Author(s)

Marilena Varrecchia, Joshua Levine, Gabriella Olmo^*, Marco Grangetto, Marta Gai, Ferdinando Di Cunto

Department of Automatics and Computer Science, Politecnico di Torino, Torino, Italy.

In this paper, we describe an algorithm that performs automatic detection and tracking of astral microtubules in fluorescence confocal images. This sub-population of microtubules only exists during and immediately before mitosis and aids in the spindle orientation by connecting it to the cell cortex. Anomalies in their dynamic behaviour play a causal role in many diseases, such as development disorders and cancer. The main novelty of the proposed algorithm lies in the fact it provides a fully automated estimation of parameters related to microtubule dynamic instability (growth velocity, track length and track lifetime), and helps in understanding the effects of intermediate drug concentrations. Its performance has been objectively assessed using publicly available synthetic data and largely employed metrics. Moreover, we present experiments addressing cell cultures doped with different concentrations of taxol and nocodazole. Such drugs are known to suppress the microtubule dynamic instability, but their effects at intermediate concentrations are not completely assessed. The algorithm has been compared with other state-of-the-art approaches, tested on consistent real datasets. The results are encouraging in terms of performance, robustness and simplicity of use, and the algorithm is now routinely employed in our Department of Molecular Biotechnology.

Medical Diagnostic Imaging, Fluorescence Confocal Microscopy, Image Segmentation, Microtubules

Varrecchia, M. , Levine, J. , Olmo, G. , Grangetto, M. , Gai, M. and Cunto, F. (2019) A Method for Astral Microtubule Tracking in Fluorescence Images of Cells Doped with Taxol and Nocodazole. Advances in Molecular Imaging, 9, 60-86. doi: 10.4236/ami.2019.94009.