EpiTools : an open-source image analysis toolkit for quantifying epithelial growth dynamics

Epithelia grow and undergo extensive rearrangements to achieve their final size and shape. Imaging the dynamics of tissue growth and morphogenesis is now possible with advances in time-lapse microscopy, but a true understanding of their complexities is limited by automated image analysis tools to extract quantitative data. To overcome such limitations, we have designed a new open-source image analysis toolkit called EpiTools. It provides user-friendly graphical user interfaces for accurately segmenting and tracking the contours of cell membrane signals obtained from 4D confocal imaging. It is designed for a broad audience, especially biologists with no computer-science background. Quantitative data extraction is integrated into a larger bioimaging platform, Icy, to increase the visibility and usability of our tools. We demonstrate the usefulness of EpiTools by analyzing Drosophila wing imaginal disc growth, revealing previously overlooked properties of this dynamic tissue, such as the patterns of cellular rearrangements

Light-sheet microscopy: a tutorial

This paper is intended to give a comprehensive review of light-sheet (LS) microscopy from an optics perspective. As such, emphasis is placed on the advantages that LS microscope configurations present, given the degree of freedom gained by uncoupling the excitation and detection arms. The new imaging properties are first highlighted in terms of optical parameters and how these have enabled several biomedical applications. Then, the basics are presented for understanding how a LS microscope works. This is followed by a presentation of a tutorial for LS microscope designs, each working at different resolutions and for different applications. Then, based on a numerical Fourier analysis and given the multiple possibilities for generating the LS in the microscope (using Gaussian, Bessel, and Airy beams in the linear and nonlinear regimes), a systematic comparison of their optical performance is presented. Finally, based on advances in optics and photonics, the novel optical implementations possible in a LS microscope are highlighted.Peer ReviewedPostprint (published version

Realistic tool-tissue interaction models for surgical simulation and planning

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in pre- and intra-operative surgical planning. Realistic modeling of medical interventions involving tool-tissue interactions has been considered to be a key requirement in the development of high-fidelity simulators and planners. The soft-tissue constitutive laws, organ geometry and boundary conditions imposed by the connective tissues surrounding the organ, and the shape of the surgical tool interacting with the organ are some of the factors that govern the accuracy of medical intervention planning.\ud \ud This thesis is divided into three parts. First, we compare the accuracy of linear and nonlinear constitutive laws for tissue. An important consequence of nonlinear models is the Poynting effect, in which shearing of tissue results in normal force; this effect is not seen in a linear elastic model. The magnitude of the normal force for myocardial tissue is shown to be larger than the human contact force discrimination threshold. Further, in order to investigate and quantify the role of the Poynting effect on material discrimination, we perform a multidimensional scaling study. Second, we consider the effects of organ geometry and boundary constraints in needle path planning. Using medical images and tissue mechanical properties, we develop a model of the prostate and surrounding organs. We show that, for needle procedures such as biopsy or brachytherapy, organ geometry and boundary constraints have more impact on target motion than tissue material parameters. Finally, we investigate the effects surgical tool shape on the accuracy of medical intervention planning. We consider the specific case of robotic needle steering, in which asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. We present an analytical and finite element (FE) model for the loads developed at the bevel tip during needle-tissue interaction. The analytical model explains trends observed in the experiments. We incorporated physical parameters (rupture toughness and nonlinear material elasticity) into the FE model that included both contact and cohesive zone models to simulate tissue cleavage. The model shows that the tip forces are sensitive to the rupture toughness. In order to model the mechanics of deflection of the needle, we use an energy-based formulation that incorporates tissue-specific parameters such as rupture toughness, nonlinear material elasticity, and interaction stiffness, and needle geometric and material properties. Simulation results follow similar trends (deflection and radius of curvature) to those observed in macroscopic experimental studies of a robot-driven needle interacting with gels

Characterisation and computational modelling of retinal stem cells in medaka (Oryzias latipes)

The central functional unit of the vertebrate eye is the retina, composed of neural retina (NR), retinal pigmented epithelium (RPE), and non-visual retina (NVR). In amphibians and fish, the retina grows throughout life via different pools of stem cells (SCs). In this work, I combined experimental and computational approaches to elucidate SC dynamics in the three retinal tissues of the teleost fish medaka (Oryzias latipes). I developed a cell centred agent based model to recapitulate post-embryonic growth of the NR and RPE. By accounting for 3D tissue geometry and continuous growth, the model reconciled conflicting hypotheses, demonstrating that competition between SCs is not mutually exclusive with lifelong coexistence of multiple SC lineages. To understand how NR and RPE regulate their proliferative output to coordinate growth rates, I developed quantitative methods to compare experiment and simulation. I tested the experimental data against simulations implementing two modes of feedback between cell proliferation and organ growth. Thus, I identified that the NR acts upstream to set the growth pace by sending an inductive growth signal, while the RPE responds downstream to this signal. Leveraging the model, I showed that NR SCs compete for niche space, but tissue geometry biases cells at certain positions to win this competition. Further, NR SCs modulate division axes and proliferation rate to change organ shape and retinal topology. Motivated by model predictions, I experimentally characterised the large SC population of the RPE, which consisted of both cycling and non-cycling quiescent cells. Putative sister cells exhibited similar temporal dynamics in local clusters, indicating that quiescence was the major mechanism for regulating proliferative output in the RPE. Finally, I experimentally showed that the NVR grows post-embryonically from a primordium, and shared all known markers for NR SCs in the same spatial distribution. Unlike NR and RPE, the NVR lacked a dedicated niche, instead proliferative cells were distributed throughout the tissue. Lineage tracing revealed a continuous relationship between RPE, NVR, and NR. Thus, the SCs of NR and RPE, and all cells of the NVR displayed plastic multipotency capable of generating all retinal tissues. By taking advantage of the positive feedback loop between experiment and simulation, this work shines a new light into a fundamental problem – growth coordination of different SC populations in a complex vertebrate organ