title: Automated Spectroscopic Tissue Classification in Colorectal Surgery.
abstract: BACKGROUND
  In colorectal surgery, detecting ureters and mesenteric arteries is of utmost importance to prevent iatrogenic injury and to facilitate intraoperative decision making. A tool enabling ureter- and artery-specific image enhancement within (and possibly through) surrounding adipose tissue would facilitate this need, especially during laparoscopy. To evaluate the potential of hyperspectral imaging in colorectal surgery, we explored spectral tissue signatures using single-spot diffuse reflectance spectroscopy (DRS). As hyperspectral cameras with silicon (Si) and indium gallium arsenide (InGaAs) sensor chips are becoming available, we investigated spectral distinctive features for both sensor ranges.
  
  
  METHODS
  In vivo wide-band (wavelength range 350-1830 nm) DRS was performed during open colorectal surgery. From the recorded spectra, 36 features were extracted at predefined wavelengths: 18 gradients and 18 amplitude differences. For classification of respectively ureter and artery in relation to surrounding adipose tissue, the best distinctive feature was selected using binary logistic regression for Si- and InGaAs-sensor spectral ranges separately. Classification performance was evaluated by leave-one-out cross-validation.
  
  
  RESULTS
  In 10 consecutive patients, 253 spectra were recorded on 53 tissue sites (including colon, adipose tissue, muscle, artery, vein, ureter). Classification of ureter versus adipose tissue revealed accuracy of 100% for both Si range and InGaAs range. Classification of artery versus surrounding adipose tissue revealed accuracies of 95% (Si) and 89% (InGaAs).
  
  
  CONCLUSIONS
  Intraoperative DRS showed that Si and InGaAs sensors are equally suited for automated classification of ureter versus surrounding adipose tissue. Si sensors seem better suited for classifying artery versus mesenteric adipose tissue. Progress toward hyperspectral imaging within this field is promising.
authors: Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands van 't Hoff Program on Medical Photonics, The Netherlands Organization for Applied Scientific Research TNO, The Netherlands rutgermschols@hotmail.com.
authors: Rutger M
authors: RM
authors: Schols
authors: van 't Hoff Program on Medical Photonics, The Netherlands Organization for Applied Scientific Research TNO, The Netherlands.
authors: Lejla
authors: L
authors: Alic
authors: Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands.
authors: Geerard L
authors: GL
authors: Beets
authors: Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands.
authors: Stéphanie O
authors: SO
authors: Breukink
authors: van 't Hoff Program on Medical Photonics, The Netherlands Organization for Applied Scientific Research TNO, The Netherlands.
authors: Fokko P
authors: FP
authors: Wieringa
authors: Department of Surgery, Maastricht University Medical Center, Maastricht, The Netherlands.
authors: Laurents P S
authors: LP
authors: Stassen
mesh_terms: D000273:Adipose Tissue / Q000737:chemistry; D000368:Aged; D000369:Aged, 80 and over; D001152:Arsenicals; D003107:Colorectal Surgery / Q000379:methods*; D005260:Female; D005708:Gallium; D006801:Humans; D007204:Indium; D008297:Male; D008638:Mesenteric Arteries / Q000737:chemistry; D008875:Middle Aged; D012825:Silicon; D013057:Spectrum Analysis / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014513:Ureter / Q000737:chemistry
chemical_list: D001152:Arsenicals; D007204:Indium; C043055:gallium arsenide; D005708:Gallium; D012825:Silicon
keywords: adipose tissue; artery; automated tissue classification; colorectal surgery; diffuse reflectance spectroscopy; tissue spectral analysis; ureter