluorescence time-to-peak.

To assess time-to-peak in FLER, a dye injection is performed in real time while looking at the region of interest, in order to capture and record the “dynamics” of diffusion as well as the evolution of fluorescence. The virtual perfusion cartography is created by averaging the signals over a 20–40 s video at the speed of 5–25 frames per second and attributing a color code based on the time required to reach the maximum intensity of each pixel. Each single pixel composing the virtual perfusion cartography is a dynamic image (2D + diffusion time) representing the average of several images (from 100 to 200). The virtual cartography can be overlapped with real-time laparoscopic images in order to obtain the enhanced reality effect (Fig. 31.2).

In the experimental setting, FLER showed the ability to exactly detect future resection lines in a laparoscopic model of mesenteric ischemia. In the initial experimental model of small bowel ischemia, the software was set to detect a reduction of fluorescence time-to-peak of 50 % and the areas identified by enhanced reality (ischemic, future resection lines, and vascular areas) showed significant and congruent changes in lactate levels, mitochondria respiratory rate, and metabolomic fingerprint of ischemia [13].

The use of the fluorescence time-to-peak slope has two advantages when compared to the use of the absolute value of “fluorescence intensity.” First, time-to-peak is independent of the distance between the light source and the imaged area. This is not the case with fluorescence intensity, which is highly dependent on distance (a low perfused area may look more intensively fluorescent when observed closely and vice versa; a highly perfused area may look poorly fluorescent when observed from far away). We experimentally demonstrated the relationship between the light source-target distance and fluorescence intensity, using a customary electromagnetic tracking device (METRIS 3D) [14]. The METRIS 3D system is composed of a tube (1.2 m long and 2.2 mm in diameter) that fits into the operating channel of a conventional endoscope and contains seven 8 by 1 mm miniature electromagnetic probes distributed on its length. Electromagnetic probes are tracked by a commercially available magnetic tracking system (Aurora, Northern Digital Inc, Waterloo, Ontario, Canada). To track the position of the D-Light P laparoscope, the METRIS 3D system was attached onto the shaft of the laparoscope, and a 2 cm plastic tool was also fixed to establish a set distance. The laparoscope was then used to target the fluorescence calibrating tool in a dark environment, and was moved in and out several times (Fig. 31.3).