Induction of morphological changes in death-induced cancer cells monitored by holographic microscopy.

We are using the label-free technique of holographic microscopy to analyze cellular parameters including cell number, confluence, cellular volume and area directly in the cell culture environment. We show that death-induced cells can be distinguished from untreated counterparts by the use of holographic microscopy, and we demonstrate its capability for cell death assessment. Morphological analysis of two representative cell lines (L929 and DU145) was performed in the culture flasks without any prior cell detachment. The two cell lines were treated with the anti-tumour agent etoposide for 1-3days. Measurements by holographic microscopy showed significant differences in average cell number, confluence, volume and area when comparing etoposide-treated with untreated cells. The cell volume of the treated cell lines was initially increased at early time-points. By time, cells decreased in volume, especially when treated with high doses of etoposide. In conclusion, we have shown that holographic microscopy allows label-free and completely non-invasive morphological measurements of cell growth, viability and death. Future applications could include real-time monitoring of these holographic microscopy parameters in cells in response to clinically relevant compounds.

Semiautomated analysis of embryoscope images: Using localized variance of image intensity to detect embryo developmental stages.

Embryo selection in in vitro fertilization (IVF) treatment has traditionally been done manually using microscopy at intermittent time points during embryo development. Novel technique has made it possible to monitor embryos using time lapse for long periods of time and together with the reduced cost of data storage, this has opened the door to long-term time-lapse monitoring, and large amounts of image material is now routinely gathered. However, the analysis is still to a large extent performed manually, and images are mostly used as qualitative reference. To make full use of the increased amount of microscopic image material, (semi)automated computer-aided tools are needed. An additional benefit of automation is the establishment of standardization tools for embryo selection and transfer, making decisions more transparent and less subjective. Another is the possibility to gather and analyze data in a high-throughput manner, gathering data from multiple clinics and increasing our knowledge of early human embryo development. In this study, the extraction of data to automatically select and track spatio-temporal events and features from sets of embryo images has been achieved using localized variance based on the distribution of image grey scale levels. A retrospective cohort study was performed using time-lapse imaging data derived from 39 human embryos from seven couples, covering the time from fertilization up to 6.3 days. The profile of localized variance has been used to characterize syngamy, mitotic division and stages of cleavage, compaction, and blastocoel formation. Prior to analysis, focal plane and embryo location were automatically detected, limiting precomputational user interaction to a calibration step and usable for automatic detection of region of interest (ROI) regardless of the method of analysis. The results were validated against the opinion of clinical experts. © 2015 International Society for Advancement of Cytometry.

Supervised classification of etoposide-treated in vitro adherent cells based on noninvasive imaging morphology.

Single-cell studies using noninvasive imaging is a challenging, yet appealing way to study cellular characteristics over extended periods of time, for instance to follow cell interactions and the behavior of different cell types within the same sample. In some cases, e.g., transplantation culturing, real-time cellular monitoring, stem cell studies, in vivo studies, and embryo growth studies, it is also crucial to keep the sample intact and invasive imaging using fluorophores or dyes is not an option. Computerized methods are needed to improve throughput of image-based analysis and for use with noninvasive microscopy such methods are poorly developed. By combining a set of well-documented image analysis and classification tools with noninvasive microscopy, we demonstrate the ability for long-term image-based analysis of morphological changes in single cells as induced by a toxin, and show how these changes can be used to indicate changes in biological function. In this study, adherent cell cultures of DU-145 treated with low-concentration (LC) etoposide were imaged during 3 days. Single cells were identified by image segmentation and subsequently classified on image features, extracted for each cell. In parallel with image analysis, an MTS assay was performed to allow comparison between metabolic activity and morphological changes after long-term low-level drug response. Results show a decrease in proliferation rate for LC etoposide, accompanied by changes in cell morphology, primarily leading to an increase in cell area and textural changes. It is shown that changes detected by image analysis are already visible on day 1 for [Formula: see text] etoposide, whereas effects on MTS and viability are detected only on day 3 for [Formula: see text] etoposide concentration, leading to the conclusion that the morphological changes observed occur before and at lower concentrations than a reduction in cell metabolic activity or viability. Three classifiers are compared and we report a best case sensitivity of 88% and specificity of 94% for classification of cells as treated/untreated.