Literature DB >> 31086705

Fully automated analysis of OCT imaging of human kidneys for prediction of post-transplant function.

Brandon Konkel1, Christopher Lavin1,2, Tong Tong Wu3, Erik Anderson1,2, Aya Iwamoto1,2, Hadi Rashid1,2, Brandon Gaitian4, Joseph Boone1,2, Matthew Cooper2, Peter Abrams2, Alexander Gilbert2, Qinggong Tang4,5, Moshe Levi1, James G Fujimoto6, Peter Andrews1, Yu Chen4.   

Abstract

Current measures for assessing the viability of donor kidneys are lacking. Optical coherence tomography (OCT) can image subsurface tissue morphology to supplement current measures and potentially improve prediction of post-transplant function. OCT imaging was performed on donor kidneys before and immediately after implantation during 169 human kidney transplant surgeries. A system for automated image analysis was developed to measure structural parameters of the kidney's proximal convoluted tubules (PCTs) visualized in the OCT images. The association of these structural parameters with post-transplant function was investigated. This study included kidneys from live and deceased donors. 88 deceased donor kidneys in this study were stored by static cold storage (SCS) and an additional 15 were preserved by hypothermic machine perfusion (HMP). A subset of both SCS and HMP deceased donor kidneys were classified as expanded criteria donor (ECD) kidneys, with elevated risk of poor post-transplant function. Post-transplant function was characterized as either immediate graft function (IGF) or delayed graft function (DGF). In ECD kidneys stored by SCS, increased PCT lumen diameter was found to predict DGF both prior to implantation and following reperfusion. In SCD kidneys preserved by HMP, reduced distance between adjacent lumen following reperfusion was found to predict DGF. Results suggest that OCT measurements may be useful for predicting post-transplant function in ECD kidneys and kidneys stored by HMP. OCT analysis of donor kidneys may aid in allocation of kidneys to expand the donor pool as well as help predict post-transplant function in transplanted kidneys to inform post-operative care.

Entities:  

Year:  2019        PMID: 31086705      PMCID: PMC6485011          DOI: 10.1364/BOE.10.001794

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  2 in total

1.  Feasibility of the soft attention-based models for automatic segmentation of OCT kidney images.

Authors:  Mousa Moradi; Xian Du; Tianxiao Huan; Yu Chen
Journal:  Biomed Opt Express       Date:  2022-04-11       Impact factor: 3.562

2.  Indoor Localization of Hand-Held OCT Probe Using Visual Odometry and Real-Time Segmentation Using Deep Learning.

Authors:  Xi Qin; Bohan Wang; David Boegner; Brandon Gaitan; Yingning Zheng; Xian Du; Yu Chen
Journal:  IEEE Trans Biomed Eng       Date:  2022-03-18       Impact factor: 4.756

  2 in total

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