3D multiscale characterization of the human placenta: Bridging anatomy and histology by X-ray phase-contrast tomography DOI Creative Commons
Jakob Reichmann,

Anne Schnurpfeil,

Scott W. Mittelstadt

et al.

PNAS Nexus, Journal Year: 2024, Volume and Issue: 4(1)

Published: Dec. 23, 2024

The human placenta exhibits a complex three-dimensional (3D) structure with interpenetrating vascular tree and large internal interfacial area. In unique yet insufficiently explored way, this parenchymal enables its multiple functions as respiratory, renal, gastrointestinal multiorgan. histopathological states are highly correlated complications health issues of mother, fetus or newborn. Macroscopic microscopic examination has so far been challenging to reconcile on the entire organ. Here we show that anatomical histological scales can be bridged advent hierarchical phase-contrast tomography brilliant synchrotron radiation. To end, exploiting new capabilities offered by BM18 beamline at ESRF, Grenoble for whole organ well coherence P10 DESY, Hamburg high-resolution, creating multiscale datasets. We also within certain limits, translation μCT instrumentation 3D becomes possible based advanced preparation CT protocols, while segmentation datasets machine learning now remains biggest challenge.

Language: Английский

Vasculature segmentation in 3D hierarchical phase-contrast tomography images of human kidneys DOI Creative Commons
Yashvardhan Jain, Claire Walsh, Ekin Yağış

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 26, 2024

Abstract Efficient algorithms are needed to segment vasculature in new three-dimensional (3D) medical imaging datasets at scale for a wide range of research and clinical applications. Manual segmentation vessels images is time-consuming expensive. Computational approaches more scalable but have limitations accuracy. We organized global machine learning competition, engaging 1,401 participants, help develop deep methods 3D blood vessel segmentation. This paper presents detailed analysis the top-performing solutions using manually curated Hierarchical Phase-Contrast Tomography human kidney, focusing on accuracy morphological analysis, thereby establishing benchmark future studies within phase-contrast tomography imaging.

Language: Английский

Citations

3
Micro to macro scale analysis of the intact human renal arterial tree with Synchrotron Tomography DOI Creative Commons
Shahrokh Rahmani, Daniyal J. Jafree, Peter Lee

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: March 29, 2023

The architecture of the kidney vasculature is essential for its function. Although structural profiling intact rodent has been performed, it challenging to map vascular larger human organs. We hypothesised that hierarchical phase-contrast tomography (HiP-CT) would enable quantitative analysis entire vasculature. Combining label-free HiP-CT imaging an from a 63-year-old male with topology network analysis, we quantitated in down scale arterioles. and rat topologies are comparable, radius decreases at significantly faster rate humans as vessels branch artery towards cortex. At branching points large vessels, radii theoretically optimised minimise flow resistance, observation not found smaller Structural differences were different spatial zones reflecting their unique functional roles. Overall, this represents first time arterial mapped providing inputs computational models synthetic architectures, implications understanding how structure individual blood collectively scales facilitate organ

Language: Английский

Citations

4
Tube2FEM: a general-purpose highly-automated pipeline for flow related processes in (embedded) tubular objects DOI

Hani Cheikh Sleimana,

Kevin M. Moerman, Diana Oliveira

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 28, 2024

Abstract This paper presents a comprehensive and highly-automated open-source pipeline for simulating flow flow-related processes in (embedded) tubular structures. Addressing critical gap computational fluid dynamics (CFD) simulation sciences, it facilitates the transition from raw three-dimensional imaging, graph networks, or CAD models of objects to refined, simulation-ready meshes. transition, traditionally labor-intensive challenging, is streamlined through series innovative steps that include surface mesh processing, centre-line construction, anisotropic generation, volumetric meshing, leading Finite Element Method (FEM) simulations. The leverages range software libraries, notably GIBBON , FEniCS Paraview provide flexibility broad applicability across different scenarios, ranging biomedical industrial applications. We demonstrate versatility our approach five distinct applications, including generation soil-root systems, lung airways, microcirculation portal vein each originating data source. Moreover, several these cases, we incorporate Computational Fluid Dynamics simulations strategies 3D-1D coupling between embedding domain embedded Finally, outline some future perspectives aimed at enhancing accuracy, reducing time, incorporating advanced modeling boundary condition further refine framework’s capabilities.

Language: Английский

Citations

0
A flexible generative algorithm for growing in silico placentas DOI Creative Commons
Diana Oliveira,

Hani Cheikh Sleiman,

Kelly Payette

et al.

PLoS Computational Biology, Journal Year: 2024, Volume and Issue: 20(10), P. e1012470 - e1012470

Published: Oct. 7, 2024

The placenta is crucial for a successful pregnancy, facilitating oxygen exchange and nutrient transport between mother fetus. Complications like fetal growth restriction pre-eclampsia are linked to placental vascular structure abnormalities, highlighting the need early detection of health issues. Computational modelling offers insights into how architecture correlates with flow oxygenation in both healthy dysfunctional placentas. These models use synthetic networks represent multiscale feto-placental vasculature, but current methods lack direct control over key morphological parameters branching angles, essential predicting dysfunction. We introduce novel generative algorithm creating silico placentas, allowing user-controlled customisation vasculatures, as individual components (placental shape, chorionic vessels, placentone) complete structure. physiologically underpinned, following laws (i.e. Murray’s Law), defined by four morphometric statistics: vessel diameter, length, angle asymmetry. Our produces structures consistent vivo measurements ex observations. sensitivity analysis highlights length variations angles play pivotal role defining network. Moreover, our approach stochastic nature, yielding different topological metrics when imposing same input settings. Unlike previous volume-filling algorithms, allows parameters, generating that closely resemble real densities investigation impact on function upcoming studies.

Language: Английский

Citations

0
3D multiscale characterization of the human placenta: Bridging anatomy and histology by X-ray phase-contrast tomography DOI Creative Commons
Jakob Reichmann,

Anne Schnurpfeil,

Scott W. Mittelstadt

et al.

PNAS Nexus, Journal Year: 2024, Volume and Issue: 4(1)

Published: Dec. 23, 2024

The human placenta exhibits a complex three-dimensional (3D) structure with interpenetrating vascular tree and large internal interfacial area. In unique yet insufficiently explored way, this parenchymal enables its multiple functions as respiratory, renal, gastrointestinal multiorgan. histopathological states are highly correlated complications health issues of mother, fetus or newborn. Macroscopic microscopic examination has so far been challenging to reconcile on the entire organ. Here we show that anatomical histological scales can be bridged advent hierarchical phase-contrast tomography brilliant synchrotron radiation. To end, exploiting new capabilities offered by BM18 beamline at ESRF, Grenoble for whole organ well coherence P10 DESY, Hamburg high-resolution, creating multiscale datasets. We also within certain limits, translation μCT instrumentation 3D becomes possible based advanced preparation CT protocols, while segmentation datasets machine learning now remains biggest challenge.

Language: Английский

Citations

0