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使用灰度共生矩阵分析去细胞猪肾中血液灌注减少所产生的血管结构和实质损伤。

Analysis of Vascular Architecture and Parenchymal Damage Generated by Reduced Blood Perfusion in Decellularized Porcine Kidneys Using a Gray Level Co-occurrence Matrix.

作者信息

Pantic Igor V, Shakeel Adeeba, Petroianu Georg A, Corridon Peter R

机构信息

Department of Medical Physiology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.

University of Haifa, Haifa, Israel.

出版信息

Front Cardiovasc Med. 2022 Mar 8;9:797283. doi: 10.3389/fcvm.2022.797283. eCollection 2022.

Abstract

There is no cure for kidney failure, but a bioartificial kidney may help address this global problem. Decellularization provides a promising platform to generate transplantable organs. However, maintaining a viable vasculature is a significant challenge to this technology. Even though angiography offers a valuable way to assess scaffold structure/function, subtle changes are overlooked by specialists. In recent years, various image analysis methods in radiology have been suggested to detect and identify subtle changes in tissue architecture. The aim of our research was to apply one of these methods based on a gray level co-occurrence matrix (Topalovic et al.) computational algorithm in the analysis of vascular architecture and parenchymal damage generated by hypoperfusion in decellularized porcine. Perfusion decellularization of the whole porcine kidneys was performed using previously established protocols. We analyzed and compared angiograms of kidneys subjected to pathophysiological arterial perfusion of whole blood. For regions of interest Santos et al. covering kidney medulla and the main elements of the vascular network, five major GLCM features were calculated: angular second moment as an indicator of textural uniformity, inverse difference moment as an indicator of textural homogeneity, GLCM contrast, GLCM correlation, and sum variance of the co-occurrence matrix. In addition to GLCM, we also performed discrete wavelet transform analysis of angiogram ROIs by calculating the respective wavelet coefficient energies using high and low-pass filtering. We report statistically significant changes in GLCM and wavelet features, including the reduction of the angular second moment and inverse difference moment, indicating a substantial rise in angiogram textural heterogeneity. Our findings suggest that the GLCM method can be successfully used as an addition to conventional fluoroscopic angiography analyses of micro/macrovascular integrity following blood perfusion to investigate scaffold integrity. This approach is the first step toward developing an automated network that can detect changes in the decellularized vasculature.

摘要

肾衰竭无法治愈,但生物人工肾可能有助于解决这一全球性问题。去细胞化提供了一个有前景的平台来生成可移植器官。然而,维持可行的脉管系统对这项技术来说是一项重大挑战。尽管血管造影术为评估支架结构/功能提供了一种有价值的方法,但专家们会忽略一些细微变化。近年来,放射学中的各种图像分析方法已被建议用于检测和识别组织结构中的细微变化。我们研究的目的是应用基于灰度共生矩阵(托帕洛维奇等人)计算算法的这些方法之一,来分析去细胞化猪肾中低灌注所产生的血管结构和实质损伤。使用先前建立的方案对整个猪肾进行灌注去细胞化。我们分析并比较了接受全血病理生理动脉灌注的肾脏的血管造影图像。对于覆盖肾髓质和血管网络主要元素的感兴趣区域,计算了五个主要的灰度共生矩阵特征:作为纹理均匀性指标的角二阶矩、作为纹理同质性指标的逆差矩、灰度共生矩阵对比度、灰度共生矩阵相关性以及共生矩阵的和方差。除了灰度共生矩阵,我们还通过使用高通和低通滤波计算各自的小波系数能量,对血管造影感兴趣区域进行了离散小波变换分析。我们报告了灰度共生矩阵和小波特征的统计学显著变化,包括角二阶矩和逆差矩的降低,这表明血管造影纹理异质性大幅增加。我们的研究结果表明,灰度共生矩阵方法可以成功地作为传统荧光透视血管造影分析的补充,用于在血液灌注后研究微/大血管完整性,以调查支架完整性。这种方法是朝着开发一个能够检测去细胞化脉管系统变化的自动化网络迈出的第一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66f7/8963813/57f9cd1ce7a0/fcvm-09-797283-g0001.jpg

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