Multispectral characterization of tissues encountered during laparoscopic colorectal surgery

Abstract

AimsThis study investigated the feasibility of automated differentiation between essential tissue types encountered during laparoscopic colorectal surgery using spectral analysis. MethodsWide band (440–1830nm) spectra were collected using an optical fiber probe and spectrometer from freshly explanted, ex vivo, human colonic specimens. These data were normalized at 810nm (an isobestic wavelength for hemoglobin and oxy-hemoglobin) and mathematically analyzed using total principal component regression (TPCR). Results929 spectra were collected from specimens of 19 patients, distinguishing 5 tissue types: mesenteric fat (MF, n=269), blood vessels (BV, n=377), colonic tissue (CT, n=213), ureter (UR, n=10) and tumorous tissue in colon (TT, n=60). For each individual tissue type the distinctive ability was determined against all other tissue types pooled as a group. Paired probability density function (PDF) of “tissue” (centered around label 1) versus “all other pooled tissues” (centered around label 0) and the cumulative distribution function (CDF) at label crossover value 0.5 was determined for each tissue type (MF: CDF=0.99 [SD=0.19]; BV: CDF=0.95 [SD=0.29]; CT: CDF=0.98 [SD=0.22]; UR: CDF=0.99 [SD=0.09]; TT: CDF=0.99 [SD=0.18]). ConclusionAutomated spectral differentiation of blood vessel, ureter, mesenteric adipose tissue, colonic tissue and tumorous tissue in colon, is feasible in freshly explanted human colonic specimens. These results may be exploited for further steps toward multi- or hyperspectrally enhanced in vivo (laparoscopic) surgical imaging.