Morphological Characterization of Colorectal Pits Using Autofluorescence Microscopy Images

Abstract

BACKGROUND: Colorectal cancer is one of the most prevalent pathologies. Its prognosis is linked to the early detection and treatment. Currently diagnosis is performed by histological analysis from polyp biopsies, followed by morphological classification. Kudo’s pit pattern classification is frequently used for the differentiation of neoplastic colorectal lesions using hematoxylin-eosin stained samples. Few articles have reported this classification with image software processing, using exogenous markers over the samples. The processing of autofluorescence images is an alternative that could allow the characterization of the pits from the crypts of Lieberkühn, bypassing staining techniques. OBJECTIVE: Processing and analysis of widefield autofluorescence microscopy images obtained by fresh colon tissue samples from a murine model of colorectal cancer in order to quantify and characterize the pits morphology by measuring morphology parameters and shape descriptors. METHODS: Adult male BALB/cCmedc strain mice (n=27), ranging from 20 to 30 g, were randomly assigned to four and five groups of treated and control animals. Colon samples were collected at day zero and at fourth, eighth, sixteenth and twentieth weeks after treatmentwith azoxymethane. Two-dimensional (2D) segmentation, quantification and morphological characterization of pits by image processing applied using macro programming from FIJI. RESULTS: Type I is the pit morphology prevailing between 53 and 81% in control group weeks. III-L and III-S types were detected in reduced percentages. Between the 33 and 56% of type I was stated as the prevailing morphology for the 4th, 8th and 20th weeks of treated groups, followed by III-L type. For the 16th week, the 39% of the pits was characterized as III-L type, followed by type I. Further, pattern types as IV, III-S and II were also found mainly in that order for almost all of the treated weeks. CONCLUSION: These preliminaries outcomes could be considered an advance in two-dimensional pit characterization as the whole image processing, comparing to the conventional procedure, takes a few seconds to quantify and characterize non-pathological colon pits as well as to estimate early pathological stages of colorectal cancer.

Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images

“…Further, as the magnifying videoscopic diagnosis has proved to be comparable with the histological diagnosis (Tamura et al, 2002), image processing techniques can help to characterize the pits morphology of the tissue being analyzed, detecting neoplastic lesions, bypassing staining techniques and decreasing the inspection and diagnostic time as well as biopsies and resources involved in the examination process. Despite the fact that research articles about morphological characterization of individual crypts or patterns mostly involve the judgment of expert endoscopists by using, for example, Kudo's pit pattern classification as a diagnostic criterion to predict the histology of colorectal lesions, some of these reports have implemented digital image processing techniques to carry out two-dimensional (2D) geometrical and shape descriptor quantifications and analyses (Erbes et al, 2018(Erbes et al, , 2019Prieto et al, 2016Prieto et al, , 2017Prieto et al, , 2019Saul et al, 2009;Takemura et al, 2010), and three-dimensional (3D) ones (Furukawa et al, 2000;Qi et al, 2008;Tan et al, 2013). Moreover, the use of autofluorescence, as an alternative to exogenous markers or staining techniques, has been reported in a few articles characterizing colorectal lesions at screening stages or from resections (Hayashi et al, 2013;van den Broek et al, 2008;Yoshioka et al, 2016).…”