Individual trabecula segmentation validation in first- and second-generation high-resolution peripheral computed tomography compared to micro-computed tomography in the distal radius and tibia

Individual trabecula segmentation validation in first- and second-generation high-resolution peripheral computed tomography compared to micro-computed tomography in the distal radius and tibia

High-resolution peripheral quantitative computed tomography (HR-pQCT) has been used for in vivo 3D visualization of trabecular microstructure. Second-generation HR-pQCT (HR-pQCT II) has been shown to have good agreement with first generation HR-pQCT (HR-pQCT I). Advanced Individual Trabecula Segment...

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Veröffentlicht in:JBMR plus 2024-03, Vol.8 (3), p.ziae007
Hauptverfasser: Dinescu, Andreea Teodora, Zhou, Bin, Hu, Yizhong Jenny, Agarwal, Sanchita, Shane, Elizabeth, Guo, Xiang-Dong Edward
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Zhou, Bin
Hu, Yizhong Jenny
Agarwal, Sanchita
Shane, Elizabeth
Guo, Xiang-Dong Edward
description High-resolution peripheral quantitative computed tomography (HR-pQCT) has been used for in vivo 3D visualization of trabecular microstructure. Second-generation HR-pQCT (HR-pQCT II) has been shown to have good agreement with first generation HR-pQCT (HR-pQCT I). Advanced Individual Trabecula Segmentation (ITS) decomposes the trabecula network into individual plates and rods. ITS based on HR-pQCT I showed a strong correlation to ITS based on micro-computed tomography (μCT) and identified trabecular changes in metabolic bone diseases. ITS based on HR-pQCT II has new potential because of the enhanced resolution but has yet to be validated. The objective of this study was to assess the agreement between ITS based on HR-pQCT I, HR-pQCT II, and μCT to assess the capability of ITS on HR-pQCT images as a tool for studying bone structure. Freshly frozen tibia and radius bones were scanned in the distal region using HR-pQCT I at 82 μm, HR-pQCT II at 60.7 μm, and μCT at 37 μm. Images were registered, binarized, and ITS analysis was performed. Bone volume fraction (pBV/TV, rBV/TV), number density (pTb.N, rTb.N), thickness (pTb.Th, rTb.Th), and plate-to-rod (PR) ratio (pBV/rBV) of trabecular plates and rods were obtained. Paired Student's -tests with post hoc Bonferroni analysis were used to examine the differences. Linear regression was used to determine the correlation coefficient. The HR-pQCT I parameters were different from the μCT measurements. The HR-pQCT II parameters were different from the μCT measurements except for rTb.N, and the HR-pQCT I parameters were different from the HR-pQCT II measurements except for pTb.Th. The strong correlation between HR-pQCT II and μCT microstructural analysis (R  = 0.55-0.94) suggests that HR-pQCT II can be used to assess changes in plate and rod microstructure and that values from HR-pQCT I can be corrected.
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Second-generation HR-pQCT (HR-pQCT II) has been shown to have good agreement with first generation HR-pQCT (HR-pQCT I). Advanced Individual Trabecula Segmentation (ITS) decomposes the trabecula network into individual plates and rods. ITS based on HR-pQCT I showed a strong correlation to ITS based on micro-computed tomography (μCT) and identified trabecular changes in metabolic bone diseases. ITS based on HR-pQCT II has new potential because of the enhanced resolution but has yet to be validated. The objective of this study was to assess the agreement between ITS based on HR-pQCT I, HR-pQCT II, and μCT to assess the capability of ITS on HR-pQCT images as a tool for studying bone structure. Freshly frozen tibia and radius bones were scanned in the distal region using HR-pQCT I at 82 μm, HR-pQCT II at 60.7 μm, and μCT at 37 μm. Images were registered, binarized, and ITS analysis was performed. Bone volume fraction (pBV/TV, rBV/TV), number density (pTb.N, rTb.N), thickness (pTb.Th, rTb.Th), and plate-to-rod (PR) ratio (pBV/rBV) of trabecular plates and rods were obtained. Paired Student's -tests with post hoc Bonferroni analysis were used to examine the differences. Linear regression was used to determine the correlation coefficient. The HR-pQCT I parameters were different from the μCT measurements. The HR-pQCT II parameters were different from the μCT measurements except for rTb.N, and the HR-pQCT I parameters were different from the HR-pQCT II measurements except for pTb.Th. 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Bone volume fraction (pBV/TV, rBV/TV), number density (pTb.N, rTb.N), thickness (pTb.Th, rTb.Th), and plate-to-rod (PR) ratio (pBV/rBV) of trabecular plates and rods were obtained. Paired Student's -tests with post hoc Bonferroni analysis were used to examine the differences. Linear regression was used to determine the correlation coefficient. The HR-pQCT I parameters were different from the μCT measurements. The HR-pQCT II parameters were different from the μCT measurements except for rTb.N, and the HR-pQCT I parameters were different from the HR-pQCT II measurements except for pTb.Th. 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Second-generation HR-pQCT (HR-pQCT II) has been shown to have good agreement with first generation HR-pQCT (HR-pQCT I). Advanced Individual Trabecula Segmentation (ITS) decomposes the trabecula network into individual plates and rods. ITS based on HR-pQCT I showed a strong correlation to ITS based on micro-computed tomography (μCT) and identified trabecular changes in metabolic bone diseases. ITS based on HR-pQCT II has new potential because of the enhanced resolution but has yet to be validated. The objective of this study was to assess the agreement between ITS based on HR-pQCT I, HR-pQCT II, and μCT to assess the capability of ITS on HR-pQCT images as a tool for studying bone structure. Freshly frozen tibia and radius bones were scanned in the distal region using HR-pQCT I at 82 μm, HR-pQCT II at 60.7 μm, and μCT at 37 μm. Images were registered, binarized, and ITS analysis was performed. Bone volume fraction (pBV/TV, rBV/TV), number density (pTb.N, rTb.N), thickness (pTb.Th, rTb.Th), and plate-to-rod (PR) ratio (pBV/rBV) of trabecular plates and rods were obtained. Paired Student's -tests with post hoc Bonferroni analysis were used to examine the differences. Linear regression was used to determine the correlation coefficient. The HR-pQCT I parameters were different from the μCT measurements. The HR-pQCT II parameters were different from the μCT measurements except for rTb.N, and the HR-pQCT I parameters were different from the HR-pQCT II measurements except for pTb.Th. The strong correlation between HR-pQCT II and μCT microstructural analysis (R  = 0.55-0.94) suggests that HR-pQCT II can be used to assess changes in plate and rod microstructure and that values from HR-pQCT I can be corrected.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>38505220</pmid><doi>10.1093/jbmrpl/ziae007</doi><oa>free_for_read</oa></addata></record>
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title Individual trabecula segmentation validation in first- and second-generation high-resolution peripheral computed tomography compared to micro-computed tomography in the distal radius and tibia
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