Correlation of Subchondral Bone Density and Structure from Plain Radiographs with Micro Computed Tomography Ex Vivo

Abstract

Osteoarthritis causes changes in the subchondral bone structure and composition. Plain radiography is a cheap, fast, and widely available imaging method. Bone tissue can be well seen from plain radiograph, which however is only a 2D projection of the actual 3D structure. Therefore, the aim was to investigate the relationship between bone density- and structure-related parameters from 2D plain radiograph and 3D bone parameters assessed from micro computed tomography (μCT) ex vivo. Right tibiae from eleven cadavers without any diagnosed joint disease were imaged using radiography and with μCT. Bone density- and structure-related parameters were calculated from four different locations from the radiographs of proximal tibia and compared with the volumetric bone microarchitecture from the corresponding regions. Bone density from the plain radiograph was significantly related with the bone volume fraction (r = 0.86; n = 44; p < 0.01). Mean homogeneity index for orientation of local binary patterns (HIangle,mean) and fractal dimension of vertical structures (FDVer) were related (p < 0.01) with connectivity density (HIangle,mean: r = −0.73, FDVer: r = 0.69) and trabecular separation (HIangle,mean: r = 0.73, FDVer: r = −0.70) when all ROIs were pooled together (n = 44). Bone density and structure in tibia from standard clinically available 2D radiographs are significantly correlated with true 3D microstructure of bone.

Bone texture analysis for prediction of incident radiographic hip osteoarthritis using machine learning: data from the Cohort Hip and Cohort Knee (CHECK) study

“…Before texture analysis, images were median filtered with a 3x3 pixels filter to remove high-frequency noise and grayscale values were expanded to full dynamic range (0 -255). Bone texture was assessed using the FSA method [1,10,11]. FSA produces fractal dimension values that are related to the roughness and complexity of the image.…”

“…A plain radiograph is a projection (summation) through a three-dimensional structure and this is one main limitation of this imaging method. However, it has been shown that radiographybased bone texture is significantly related with the three-dimensional structure of bone [1][2][3][4][5].…”

“…Radiography-based texture analysis of the proximal femur has been applied for example in osteoporosis and in the assessment of femoral neck fracture risk [7,8]. However, in OA research, the majority of studies analyzing bone texture are concentrated on the knee, using mostly fractal-based texture analysis methods [1,[9][10][11][12][13]. There is evidence that tibial trabecular bone texture can be used to predict both development and progression of OA as well as total knee replacement [14][15][16][17][18][19][20][21].…”

Quantitative imaging methods in osteoporosis

“…Pulkkinen et al extracted several geometrical and trabecular parameters from plain pelvic radiographs and related these to hip fracture risk (20). It has also been shown that bone densityand structure-related parameters can be calculated from radiographs of the proximal tibia in cadavers (21) and in subjects with osteoarthritis (22).…”

Quantifying Subresolution 3D Morphology of Bone with Clinical Computed Tomography

“…4,19,26 Textural analysis of 2D radiographs has been shown to be sensitive to OA-related structural alterations and changes in bone density of subchondral bone. 13,14,19 For volumetric data, grey-level co-occurrence matrix (GLCM) based texture analysis, first introduced by Haralick, 11,12 has been previously applied to medical CT imaging of bone. 8,20,22 Moreover, GLCM parameters have shown good correlations to the BV/TV and biomechanical properties of bone from lCT data when the volumetric data is re-projected in 2D.…”