3D membrane segmentation and quantification of intact thick cells using cryo soft X-ray transmission microscopy: a pilot study

Structural analysis of biological membranes is important for understanding cell and sub-cellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10μm) with details of sub-cellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis.R.C. was partially funded by the Instituto de Salud Carlos III, Spain (FIS- PI11/01709), and BE-DGR 2012 BE1 00308 from AGAUR, Catalonia, Spain. C.Z. acknowledges the financial support from the Spanish Ministry of Economy and Competitiveness, through the Maria de Maeztu Programme for Centres/Units of Excellence in R&D (MDM-2015-0502). O.K. was supported by the Seventh Framework Program of the European Commission, grant agreement 278486: DEVELAGE. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under BioStruct-X (grant agreement N283570), the Spanish Ministry of Economy and Competitiveness (grant TIN2014-52923-R) and FEDER

Estimation of electrical pathways finding minimal cost paths from electro-anatomical mapping of the left ventricle

The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, electro-anatomical mappings of patient-specific activation times on the left ventricle surface can be estimated, providing crucial information to the clinicians for guiding cardiac treatment. However, some electrical pathways of particular interest such as Purkinje or still viable conduction channels are difficult to interpret in these maps. We present here a novel method to find some of these electrical pathways using minimal cost paths computations on surface maps. Experiments to validate the proposed method have been carried out in simulated data, and also in clinical data, showing good performance on recovering the main characteristics of simulated Purkinje trees (e.g. end-terminals) and promising results on a real case of fascicular VT.This work is partially funded by the Sub-programa de Proyectos de Investigación en Salud Instituto de Salud Carlos III, Spain (FIS - PI11/01709), by Spanish Ministry of Science and Innovation (TIN2011-28067), and by eTorso project (2013-001404) from Generalitat de Valencia

Estimation of electrical pathways finding minimal cost paths from electro-anatomical mapping of the left ventricle

The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, electro-anatomical mappings of patient-specific activation times on the left ventricle surface can be estimated, providing crucial information to the clinicians for guiding cardiac treatment. However, some electrical pathways of particular interest such as Purkinje or still viable conduction channels are difficult to interpret in these maps. We present here a novel method to find some of these electrical pathways using minimal cost paths computations on surface maps. Experiments to validate the proposed method have been carried out in simulated data, and also in clinical data, showing good performance on recovering the main characteristics of simulated Purkinje trees (e.g. end-terminals) and promising results on a real case of fascicular VT.This work is partially funded by the Sub-programa de Proyectos de Investigación en Salud Instituto de Salud Carlos III, Spain (FIS - PI11/01709), by Spanish Ministry of Science and Innovation (TIN2011-28067), and by eTorso project (2013-001404) from Generalitat de Valencia

Toward integrated management of cerebral aneurysms

In the last few years, some of the visionary concepts behind the virtual physiological human began to be demonstrated on various clinical domains, showing great promise for improving healthcare management. In the current work, we provide an overview of image- and biomechanics-based techniques that, when put together, provide a patient-specific pipeline for the management of intracranial aneurysms. The derivation and subsequent integration of morphological, morphodynamic, haemodynamic and structural analyses allow us to extract patient-specific models and information from which diagnostic and prognostic descriptors can be obtained. Linking such new indices with relevant clinical events should bring new insights into the processes behind aneurysm genesis, growth and rupture. The development of techniques for modelling endovascular devices such as stents and coils allows the evaluation of alternative treatment scenarios before the intervention takes place and could also contribute to the understanding and improved design of more effective devices. A key element to facilitate the clinical take-up of all these developments is their comprehensive validation. Although a number of previously published results have shown the accuracy and robustness of individual components, further efforts should be directed to demonstrate the diagnostic and prognostic efficacy of these advanced tools through large-scale clinical trials.This work was partially supported by the @neurIST Integrated Project (co-financed by the European Commission through contract no. IST-027703), a CDTI CENIT-CDTEAM grant funded by the Spanish Ministry of Science and Innovation (MICINN-CDTI) and Philips Healthcare (Best, The Netherlands). The authors are also grateful for the support provided by ANSYS Inc. (Canonsburg, PA, USA)