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Comparison of radiographic texture analysis from computed radiography and bone densitometry systems
Author(s) -
Wilkie Joel R.,
Giger Maryellen L.,
Chinander Michael R.,
Vokes Tamara J.,
Li Hui,
Dixon Larry,
Jaros Vit
Publication year - 2004
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 - 10.1118/1.1650529
Subject(s) - densitometry , osteoporosis , radiography , medicine , bone mineral , computed radiography , digital radiography , nuclear medicine , heel , biomedical engineering , radiology , image quality , anatomy , artificial intelligence , computer science , pathology , image (mathematics)
Osteoporosis is a disease that results in an increased risk of bone fracture due to a loss of bone mass and deterioration of bone structure. Bone mineral density (BMD) provides a measure of bone mass and is frequently measured by bone densitometry systems to diagnose osteoporosis. In addition, computerized radiographic texture analysis (RTA) is currently being investigated as a measure of bone structure and as an additional diagnostic predictor of osteoporosis. In this study, we assessed the ability of a peripheral bone densitometry (PD) system to yield images useful for RTA. The benefit of such a system is that it measures BMD by dual‐energy x‐ray absorptiometry and therefore provides high‐ and low‐energy digital radiographic images. The bone densitometry system investigated was the GE/Lunar PIXI, which provides 512 × 512 digital images of the heel or forearm (0.2 mm pixels). We compared texture features of heel images obtained with this PD system to those obtained on a Fuji computed radiography (CR) system (0.1 mm pixels). Fourier and fractal‐based texture features of images from 24 subjects who had both CR and BMD exams were calculated, and correlation between the two systems was analyzed. Fourier‐based texture features characterize the magnitude, frequency content, and orientation of the trabecular bone pattern. Good correlation was found between the two modalities for the first moment (FMP) with r = 0.71( p value < 0.0001 ) and for minimum FMP with r = 0.52( p value = 0.008 ) . Root‐mean‐square (RMS) did not correlate with r = 0.31( p value > 0.05 ) , while the standard deviation of the RMS did correlate with r = 0.79( p value < 0.0001 ) . Good correlation was also found between the two modalities for the fractal‐based texture features with r = 0.79( p value < 0.0001 ) for the global Minkowski dimension and r = 0.63( p value = 0.0007 ) for the fractal dimension from a box counting method. The PD system therefore may have the potential for yielding heel images suitable for RTA.