Estimating quantitative physiological and morphological tissue parameters of murine tumor models using hyperspectral imaging and optical profilometry

Understanding tumors and their micro-environment are essential for successfuland accurate disease diagnosis. Tissuephysiology and morphology are altered intumors compared to healthy tissues, andthere is a need to monitor tumors and their surrounding tissues, includingblood vessels, non-invasively. This preliminary study utilizes a multimodaloptical imaging system combining hyperspectral imaging (HSI) and three-dimensional (3D) optical profilometry (OP) to capture hyperspectral imagesand surface shapes of subcutaneously grown murine tumor models. Hyper-spectral images are corrected with 3D OP data and analyzed using the inverse-adding doubling (IAD) method to extract tissue properties such as melaninvolume fraction and oxygenation. Blood vessels are segmented using theB-COSFIRE algorithm from oxygenation maps. From 3D OP data, tumor vol-umes are calculated and compared to manual measurements using a verniercaliper. Results show that tumors can be distinguished from healthy tissuebased on most extracted tissue parameters (p