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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.
Afiliación
  • Ma X; Department of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.
  • Moradi M; Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, USA.
  • Ma X; Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, USA.
  • Tang Q; The Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA.
  • Levi M; Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC, USA.
  • Chen Y; Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, USA. yuchen@fjnu.edu.cn.
  • Zhang HK; College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, Fujian, PR China. yuchen@fjnu.edu.cn.
Commun Eng ; 3(1): 122, 2024 Sep 02.
Article en En | MEDLINE | ID: mdl-39223332
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Commun Eng Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Commun Eng Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido