Automated spectroscopic tissue classification in colorectal surgery 109 Introduction In colorectal resection, surgical dissection and intraoperative decision‐making involves visual distinction of critical anatomy, such as ureters and arteries. Especially during laparoscopy, when spatial perception from direct sight and haptic feedback from palpation are absent, identifying these tissues can be even more challenging than during open surgery. Reported incidence of ureteral injury during this type of surgery is 0.66%1, which may cause serious clinical problems like intra‐abdominal sepsis, renal failure and loss of renal function2. Additionally, incidence of iatrogenic ureteral injuries in patients undergoing laparoscopy was found to be significantly higher compared to open procedures (0.15% in open surgery and 0.66% in laparoscopic surgery)1,3. In obese patients, ureter identification can be especially challenging and time‐consuming. While the ureter is a unique structure, there are several arteries in the mesentery of the colon. Detecting the course of these arteries is e.g. crucial in deciding how to maintain proper arterial blood supply of the colorectal anastomosis after colorectal resection. Proper arterial blood supply is an important factor of anastomotic viability4 and, if disrupted, a risk factor for anastomotic leakage. Anastomotic leakage occurs in 6.4‐7.5% of patients undergoing colonic cancer surgery5,6. A non‐invasive tool enhancing the visual contrast of ureters and arteries within adipose surroundings is desirable for improved intraoperative recognition of these structures. Near‐infrared fluorescence imaging has been demonstrated for real‐time, intraoperative visualization of ureters7‐9 and arteries10‐12. However, this technique requires administration of a contrast agent. Exploration of optical spectroscopic techniques based on endogenous contrasts might offer an alternative. Hyperspectral camera technology, with pre‐acquired library‐spectra recorded on the earth surface are used to generate satellite images for discovering places of interest for e.g. agricultural purposes13,14 or military and homeland security applications15. This technology incorporates potential to facilitate image‐guided surgery as well16. It has, for example, been investigated for contrast enhancement of coronary arteries during open heart surgery17, for intraoperative assessment of tissue oxygen saturation18,19, for intraoperative enhancement of bile ducts20 and for intraoperative tumor detection21. Medical hyperspectral imaging systems usually are based on silicon (Si) or indium gallium arsenide (InGaAs) camera chips. Si roughly covers the wavelength range of 400 – 1000 nm, whereas InGaAs is typically sensitive in the 900 – 1700 nm wavelength region with the possibility to push its boundary up to 2500 nm16. In an abdominal surgery pig model, Akbari et al.22, demonstrated the potential of hyperspectral imaging (wavelength range 400 – 1700 nm) for detection and differentiation of arteries and veins. Furthermore, the potential of in vivo multispectral
proefschrift_Schols_SLV
To see the actual publication please follow the link above