Michael R. Chinander

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

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

P\left( f \right) = {B \mathord{\left/ {\vphantom {B {f^\beta }}} \right. \kern-\nulldelimiterspace} {f^\beta }}

Normalized BMD as a predictor of bone strength.

was evaluated for the mammographic patterns. The performance of exponent β 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 β values of 2.92 (±0.28) and 2.47(±0.20), respectively. An Az value of 0.90 was achieved in distinguishing between gene mutation carriers and low-risk women in the entire database, with an Az 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.

Temporal radiographic texture analysis in the detection of periprosthetic osteolysis

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 (R2) improved over the use of BMD alone. For bone strength, the R2 was improved from 0.24 using conventional BMD to 0.48 using a four-predictor model. Similar results were obtained in the prediction of Youngs modulus, i.e., the R2 was 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.

Investigation of physical image quality indices of a bone densitometry system

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.

Development of a model for breast tomosynthesis image acquisition

We are developing computerized methods for characterizing the bone texture pattern from digitized skeletal radiographs. For this method to be useful clinically, it must be able to distinguish between weak and strong bone under the range of exposure conditions potentially encountered in the clinical setting. In this study, we examined the effect of exposure conditions on Fourier-based texture features. Thirty-four femoral specimens from total hip arthroplasties were radiographed multiple times under different exposure conditions. The specimens underwent mechanical strength testing from which load to failure values were obtained. The performance of the texture features were investigated in the task of distinguishing between strong and weak bone as characterized by the load to failure values. The texture features showed no dependence upon focal spot size of the x-ray tube or magnification. The texture features did show a dependence with relative exposure, peak kilovoltage, and amount of scattering material.

Investigation of using bone texture analysis on bone densitometry images.

RATIONALE AND OBJECTIVES In the noninvasive evaluation of bone quality, bone mineral density (BMD) has been shown to be the single most important predictor of bone strength and osteoporosis-related fracture. Among the methods of measuring BMD, dual x-ray absorptiometry (DXA) has widespread acceptance due to its low radiation, low cost, and high precision. However, DXA measures area BMD instead of true volumetric density; thus, a larger bone will tend to have a high BMD than will a smaller bone. Therefore, the comparison of BMDs of bones of different sizes can be misleading. In this study, the authors tried to compensate for the size effect by normalizing the area BMD with bone size as measured from a standard pelvic radiograph. MATERIALS AND METHODS The overall method for calculation of normalized BMD included conventional area-based BMD from DXA and the extraction of geometric measures from pelvic radiographs. The database for analysis included 34 femoral neck specimens. Regression analysis was performed between the normalized volumetric BMD, measured from femoral neck region, and the mechanical properties obtained from trabecular bone cubes machined from the same region. RESULTS After normalization of the area BMD, the coefficient of determination increased from 0.30 to 0.43 for the Young modulus and from 0.27 to 0.37 for bone compressive strength. CONCLUSION A noninvasive method of normalizing BMD can improve the prediction of bone mechanical properties and has potential in monitoring changes in growing skeletons and in the clinical evaluation of bone quality.

Computerized analysis of mammographic parenchymal patterns using fractal analysis

Periprosthetic osteolysis is one of the most serious long-term problems in total hip arthroplasty. It has been primarily attributed to the bodys 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.