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Project results short video series: Human model ex-vivo MPM database


As part of the commitment of the PICCOLO project to make openly accessible scientific data, a human model ex-vivo multiphoton database has been generated for its publication. The dataset consists of a set of co-registered Haematoxylin-Eosin (H&E) and multiphoton microscopy (MPM) images acquired from thin colon tissue sections prepared at the Basurto University Hospital (Bilbao). The whole dataset contains a total of 50 samples of colon lesions, obtained by colonoscopy and colectomies from 24 men and 19 women, of which 24 are malignant neoplasias (adenocarcinomas), 19 are preneoplastic lesions (adenomas), 2 are hyperplasias and 5 are healthy colon tissues.

MPM images were acquired from paraffin-embedded blank tissue slices using a custom-made two-photon laser scanning microscopy setup, located at the European Laboratory for Non-linear Spectroscopy (LENS, Florence). Thin tissue samples were imaged at a resolution of 500 nm/pxl, hence providing microscopic resolution over a macroscopic sample size using two different contrast mechanisms: two-photon fluorescence (TPF) and second-harmonic generation (SHG) microscopy. The same specimens were then H&E labelled and imaged in order to obtain a perfect co-registration of MPM and H&E images, as shown in the Figure below, where MPM and H&E image tiles originating from the same sample are stitched together to demonstrate the co-registration.

This novel database can be used with advanced machine learning algorithms to develop new non-invasive in-situ optical biopsy applications for colorectal cancer.

It represents a unique Open Access human model ex-vivo MPM database for colorectal cancer, freely accessible by researchers and clinicians. The details of this output will be openly accessible through publications in scientific journals at the scientific community´s disposal.



Riccardo Cicchi

European Laboratory for Non-linear Spectroscopy (LENS)

Project results short video series: Human model ex-vivo MPM database
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