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Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography

Ma, Xihan
Moradi, Mousa
Ma, Xiaoyu
Tang, Qinggong
Levi, Moshe
Chen, Yu
Zhang, Haichong K
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Abstract

Optical coherence tomography (OCT) can be used to image microstructures of human kidneys. However, current OCT probes exhibit inadequate field-of-view, leading to potentially biased kidney assessment. Here we present a robotic OCT system where the probe is integrated to a robot manipulator, enabling wider area (covers an area of 106.39 mm by 37.70 mm) spatially-resolved imaging. Our system comprehensively scans the kidney surface at the optimal altitude with preoperative path planning and OCT image-based feedback control scheme. It further parameterizes and visualizes microstructures of large area. We verified the system positioning accuracy on a phantom as 0.0762 ± 0.0727 mm and showed the clinical feasibility by scanning ex vivo kidneys. The parameterization reveals vasculatures beneath the kidney surface. Quantification on the proximal convoluted tubule of a human kidney yields clinical-relevant information. The system promises to assess kidney viability for transplantation after collecting a vast amount of whole-organ parameterization and patient outcomes data.

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Ma X, Moradi M, Ma X, Tang Q, Levi M, Chen Y, Zhang HK. Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography. Commun Eng. 2024 Sep 2;3(1):122. doi: 10.1038/s44172-024-00264-7. PMID: 39223332; PMCID: PMC11368928.

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DOI
10.1038/s44172-024-00264-7
PubMed ID
39223332
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Funding and Acknowledgements
The UMass Center for Clinical and Translational Science (UMCCTS), UL1TR001453, provided funding for this study. The post-scan histopathology was performed at the University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.
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Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2024Attribution 4.0 International