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Characterization of bone quality using computer‐extracted radiographic features
Author(s) -
Jiang Chunsheng,
Giger Maryellen L.,
Chinander Michael R.,
Martell John M.,
Kwak Sandy,
Favus Murray J.
Publication year - 1999
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.598604
Subject(s) - femoral neck , bone mineral , radiography , medicine , densitometry , osteoporosis , trabecular bone , bone density , pelvis , nuclear medicine , biomedical engineering , radiology , pathology
Both bone mineral density (BMD) and trabecular structure are important determinates of bone mechanical properties. However, neither BMD or trabecular structural features can completely explain the variations in bone mechanical properties. In this study, we combine BMD and bone structural features to characterize bone mechanical behavior. Radiographs were obtained from 34 femoral neck specimens excised during total hip arthroplasties. Each neck radiograph was digitized and a region of interest (ROI) was selected from the medial side of the femoral neck. Textural features, the global Minkoswski dimension and trabecular orientation, were extracted from each ROI image using Minkowski dimension analysis. The BMD of each specimen was measured using dual‐energy x‐ray absorptiometry (DXA) and subsequently normalized by bone size as measured from a standard pelvis radiograph. Mechanical testing was performed on the trabecular bone cubes machined from each femoral neck to yield bone mechanical properties. Multiple regression was performed to select the best features to predict bone mechanical properties. The results suggest that, using multiple predictors including normalized BMD structural features, and patient age, the coefficients of determination( R 2 ) improved over the use of BMD alone. For bone strength, the R 2was improved from 0.24 using conventional BMD to 0.48 using a four‐predictor model. Similar results were obtained in the prediction of Young's modulus, i.e., the R 2was improved from 0.25 to 0.55 in going from the model using conventional BMD to a four‐predictor model. This study demonstrates the contributions of normalized BMD, structural features, and age to bone mechanical properties, and suggests a potential method for the noninvasive evaluation of bone mechanical properties.