Temporal radiographic texture analysis in the detection of periprosthetic osteolysis.

Periprosthetic osteolysis is one of the most serious long-term problems in total hip arthroplasty. It has been primarily attributed to the body's inflammatory response to submicron polyethylene particles worn from the hip implant, and it leads to bone loss and structural deterioration in the surrounding bone. It was previously demonstrated that radiographic texture analysis (RTA) has the ability to distinguish between osteolysis and normal cases at the time of clinical detection of the disease; however, that analysis did not take into account the changes in texture over time. The goal of this preliminary analysis, however, is to assess the ability of temporal radiographic texture analysis (tRTA) to distinguish between patients who develop osteolysis and normal cases. Two tRTA methods were used in the study: the RTA feature change from baseline at various follow-up intervals and the slope of the best-fit line to the RTA data series. These tRTA methods included Fourier-based and fractal-based features calculated from digitized images of 202 total hip replacement cases, including 70 that developed osteolysis. Results show that separation between the osteolysis and normal groups increased over time for the feature difference method, as the disease progressed, with area under the curve (AUC) values from receiver operating characteristic analysis of 0.65 to 0.72 at 15 years postsurgery. Separation for the slope method was also evident, with AUC values ranging from 0.65 to 0.76 for the task of distinguishing between osteolysis and normal cases. The results suggest that tRTA methods have the ability to measure changes in trabecular structure, and may be useful in the early detection of periprosthetic osteolysis.

Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment.

PURPOSE: The purpose of the study was to evaluate the usefulness of power law spectral analysis on mammographic parenchymal patterns in breast cancer risk assessment. MATERIALS AND METHODS: Mammograms from 172 subjects (30 women with the BRCA1/BRCA2 gene mutation and 142 low-risk women) were retrospectively collected and digitized. Because age is a very important risk factor, 60 low-risk women were randomly selected from the 142 low-risk subjects and were age matched to the 30 gene mutation carriers. Regions of interest were manually selected from the central breast region behind the nipple of these digitized mammograms and subsequently used in power spectral analysis. The power law spectrum of the form P(f) = B/f(beta) was evaluated for the mammographic patterns. The performance of exponent beta as a decision variable for differentiating between gene mutation carriers and low-risk women was assessed using receiver operating characteristic analysis for both the entire database and the age-matched subset. RESULTS: Power spectral analysis of mammograms demonstrated a statistically significant difference between the 30 BRCA1/BRCA2 gene mutation carriers and the 142 low risk women with an average beta values of 2.92 (+/-0.28) and 2.47(+/-0.20), respectively. An A (z) value of 0.90 was achieved in distinguishing between gene mutation carriers and low-risk women in the entire database, with an A (z) value of 0.89 being achieved on the age-matched subset. CONCLUSIONS: The BRCA1/BRCA2 gene mutation carriers and low-risk women have different mammographic parenchymal patterns. It is expected that women identified as high risk by computerized feature analyses might potentially be more aggressively screened for breast cancer.

Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms.

RATIONALE AND OBJECTIVES: Mammographic density and parenchymal patterns have been shown to be related to the risk of developing breast cancer. Thus, computerized texture analysis of breast parenchymal patterns on mammograms may be useful in assessing breast cancer risk. MATERIALS AND METHODS: A comparative evaluation was conducted of various computer-extracted texture features of mammographic parenchymal patterns of women with BRCA1/BRCA2 gene mutations and those of women at low risk of developing breast cancer. Mammograms from 172 subjects (30 women with either the BRCA1 or BRCA2 gene mutation and 142 low-risk women) were analyzed. Computerized texture features were extracted from regions-of-interest to assess the mammographic parenchymal patterns in the images. Receiver operating characteristic analysis was used to assess the performance of these features in the task of distinguishing between the two groups of women. RESULTS: Quantitative texture analysis on digitized mammograms demonstrated that gene-mutation carriers and low-risk women have different mammographic parenchymal patterns. Gene-mutation carriers presented with parenchymal patterns that were denser, coarser, and lower in contrast than those of the low-risk group. For the gene-mutation carriers, their mammographic patterns appear to contain less high-frequency component as indicated by higher coarseness values, lower fractal dimensions, and smaller edge gradients, which yielded corresponding A(z) values of 0.79, 0.84, and 0.78, respectively, in the task of distinguishing between gene-mutation carriers and the low-risk group with the entire dataset. The contrast measure calculated from co-occurrence matrix method, which describes local image variation, yielded an A(z) value of 0.86 in distinguishing between the two groups of women. CONCLUSION: Computerized texture analysis of mammograms provides radiographic descriptors of mammographic parenchymal patterns. The computer-extracted features may be useful for identifying women at high risk for breast cancer and for monitoring the treatment of breast cancer patients.

Investigation of physical image quality indices of a bone densitometry system.

Osteoporosis is a disease characterized by a loss of bone mass and a deterioration of bone structure. Bone mineral density (BMD) measures bone mass and is currently the method used to diagnose osteoporosis, while computerized radiographic texture analysis (RTA) is being investigated as a measure of bone structure. The GE/Lunar PIXI peripheral bone densitometer (PD) system, which uses dual-energy subtraction to measure BMD, also provides a digital image of the heel or forearm. The goal of our current research was to evaluate the physical imaging properties of the PIXI system (pixel size of 0.2 mm) compared to a Fuji computed radiography (CR) system (pixel size of 0.1 mm) to determine its suitability for texture analysis from image data. Contrast was measured using a series of uniform images covering the useful clinical exposure range. Spatial resolution was characterized by the presampling modulation transfer function (MTF) determined by an edge method. Noise power spectra (NPS) for different exposures were calculated using a two-dimensional Fourier analysis method. The expectation modulation transfer function was measured and combined with the NPS data to calculate the noise-equivalent number of quanta. The slope of the characteristic curve of the peripheral densitometer (PD) system was found to be position dependent across the image, although this dependence was substantially reduced by use of the system's clinical-settings corrections. An MTF value of 0.5 was found at 0.5 cycles/mm for the densitometry system compared to the same value at 1.6 cycles/mm for the CR system. Unlike the CR system, the NPS of the densitometry system was found not to be directionally dependent and did not drop off at higher spatial frequencies.

Comparison of radiographic texture analysis from computed radiography and bone densitometry systems.

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 x 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.