Polarization and depolarization metrics as optical markers in support to histopathology of ex vivo colon tissue

Deyan Ivanov*, Viktor Dremin, Ekaterina Borisova, Alexander Bykov, Tatiana Novikova, Igor Meglinski, Razvigor Ossikovski

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Tissue polarimetry holds great promise to improve the effectiveness of conventional cancer diagnostics and staging, being a fast, minimally invasive, and low-cost optical technique. We introduce an enhanced diagnostic method for ex vivo colon specimens assessment by utilizing Stokes and Mueller matrix polarimetry. The proposed method makes use of experimental Mueller matrices, measured from healthy and tumor zones of a colon specimen, as input data for post-processing algorithms that include physical realisability filtering, symmetric decomposition and estimation of various polarization and depolarization metrics for colon specimen diagnostics. We validated our results with the gold standard histological diagnostics provided by pathologists. It was found that the Stokes-Mueller matrix polarimetry, combined with the appropriate filtering, decomposition algorithms and polarization/depolarization metrics calculations provides relevant optical markers of the colon tissue pathological conditions (healthy versus cancer), as confirmed by histopathology analysis. This approach potentially provides physicians with valuable and complementary information that holds promises in helping with the diagnostics of colon tissue specimens.

Original languageEnglish
Pages (from-to)4560-4572
Number of pages13
JournalBiomedical Optics Express
Issue number7
Publication statusPublished - 30 Jun 2021

Bibliographical note

Funding Information:
Deyan Ivanov acknowledges the PhD fellowship funding by the Doctoral School of Institut Polytechnique de Paris. Ministry of Science and Higher Education of the Russian Federation (075-15-2020-926); Bulgarian National Science Fund (#KP06-N28/11/14.12.18); Academy of Finland (314369, 325097); ATTRACT (777222); Infotech Oulu.

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