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Micro to macro scale analysis of the intact human renal arterial tree with Synchrotron Tomography

Rahmani, Shahrokh; Jafree J. Daniyal; Lee D. Peter; Tafforeau, Paul; Jacob, Joseph; Bellier, Alexandre; Ackermann, Maximilian; Jonigk D. Danny; Shipley J. Rebecca; Long A. David; Walsh L. Claire

The information are related to the quantified morphological parameters of the arterial network of a human kidney, which was scanned using Hierarchical phase-contrast tomography (HiP-CT) at the European Synchrotron Radiation Facility (ESRF) with a voxel resolution of 25 micrometers ( To obtain access to the raw image data, please refer to the Human Organ Atlas website at following link:

Code folder: This folder contains Python and MATLAB files for calculating morphological parameters of the renal arterial network, including topological and Strahler generations, branching angle, colored Strahler generation representation, Murray's law, and radius correction for collapsed vessels.

Data_and_Calculated_parameters folder: The folder contains Excel files, network labels, and the network spatial graph. The Excel files contain skeletonized data on the renal arterial network in the human kidney, including information such as segments, nodes, node coordinates, and points. An additional Excel file contains various calculated parameters such as branching angle, radius vs. Strahler generation, radius over length vs. Strahler generation, tortuosity, Strahler and topological generations, and branching ratio.

The authors would like to express their gratitude for the financial support provided by the Chan Zuckerberg Initiative DAF (2020-225394), an advised fund of SVCF, the MRC (MR/R025673/1), and ESRF beamtimes (md1252 & md1290). P.D.L. is supported by a Royal Academy of Engineering Chair in Emerging Technologies (CiET1819/10). D.J.J. is supported by a Foulkes Foundation Postdoctoral Fellowship. D.A.L. is supported by a Wellcome Trust Investigator Award (220895/Z/20/Z) and by the National Institute for Health Research (NIHR) Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. This research was funded in part by the Wellcome Trust [209553/Z/17/Z]. M.A. is supported by the National Institutes of Health (NIH) (HL94567 and HL134229). For the purpose of open access, the author has applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission. JJ, was also supported by the NIHR UCLH Biomedical Research Centre, UK.
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The manuscript is currently under review and the dataset and codes are available upon request to the Editor, Reviewers, and all authors.

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