NeuriTES. Monitoring neurite changes through transfer entropy and semantic segmentation in bright-field time-lapse microscopy

Arianna Mencattini; Alida Spalloni; Paola Casti; Maria Colomba Comes; Davide Di Giuseppe; Gianni Antonelli; Michele D'Orazio; Joanna Filippi; Francesca Corsi; Hervé Isambert; Corrado Di Natale; Patrizia Longone; Eugenio Martinelli

doi:10.1016/j.patter.2021.100261

NeuriTES. Monitoring neurite changes through transfer entropy and semantic segmentation in bright-field time-lapse microscopy

Patterns (N Y). 2021 May 25;2(6):100261. doi: 10.1016/j.patter.2021.100261. eCollection 2021 Jun 11.

Authors

Arianna Mencattini^{1

2}, Alida Spalloni³, Paola Casti^{1

2}, Maria Colomba Comes^{1

2}, Davide Di Giuseppe^{1

2}, Gianni Antonelli^{1

2}, Michele D'Orazio^{1

2}, Joanna Filippi^{1

2}, Francesca Corsi², Hervé Isambert⁴, Corrado Di Natale¹, Patrizia Longone³, Eugenio Martinelli^{1

2}

Affiliations

¹ Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.
² Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy.
³ Molecular Neurobiology Unit, Fondazione Santa Lucia-IRCCS, Via Ardeatina, 306/354, 00179 Rome, Italy.
⁴ Institut Curie - Centre de Recherche, CNRS-UMR168 11, rue P. et M. Curie, 75005 Paris, France.

Abstract

One of the most challenging frontiers in biological systems understanding is fluorescent label-free imaging. We present here the NeuriTES platform that revisits the standard paradigms of video analysis to detect unlabeled objects and adapt to the dynamic evolution of the phenomenon under observation. Object segmentation is reformulated using robust algorithms to assure regular cell detection and transfer entropy measures are used to study the inter-relationship among the parameters related to the evolving system. We applied the NeuriTES platform to the automatic analysis of neurites degeneration in presence of amyotrophic lateral sclerosis (ALS) and to the study of the effects of a chemotherapy drug on living prostate cancer cells (PC3) cultures. Control cells have been considered in both the two cases study. Accuracy values of 93% and of 92% are achieved, respectively. NeuriTES not only represents a tool for investigation in fluorescent label-free images but demonstrates to be adaptable to individual needs.

Keywords: ALS disease; bright-field time-lapse microscopy; cancer cell treatment; semantic segmentation; transfer entropy; video analysis.