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Proceedings Paper

Micro-CT analysis of trabecular parameters gradients in femurs of mice affected by chronic kidney disease
Author(s): Daniel W. Shin; Alexander R. Podgorsak; Kenneth Seldeen; Lee Chaves; Shruthi Thomas; Amanda Honan; Sham Abyad; Bruce Troen; Rabi Yacoub; Ciprian N. Ionita
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Paper Abstract

Chronic kidney disease (CKD) is associated with gradual bone loss that occurs from the failure of the kidneys to regulate bone mineralization. Degradation of bone structure can be quantified with the usage of Micro-CT. The current methods of quantitative imaging typically use a single region of interest (ROI) that segments the whole trabecular region and obtain bone parameters, which usually are not homogenous across such a large ROI. Here we introduce a novel method of quantifying bone parameters that can be used to determine overall bone health. This method analyzes sequential regions on the trabecular bone with multiple small ROIs and evaluates the gradients of bone parameters across these ROIs. Two C57Bl/6J mice femur groups were prepared: a control and CKD groups. All femurs were scanned with a Micro-CT system using tube voltage of 60 kV and current of 0.667 mA. Femur volumes were reconstructed with the Feldkamp-Davis-Kress algorithm and were imported into MicroView to perform bone analysis. Six different sequential ROIs were selected at different distances from the growth plate (0.5mm increments). The gradients of bone parameters along the ROI distance for the control and CKD group were compared. Significant differences were found between two groups in the gradients of bone volume density (P = 0.0002), connective density (P = 0.0003), trabecular spacing (P = 0.001), and trabecular number (P = 0.01). As a result, our method identified a sharp change in several parameters representing a novel and biologically significant strategy.

Paper Details

Date Published: 12 March 2018
PDF: 13 pages
Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 105781M (12 March 2018); doi: 10.1117/12.2293567
Show Author Affiliations
Daniel W. Shin, Univ. at Buffalo (United States)
Toshiba Stroke and Vascular Research Ctr. (United States)
Alexander R. Podgorsak, Univ. at Buffalo (United States)
Toshiba Stroke and Vascular Research Ctr. (United States)
Kenneth Seldeen, Univ. at Buffalo (United States)
Veterans Affairs Western New York Healthcare System (United States)
Lee Chaves, Univ. at Buffalo (United States)
Shruthi Thomas, Univ. at Buffalo (United States)
Amanda Honan, Univ. at Buffalo (United States)
Sham Abyad, Univ. at Buffalo (United States)
Bruce Troen, Univ. at Buffalo (United States)
Veterans Affairs Western New York Healthcare System (United States)
Rabi Yacoub, Univ. at Buffalo (United States)
Ciprian N. Ionita, Univ. at Buffalo (United States)
Toshiba Stroke and Vascular Research Ctr. (United States)


Published in SPIE Proceedings Vol. 10578:
Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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