SpheroidPicker for automated 3D cell culture manipulation using deep learning

Abstract

Recent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20% of all deaths. High-throughput screening of cancer cell cultures has dominated the search for novel, effective anticancer therapies in the past decades. Recently, functional assays with patient-derived ex vivo 3D cell culture have gained importance for drug discovery and precision medicine. We recently evaluated the major advancements and needs for the 3D cell culture screening, and concluded that strictly standardized and robust sample preparation is the most desired development. Here we propose an artificial intelligence-guided low-cost 3D cell culture delivery system. It consists of a light microscope, a micromanipulator, a syringe pump, and a controller computer. The system performs morphology-based feature analysis on spheroids and can select uniform sized or shaped spheroids to transfer them between various sample holders. It can select the samples from standard sample holders, including Petri dishes and microwell plates, and then transfer them to a variety of holders up to 384 well plates. The device performs reliable semi- and fully automated spheroid transfer. This results in highly controlled experimental conditions and eliminates non-trivial side effects of sample variability that is a key aspect towards next-generation precision medicine.

A platform for automated and label-free monitoring of morphological features and kinetics of spheroid fusion

“…On the other hand, several systems for the automated analysis of single spheroids have been reported (Grexa et al, 2021;Piccinini 2015;Vinci et al, 2012). Although they achieve similar or higher performance than our method, they are often validated on large (>300 µm diameter) and/or relatively immature (<7 days) spheroids (Grexa et al, 2021;Piccinini 2015;Vinci et al, 2012). Small spheroids (<150 µm) and increased maturation levels (>7 days) pose additional challenges, such as single cells/debris and low-contrast regions.…”

“…This becomes labor-intensive and time-consuming when conducting highthroughput screenings. Other methods, developed for the characterization of single spheroids (Piccinini 2015;Grexa et al, 2021;Vinci et al, 2012), often exhibit more automation but lack important features such as the contact length, both spheroid widths, the intersphere angles, and doublet rotation, which have proven to be relevant to understand the complex mechanisms behind tissue fusion (Susienka et al, 2016). Moreover, these methods are often validated on immature spheroids.…”

Robotics-driven manufacturing of cartilaginous microtissues for the bio-assembly of skeletal implants

“…Monitoring of microtissue cultures and their morphometric quality profiles can be done non-invasively through imaging. Software is already available to segment and analyse microtissues in hydrogel microwells and floating cultures, even enabling selection of desirable microtissues and studying their fusion kinetics (13)(14)(15)(16)(17). Commercial microwell systems are typically produced from PCL or PDMS in different microwell shapes, which interact with light, creating complex backgrounds in brightfield images.…”

A deep learning-based pipeline for analyzing the influences of interfacial mechanochemical microenvironments on spheroid invasion using differential interference contrast microscopic images

“…The spheroid cultures effectively resemble in vivo avascular tissue-like cellular characteristics in morphology, signal transmission, cell-cell communication, metastasis, and mechanical stimulation when compared to monolayer cultures [ 9 ]. Although several pieces of software have been created to analyze the invasive and migratory behaviors of spheroids using microscopic data, these tools can only extract particular cell morphologies at two- or three-time points during the time-lapse observation process [ [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] ]. On the other hand, researchers used to visualize the details of spheroid structures and track the status of their migration and invasion under confocal fluorescence microscopy [ [18] , [19] , [20] , [21] ].…”