Literature DB >> 29185923

ReViMS: Software tool for estimating the volumes of 3-D multicellular spheroids imaged using a light sheet fluorescence microscope.

Filippo Piccinini1, Anna Tesei1, Michele Zanoni1, Alessandro Bevilacqua2.   

Abstract

Cancer 3-D spheroids are widely used to test drugs and radiotherapy treatments. These 3-D cell clusters range from tens to hundreds of micrometers in size, with shapes that typically differ from a perfect sphere. Change in spheroid volume is one of the most important parameters for evaluating treatment efficacy, and using light sheet fluorescence microscopes (LSFM), optical sections of samples in that size range can be obtained. However, there remains a lack of validated methods for quantifying the volumes of 3-D multicellular aggregates. Here, we present Reconstruction and Visualization from Multiple Sections (ReViMS), an open-source, user-friendly software for automatically segmenting z-stacks of fluorescence images and estimating the volumes of 3-D multicellular spheroids. To assess the precision and accuracy of the volume estimates obtained with ReViMS, we used several cancer spheroids imaged with LSFM. Both the precision and accuracy were >95%, demonstrating the effectiveness of ReViMS.

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Year:  2017        PMID: 29185923     DOI: 10.2144/000114609

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  3 in total

Review 1.  Precision Medicine in Head and Neck Cancers: Genomic and Preclinical Approaches.

Authors:  Giacomo Miserocchi; Chiara Spadazzi; Sebastiano Calpona; Francesco De Rosa; Alice Usai; Alessandro De Vita; Chiara Liverani; Claudia Cocchi; Silvia Vanni; Chiara Calabrese; Massimo Bassi; Giovanni De Luca; Giuseppe Meccariello; Toni Ibrahim; Marco Schiavone; Laura Mercatali
Journal:  J Pers Med       Date:  2022-05-24

2.  Digital Spindle: A New Way to Explore Mitotic Functions by Whole Cell Data Collection and a Computational Approach.

Authors:  Norio Yamashita; Masahiko Morita; Hideo Yokota; Yuko Mimori-Kiyosue
Journal:  Cells       Date:  2020-05-19       Impact factor: 6.600

3.  A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation.

Authors:  Kalyanaraman Vaidyanathan; Chuangqi Wang; Amanda Krajnik; Yudong Yu; Moses Choi; Bolun Lin; Junbong Jang; Su-Jin Heo; John Kolega; Kwonmoo Lee; Yongho Bae
Journal:  Sci Rep       Date:  2021-12-02       Impact factor: 4.379

  3 in total

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