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Donor kidney assessment by robotic optical coherence tomography

Nature Reviews Bioengineering volume 2, page 808 (2024)Cite this article

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The critical shortage of donor kidneys for transplantation necessitates improved methods for organ viability assessment. Current evaluation techniques, such as the Kidney Donor Profile Index and pre-transplant donor biopsy, are either non-specific or invasive, with restricted sample volume. To overcome these limitations, optical coherence tomography (OCT) can provide high-resolution, in situ and real-time 2D cross-sectional imaging of kidneys to enable non-invasive prediction of post-transplant renal functions. However, current systems have low resolution, are not robust across different environmental conditions, have low range of motion and/or manoeuvrability, or have narrow field-of-view. Now, writing in Communications Engineering, Yu Chen, Haichong K. Zhang and colleagues present a robotic OCT (R-OCT) system that offers robust, flexible and automatic scanning of the surface of a full kidney for quality assessment prior to transplantation.

The team validated the imaging accuracy and flexibility of their R-OCT system using ex vivo kidney samples, demonstrating its capability to produce detailed maps of kidney tissue heterogeneity, including renal microstructures. The high localization accuracy of the system was confirmed through phantom experiments and can reveal anatomical features of renal structures in ex vivo porcine and human kidney samples. Notably, the R-OCT system’s parameter maps provide quantitative information on proximal convoluted tubule lumen diameters — a key indicator of potentially delayed graft function.

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References

Original article

  • Ma, X. et al. Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography. Commun. Eng. 3, 122 (2024)

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  1. Nature Reviews Bioengineering https://www.nature.com/natrevbioeng/

    Sadra Bakhshandeh

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  1. Sadra Bakhshandeh
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Correspondence to Sadra Bakhshandeh.

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This text on an editorially selected paper was initially drafted using artificial intelligence, then revised and fact-checked by an editor to meet Nature Portfolio publication standards.

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Bakhshandeh, S. Donor kidney assessment by robotic optical coherence tomography. Nat Rev Bioeng 2, 808 (2024). https://doi.org/10.1038/s44222-024-00254-6

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