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PMC10287567
An integrated cell atlas of the lung in health and disease.
The results were filtered such that genes expressed in <30% of cells of the cluster of interest were excluded, as well as genes that were expressed in >20% of cells outside of the cluster and genes with a multiple testing-corrected P value (using the Benjamini–Hochberg procedure) above 0.05 (Supplementary Table 14).
PMC10287567
An integrated cell atlas of the lung in health and disease.
To investigate whether the HLCA can be used to identify disease-associated cell states shared across multiple diseases, MDMs from the HLCA core, together with all cells from the mapped datasets labeled as MDMs based on label transfer, were jointly analyzed.
PMC10287567
An integrated cell atlas of the lung in health and disease.
Datasets and diseases with fewer than 50 MDMs were excluded from the analysis.
PMC10287567
An integrated cell atlas of the lung in health and disease.
The cells were subsequently clustered as described above for the cross-dataset IPF analysis.
PMC10287567
An integrated cell atlas of the lung in health and disease.
Finally, a Wilcoxon rank-sum test was used on the normalized data to detect differentially expressed genes per cluster (number of cells per cluster: n = 64,915 (cluster 0), 47,539 (cluster 1), 32,027 (cluster 2), 31,097 (cluster 3), 25,267 (cluster 4), 1,998 (cluster 5) and 307 (cluster 6)).
PMC10287567
An integrated cell atlas of the lung in health and disease.
The results were filtered as described above (Supplementary Table 15).
PMC10287567
An integrated cell atlas of the lung in health and disease.
The following tools and versions were used: R (version 4.1.1 for covariate modeling and version 4.0.3 for GSEA); edgeR (version 3.28.1); lme4 (version 1.1-27.1); LDSC (version 1.0.1); Limma (version 3.46.0); Scanpy (version 1.9.1); scArches (version 0.3.5); scIB (version 0.1.1); scikit-learn (version 0.24.1); and scvi-tools (scANVI; version 0.8.1).
PMC10287567
An integrated cell atlas of the lung in health and disease.
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
PMC10287567
An integrated cell atlas of the lung in health and disease.
Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41591-023-02327-2.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The architecture of kidney vasculature is essential the organ's specialised functions, yet is challenging to structurally map in an intact human organ.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Here, we combined hierarchical phase-contrast tomography (HiP-CT) with topology network analysis to enable quantitative assessment of the intact human kidney vasculature, from the renal artery to interlobular arteries.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Comparison with kidney vascular maps described for rodents revealed similar topologies to human, but human kidney vasculature possessed a significantly sharper decrease in radius from hilum to cortex, deviating from theoretically optimal flow resistance for smaller vessels.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Structural differences in kidney hilar, medullary and cortical vasculature reflected unique functional adaptations of each zone.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
This work represents the first time the arterial vasculature of an intact human kidney has been mapped beyond segmental arteries, potentiating novel computational models of kidney vascular flow in humans.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Our analyses have implications for understanding how blood vessel structure collectively scales to facilitate specialised functions in human organs.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The vasculature of the kidney is highly specialised and serves multiple functions, including the delivery of oxygen and nutrients to the organ’s parenchyma, whilst also facilitating plasma ultrafiltration and solute reabsorption.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Despite only comprising approximately 1% of body weight, the kidney receives up to 20% of cardiac output.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Blood enters the kidney through the renal artery, which branches from the abdominal aorta and enters the kidney hilum.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Once within the kidney, the renal artery divides hierarchically, first into segmental or renal feeding arteries which pass through the kidney pelvis, then branching into interlobar arteries which pass through columns between the pyramids of the kidney medulla.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
At the distal end of the kidney columns, interlobar arteries branch into arcuate arteries that arch around the outer surface of the kidney pyramids.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
From these, the interlobular vessels branch and penetrate the surrounding kidney cortex, before finally terminating at afferent arterioles.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
This complex network perfuses specialised capillary networks, including glomerular capillaries across which plasma ultrafiltration occurs, efferent arterioles and peritubular capillaries or vasa recta, which facilitate dynamic solute exchange in the cortex and medulla, respectively.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Thereafter, venous return follows the arterial supply out of the organ.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Structural and molecular changes to the kidney vasculature are a common feature of kidney pathologies, including multiple aetiologies of chronic kidney disease (CKD) and transplant rejection in both animal models and patients.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Therefore, studying kidney vascular patterning has implications for understanding the basis of kidney function in health and disease, and aids surgical planning for tumour resection, nephrectomy and transplantation.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Vascular geometries also have a central role to play in computational models that underpin the creation of digital twins, such as through the generation of synthetic data, and blood flow modelling, which are playing an increasing role in biomedical research.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Vascular imaging of the kidney has advanced following technological innovations in micro-computed tomography (μCT), magnetic resonance imaging (MRI) and μMRI, ultrasound, lightsheet microscopy and photoacoustic imaging.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
These techniques have been used to generate quantitative analyses of vascular network geometry in intact kidneys of model organisms, particularly rodents, in which kidney diameter reaches up to 12 mm.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Comparatively human kidneys, with a diameter of approximately 5 cm are far more challenging to image at high resolution whilst still intact.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Corrosion casting of human kidneys has highlighted vascular heterogeneity and generated intricate 3D casts (down to 100 µm) but provides limited quantitative or accessible digitised geometries of the vascular network.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Optical clearing and lightsheet microscopy have been used to quantify portions of the human kidney vascular network.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
However, as far as the authors are aware, there is no published dataset capturing the intact vascular network of the human kidney beyond approximately six vessel divisions without physical sectioning or subsampling of the tissue.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
MRI has been used to quantify larger vessels both in vivo and post mortem, but for large volumes of interest (VOI), lacks the resolution capable of imaging small vessels and arterioles.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
µMRI can be used to image down to ~50 µm/voxel, but is limited to smaller biological samples such as rodent kidneys.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
CT and µCT have been used extensively to image and analyse rodent renal vasculature, and have also been applied to study the vasculature of ex vivo human lung and fetal kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
However, no detailed segmentation and quantitative analysis of vascular networks in the human kidney have been performed down to the level of arterioles, because of a lack of available imaging data.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Due to this limitation, analysis of human kidney vascular networks is often focused on the first three, large branches of the arterial tree, or limited to subregions within the network.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Where multiscale modelling has been performed, parameters from rodent kidneys are assumed to be representative of human kidney vascular networks.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
However, semi-quantitative studies of human kidney vascular casts have shown large anatomical variation in segmental artery patterning, whilst smaller vessels such as the arcuate arteries, interlobular arteries and afferent or efferent arterioles have not been assessed quantitatively at the organ scale.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
One imaging modality that could address the challenge of imaging intact organ vascular networks is synchrotron phase-contrast tomography.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Hierarchical phase-contrast tomography (HiP-CT) is a technique which leverages the European Synchrotron Radiation Facility’s (ESRF) Extremely Brilliant Source (EBS), a high-energy fourth-generation synchrotron source, to image intact human organs.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
By utilising the high spatial coherence of the ESRF-EBS and the long beamlines available at ESRF, the development of HiP-CT has allowed the scaling of synchrotron phase-contrast tomography to sample sizes up to and including intact human organs.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Datasets created with HiP-CT are hierarchically nested three-dimensional (3D) volumes at multiple resolutions, with exceptional soft tissue contrast spanning from small VOI to the whole intact organ (Fig. 1A).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
As an example of HiP-CT’s potential, we have previously profiled human glomerular morphology and number across cubic centimetres of intact human kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
However, the soft tissue contrast achievable with HiP-CT, coupled with its high spatial resolution, potentiates the visualisation and quantification of vascular networks across whole human organs, and could address the limitations of current imaging technologies used to map kidney vascular architecture.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Fig. 1Multi-level segmentation of the human kidney arterial network.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
A Overview of the hierarchical image volumes that can be acquired with Hierarchical Phase-Contrast Tomography (HiP-CT).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Brown, cyan and yellow volumes show the whole organ acquired at 25 µm per voxel, with sub-volumes (Aii) acquired at 6 and 2.6 µm per voxel, respectively, in the intact human kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Bi–iv Vascular segmentation performed across the three resolutions of HiP-CT data, enabling the intact arterial network to be visualised and segmented.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Red arrows in (Biv) indicate segmented glomeruli.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Ci Diagram of the anatomical organisation of the human kidney arterial network, with insert in (Cii) showing the smaller arterioles and capillaries.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
D The vasculature of the HiP-CT imaged kidney was partitioned into four territories, with each territory denoted by a different colour.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
A Overview of the hierarchical image volumes that can be acquired with Hierarchical Phase-Contrast Tomography (HiP-CT).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Brown, cyan and yellow volumes show the whole organ acquired at 25 µm per voxel, with sub-volumes (Aii) acquired at 6 and 2.6 µm per voxel, respectively, in the intact human kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Bi–iv Vascular segmentation performed across the three resolutions of HiP-CT data, enabling the intact arterial network to be visualised and segmented.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Red arrows in (Biv) indicate segmented glomeruli.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Ci Diagram of the anatomical organisation of the human kidney arterial network, with insert in (Cii) showing the smaller arterioles and capillaries.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
D The vasculature of the HiP-CT imaged kidney was partitioned into four territories, with each territory denoted by a different colour.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Here, we demonstrate how the arterial network of an intact human kidney can be extracted and quantified across multiple length scales using HiP-CT without use of a vascular contrast agent.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Our pipeline utilises the benefits of HiP-CT, such as validation of segmentation using multiscale data, whilst also providing solutions for the technical challenges associated with HiP-CT, for example, the collapse of large vessels.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Within the human kidney, we delineated the extent and morphology of the vasculature, from the renal artery down to the interlobular arteries.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
In doing so, we were able to quantify heterogeneity in vascular architecture within the context of ordering schemes describing morphological network branching.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
We also demonstrate how the multiscale nature of HiP-CT allows estimation of the vascular network between the interlobular arteries and afferent arterioles in smaller VOIs, which we describe as 'local' scans,within the still-intact kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
We perform a quantitative comparison between our human and previously published rodent kidney vascular networks, the latter of which has been used as inputs for biophysical modelling of kidney vascular blood flow.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
We further demonstrate how the label-free nature and exceptional soft tissue contrast of HiP-CT allow vascular heterogeneity to be quantified in the context of other anatomical features, such as the different compartments of the kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Such spatial variations highlight the link between regional structure and function, reinforcing the importance of quantitative analyses for understanding and modelling regional microenvironments within the human kidney.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Using HiP-CT in a hierarchical fashion, we imaged the whole intact kidney obtained from a 63-year-old male organ donor.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
We initially performed an overview scan of the entire kidney at 25 μm per voxel, followed by selecting and imaging representative VOIs at 6.5 μm per voxel and 2.6 μm per voxel (Fig. 1A).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
As these image volumes are inherently aligned, expert annotation using renal anatomical landmarks (Fig. 1B) was applied to the image volumes taken at each resolution to produce a multiscale segmented model of the kidney’s arterial network (Supplementary Movie 1).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
From the segmented data, we were able to identify examples of and interconnect all known anatomical subdivisions of the kidney arterial system (Fig. 1C).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The segmental pattern of anterior, posterior, superior and inferior territories supplying the kidney parenchyma was clearly delineated.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Each vascular territory (Fig. 1D and Supplementary Movie 2) had a corresponding kidney arterial branch originating from the hilum, which bifurcated before hierarchical branching towards the cortical parenchyma.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
We next sought to quantitate the arterial network in a reliable and reproducible manner.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
As we have previously shown that quantitative features of vascular networks can vary by the image processing pipeline used, we developed our own bespoke image processing pipeline (Fig. 2), involving reduction of the initial HiP-CT image to a skeleton, or spatial graph representation, of the arterial network.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The graph representation comprises a set of ‘nodes’; defined as 3D locations where vessels meet or end, and ‘segments’; defined as the connections between these nodes (see Supplementary Fig. 6A and Fig. 4A).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Our pipeline comprises 8 steps, which are fully detailed in our Supplementary Note 2, and enables the generation of a spatial graph from segmented HiP-CT data, with quantification of error in segmentation (from multiscale comparison) and skeletonization (through application of the skeletonization metric).Fig.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
2Overview of the pipeline for the extraction and correction of the human kidney vascular network skeleton.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 1: Segmentation is performed with quantitative validation using a higher resolution VOI.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 2: Skeletonization is optimised by comparison of skeletonization algorithms and the skeleton super-metric.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The super-metric is a projection of the distance vector between the reconstructed skeleton and the segmented image onto a weighted space.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
It contains 5 contributing terms: network volume (Vol.),
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
connected components (CC), Euler Number, Centerline sensitivity (cl sens.)
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
and Bifurcation DICE (BB DICE).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 3: An initial truncated Strahler order (tSO) calculation is made on the skeletonised network.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 4: Using the tSO from Step 3 the network can be split into larger calibre (tSO ) and smaller calibre vessels (tSO ).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The larger calibre vessel can then be smoothed as shown in insets, orange arrows show the points where smoothing has noticeably acted on regions of larger vessels.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 5: tSO vs mean radius is plotted for every segment (blue circles); potential collapsed vessels (red crosses) are flagged for all larger vessels and identified in smaller calibre segments by those as having a radius below the 90% percentile for their tSO.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 6: The segments identified as outliers are presented to an annotator in an interact pop-up window, which allows the annotator to visualise the segment and manually confirm if it should be corrected for collapse.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 7: For vessels which are confirmed as collapsed, planes which are normal to the centreline of the vessel (indicated by orange arrows) are created at every point along the centreline, these are presented in pop-up windows to the annotator, as are the 2D image for each orthogonal plane (lower panels).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
From these 2D planes, the collapsed vessel is identified (red cross) and the perimeter (yellow dashed line) is extracted.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The perimeter is used to calculate an equivalent radius and assigned as the new radius of the segment.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 8: The new radii at each point are plotted, and outliers are removed to reduce the effect of any remaining tortuosity in the centerlines.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
At this stage, the annotator can also manually remove planes that are visibly affected by residual tortuosity.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 1: Segmentation is performed with quantitative validation using a higher resolution VOI.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 2: Skeletonization is optimised by comparison of skeletonization algorithms and the skeleton super-metric.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
The super-metric is a projection of the distance vector between the reconstructed skeleton and the segmented image onto a weighted space.
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
It contains 5 contributing terms: network volume (Vol.),
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
connected components (CC), Euler Number, Centerline sensitivity (cl sens.)
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
and Bifurcation DICE (BB DICE).
PMC12408821
Mapping the arterial vascular network in an intact human kidney using hierarchical phase-contrast tomography.
Step 3: An initial truncated Strahler order (tSO) calculation is made on the skeletonised network.