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

The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesio...

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Veröffentlicht in:Microscopy research and technique 2022-05, Vol.85 (5), p.1937-1948
Hauptverfasser: Erbes, Luciana A., Izaguirre, María F., Casco, Víctor H., Adur, Javier
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container_end_page 1948
container_issue 5
container_start_page 1937
container_title Microscopy research and technique
container_volume 85
creator Erbes, Luciana A.
Izaguirre, María F.
Casco, Víctor H.
Adur, Javier
description The prognosis of colorectal cancer (CRC), one of the most prevalent pathologies worldwide, is linked to early detection. Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesions. Its use as a highly accurate two‐dimensional diagnostic criterion has increased, mostly involving expert endoscopists’ judgment. The processing of autofluorescence images could allow the diagnostic, bypassing staining techniques and decreasing the biopsies, resources and times involved in the inspection. That criterion could be extended by data of the pit three‐dimensional (3D) morphology. Thus, this work was aimed at obtaining 3D morphological information by quantifying geometrical and shape descriptors through software processing and analysis of widefield autofluorescence microscopy image stacks acquired by fresh colon tissue samples from a murine model of CRC. Statistical analyses included pits from control mice and from the second (2nd), fourth (4th), and eighth (8th) weeks of treatment. Statistically significant differences were found for almost all parameters between the pits from control and from the 4th treated week, stating that the major morphological changes begin after the 2nd week. In particular, pits from control or initial treatment time points were more tubular, straighter and less rough than the ones from later treatment points. Therefore, they may be more associated to normal or non‐neoplastic crypt lumens than linked to adenomas or even cancer crypts. These preliminary outcomes could be considered an advance in 3D pit morphology characterization. 3D representations of around 50 μm of the colorectal pits, from the outer mucosal layer to the inside, exemplifying the morphologies found in control and AOM/DSS treated time points.
doi_str_mv 10.1002/jemt.24055
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Kudo's pit pattern classification states morphological pit patterns of the Lieberkühn crypts by analyzing the superficial mucosa, predicting the histology of colorectal lesions. Its use as a highly accurate two‐dimensional diagnostic criterion has increased, mostly involving expert endoscopists’ judgment. The processing of autofluorescence images could allow the diagnostic, bypassing staining techniques and decreasing the biopsies, resources and times involved in the inspection. That criterion could be extended by data of the pit three‐dimensional (3D) morphology. Thus, this work was aimed at obtaining 3D morphological information by quantifying geometrical and shape descriptors through software processing and analysis of widefield autofluorescence microscopy image stacks acquired by fresh colon tissue samples from a murine model of CRC. Statistical analyses included pits from control mice and from the second (2nd), fourth (4th), and eighth (8th) weeks of treatment. 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subjects Adenoma - diagnostic imaging
Adenoma - pathology
Animal models
Animals
autofluorescence
Biopsy
Cancer
Colon
Colonoscopy - methods
Colorectal cancer
Colorectal carcinoma
Colorectal Neoplasms - diagnostic imaging
Colorectal Neoplasms - pathology
Criteria
crypt
Crypts
Histology
Image acquisition
Inspection
Lumens
Mathematical models
Medical imaging
Mice
Microscopy
Morphology
Mucosa
pit
Pits
Statistical analysis
Statistical methods
three‐dimensional morphology
title Three‐dimensional morphological characterization of colorectal pits from label‐free microscopy images
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