Mammographic density as a marker of susceptibility to breast cancer: a hypothesis

We propose that radiological features of breast tissue provide an index of cumulative exposure to the current and past hormonal and reproductive events that influence breast cancer incidence. The changes in breast tissue that occur with ageing, and changes in the associated radiological features of the breast, are similar to the concept of "breast tissue ageing" proposed by Pike, and may explain features of the age-specific incidence of breast cancer, both within the population and between populations. These radiological features can be observed and measured, can be related directly to risk of breast cancer, and are likely to be of value in research into the etiology of breast cancer. Identification of the sources of variation in this radiological characteristic of the breast is likely to lead to a better understanding of the factors that cause breast cancer and to new approaches to prevention of the disease.

Field nonuniformity correction for quantitative analysis of digitized mammograms

Several factors, including the heel effect, variation in distance from the x-ray source to points in the image and path obliquity contribute to the signal nonuniformity of mammograms. To best use digitized mammograms for quantitative image analysis, these field non-uniformities must be corrected. An empirically based correction method, which uses a bowl-shaped calibration phantom, has been developed. Due to the annular spherical shape of the phantom, its attenuation is constant over the entire image. Remaining nonuniformities are due only to the heel and inverse square effects as well as the variable path through the beam filter, compression plate and image receptor. In logarithmic space, a normalized image of the phantom can be added to mammograms to correct for these effects. Then, an analytical correction for path obliquity in the breast can be applied to the images. It was found that the correction causes the errors associated with field nonuniformity to be reduced from 14% to 2% for a 4 cm block of material corresponding to a combination of 50% fibroglandular and 50% fatty breast tissue. A repeatability study has been conducted to show that in regions as far as 20 cm away from the chest wall, variations due to imaging conditions and phantom alignment contribute to <2% of overall corrected signal.

Biomechanical 3-D finite element modeling of the human breast using MRI data

Breast tissue deformation modeling has recently gained considerable interest in various medical applications. A biomechanical model of the breast is presented using a finite element (FE) formulation. Emphasis is given to the modeling of breast tissue deformation which takes place in breast imaging procedures. The first step in implementing the FE modeling (FEM) procedure is mesh generation. For objects with irregular and complex geometries such as the breast, this step is one of the most difficult and tedious tasks. For FE mesh generation, two automated methods are presented which process MRI breast images to create a patient-specific mesh. The main components of the breast are adipose, fibroglandular and skin tissues. For modeling the adipose and fibroglandular tissues, we used eight noded hexahedral elements with hyperelastic properties, while for the skin, we chose four noded hyperelastic membrane elements. For model validation, an MR image of an agarose phantom was acquired and corresponding FE meshes were created. Based on assigned elasticity parameters, a numerical experiment was performed using the FE meshes, and good results were obtained. The model was also applied to a breast image registration problem of a volunteer's breast. Although qualitatively reasonable, further work is required to validate the results quantitatively.

Variables impacting on patients' perceptions of discharge from short-stay hospitalisation or same-day surgery

The paper presents components of a study (n = 929) that was designed to examine, at one specific point in time, the hospital experience of the patient and the patient's corresponding recovery at home. Variables that captured the hospitalization and recovery experience relate to the degree of patient involvement in decisions about their treatment and discharge plans. Levels of health and recovery-related information reported by patients and their level of confidence in ability to resume regular activities once home were also measured. In general, individuals reported what many would consider having received less than optimal levels of information about their illness and recovery at home. Many patients also reported that they neither participated, nor were consulted on their needs or perceptions during their hospitalization. Expectations were that problems that patients might experience once home would have their origins in problems from within the community. However, the community resources were found to be less implicated and hospital resources more so. This suggests the importance of examining institutional issues even when one is focusing on the delivery of community services.

Radiologists' preferences for digital mammographic display. The International Digital Mammography Development Group

PURPOSE

To determine the preferences of radiologists among eight different image processing algorithms applied to digital mammograms obtained for screening and diagnostic imaging tasks.

MATERIALS AND METHODS

Twenty-eight images representing histologically proved masses or calcifications were obtained by using three clinically available digital mammographic units. Images were processed and printed on film by using manual intensity windowing, histogram-based intensity windowing, mixture model intensity windowing, peripheral equalization, multiscale image contrast amplification (MUSICA), contrast-limited adaptive histogram equalization, Trex processing, and unsharp masking. Twelve radiologists compared the processed digital images with screen-film mammograms obtained in the same patient for breast cancer screening and breast lesion diagnosis.

RESULTS

For the screening task, screen-film mammograms were preferred to all digital presentations, but the acceptability of images processed with Trex and MUSICA algorithms were not significantly different. All printed digital images were preferred to screen-film radiographs in the diagnosis of masses; mammograms processed with unsharp masking were significantly preferred. For the diagnosis of calcifications, no processed digital mammogram was preferred to screen-film mammograms.

CONCLUSION

When digital mammograms were preferred to screen-film mammograms, radiologists selected different digital processing algorithms for each of three mammographic reading tasks and for different lesion types. Soft-copy display will eventually allow radiologists to select among these options more easily.

Image processing algorithms for digital mammography: a pictorial essay

Digital mammography systems allow manipulation of fine differences in image contrast by means of image processing algorithms. Different display algorithms have advantages and disadvantages for the specific tasks required in breast imaging-diagnosis and screening. Manual intensity windowing can produce digital mammograms very similar to standard screen-film mammograms but is limited by its operator dependence. Histogram-based intensity windowing improves the conspicuity of the lesion edge, but there is loss of detail outside the dense parts of the image. Mixture-model intensity windowing enhances the visibility of lesion borders against the fatty background, but the mixed parenchymal densities abutting the lesion may be lost. Contrast-limited adaptive histogram equalization can also provide subtle edge information but might degrade performance in the screening setting by enhancing the visibility of nuisance information. Unsharp masking enhances the sharpness of the borders of mass lesions, but this algorithm may make even an indistinct mass appear more circumscribed. Peripheral equalization displays lesion details well and preserves the peripheral information in the surrounding breast, but there may be flattening of image contrast in the nonperipheral portions of the image. Trex processing allows visualization of both lesion detail and breast edge information but reduces image contrast.

Screen-film and digital mammography. Image quality and radiation dose considerations

Factors affecting image quality and patient dose in screen-film and digital mammography have been discussed. Some proposed parameters for judging image quality and breast exposure measurements and dose calculations relating to changes in image quality factors have been reviewed. It is important to remember that the goal in making a mammogram is to obtain as much diagnostic information as possible at the lowest dose compatible with that information. As noted previously, this necessitates compromises (i.e., an optimization of factors that affect image quality). These include beam quality, compression, imaging geometry, grids, receptor characteristics, processing of the film or digital image, and display and viewing conditions. If this is done correctly, a high-quality mammogram can be obtained at a reasonably low dose to the patient. The goal is not simply to use as low a dose as possible, because if this is done there is a large risk of degrading the performance of mammography in detecting or accurately characterizing small, node-negative cancers.

Mammographic densities and risk of breast cancer among subjects with a family history of this disease

BACKGROUND

A family history of breast cancer is known to increase risk of the disease, but other genetic and environmental factors that modify this risk are likely to exist. One of these factors is mammographic density, and we have sought evidence that it is associated with increased risk of breast cancer among women with a family history of breast cancer.

METHODS

We used data from a nested case-control study based on the Canadian National Breast Screening Study (NBSS). From 354 case patients with incident breast cancer detected at least 12 months after entry into the NBSS and 354 matched control subjects, we analyzed subjects who were identified as having a family history of breast cancer according to one of three, nonmutually exclusive, criteria. We compared the mammographic densities of case patients and control subjects by radiologic and computer-assisted methods of measurement.

RESULTS

After adjustment for other risk factors for breast cancer, the relative risks (RRs) between the most and least extensive categories of breast density were as follows: For at least one first-degree relative with breast cancer, RR = 11.14 (95% confidence interval [CI] = 1.54-80.39); for at least two affected first- or second-degree relatives, RR = 2.57 (95% CI = 0.23-28.22); for at least one first- or second-degree relative with breast cancer, RR = 5.43 (95% CI = 1.85-15.88).

CONCLUSIONS

These results suggest that mammographic density may be strongly associated with risk of breast cancer among women with a family history of the disease. Because mammographic densities can be modified by dietary and hormonal interventions, the results suggest potential approaches to the prevention of breast cancer in women with a family history of breast cancer.

Macronutrient intake and change in mammographic density at menopause: results from a randomized trial

To examine the effects of dietary fat intake on breast cancer risk, we are conducting a randomized trial of dietary intervention in women with extensive areas of radiologically dense breast tissue on mammography, a risk factor for breast cancer. Early results show that after 2 years on a low-fat, high-carbohydrate diet there is a significant reduction in area of density, particularly in women going through menopause. In women who went through menopause during the 2-year follow-up, the mean decreases in area of density and percentage of density in the intervention group were 11.0 cm2 and 11.0%, respectively, whereas the control group decreased 4.5 cm2 and 5.2%. The purpose of this analysis was to determine whether changes in intake of specific macronutrients could account for the observed reduction in breast density in these women. Differences between 2-year and baseline values of macronutrients (averaged over 3 nonconsecutive days of food intake) were calculated. We examined the effect of dietary variables, adjusted for changes in total calorie intake and weight and for family history of breast cancer, on changes in area of density and percentage of density using linear regression. Reduction in total or saturated fat intake or cholesterol intake was significantly associated with decreased dense area (p < or = .004). The most significant dietary variable associated with reduction in percentage of density was reduction in dietary cholesterol intake (P = 0.001), although reducing saturated fat intake was of borderline significance (P = 0.05). The effect of the membership in the intervention and control groups on change in area of density or percentage of density was reduced by models that included changes in intake of any fat, or cholesterol, or carbohydrates. The observation of an effect of diet at menopause on breast density, a marker of increased risk of breast cancer, may be an indication that exposures at this time have an enhanced effect on subsequent risk.

The quantitative analysis of mammographic densities

Quantitative classification of mammographic parenchyma based on radiological assessment has been shown to provide one of the strongest estimates of the risk of developing breast cancer. Existing classification schemes, however, are limited by coarse category scales. In addition, subjectivity can lead to sizeable interobserver and intraobserver variations. Here, we propose an interactive thresholding technique applied to digitized film-screen mammograms, which assesses the proportion of the mammographic image representing radiographically dense tissue. Observers viewed images on a CRT display and selected grey-level thresholds from which the breast and regions of dense tissue in the breast were identified. The proportion of radiographic density was then calculated from the image histogram. The technique was evaluated for the mammograms of 30 women and is well correlated (R > 0.91, Spearman coefficient) with a six-category subjective classification of radiographic density by radiologists. The technique was found to be very reliable with an intraclass correlation coefficient between observers typically R > 0.9. This technique may have a role in routine mammographic analysis for the purpose of assessing risk categories and as a tool in studies of the etiology of breast cancer, in particular for monitoring changes in breast parenchyma during potential preventive interventions.

Mammographic densities and breast cancer risk

The radiological appearance of the female breast varies among individuals because of differences in the relative amounts and X-ray attenuation characteristics of fat and epithelial and stromal tissues. Fat is radiolucent and appears dark on a mammogram, and epithelium and stroma are radiodense and appear light. We review here the evidence that these variations, known as mammographic parenchymal patterns, are related to risk of breast cancer. Studies that used quantitative measurement to classify mammographic patterns have consistently found that women with dense tissue in more than 60-75% of the breast are at four to six times greater risk of breast cancer than those with no densities. These risk estimates are independent of the effects of other risk factors and have been shown to persist over at least 10 years of follow up. Estimates of attributable risk suggest that this risk factor may account for as many as 30% of breast cancer cases. Mammographically dense breast tissue is associated both with epithelial proliferation and with stromal fibrosis. The relationship between these histological features and risk of breast cancer may by explained by the known actions of growth factors that are thought to play important roles in breast development and carcinogenesis. Mammographically dense tissue differs from most other breast cancer risk factors in the strength of the associated relative and attributable risks for breast cancer, and because it can be changed by hormonal and dietary interventions. This risk factor may be most useful as a means of investigating the etiology of breast cancer and of testing hypotheses about potential preventive strategies.

The effect of phosphor persistence on image quality in digital x-ray scanning systems

A digital x-ray scanning system offers several advantages over conventional film-screen systems. However, there are sources of image degradation resulting from the scanning motion, such as motion blur due to the temporal response of the phosphor. This mechanism produces an asymmetrical blur, requiring the use of the complex optical transfer function (OTF) rather than the normal modulation transfer function (MTF) for correct characterization of image resolution. The luminescence response of eight phosphors was measured under pulsed x-ray excitation. A weighted exponential model was used to represent the primary luminescence. The dominant luminescence life-times ranged from 2.7 microseconds for Gd2O2S:Pr to 558 microseconds for Gd2O2S:Tb. The long term response was also measured, monitoring significant increases in a slow form of luminescence known as afterglow. Afterglow was modeled by an inverse power law equation. Afterglow was found to be strong in two of the phosphors studied (ZnCdS:Ag and YTaO4). In selecting a phosphor for a scanning system, it must satisfy several criteria, including a fast temporal response. Thus, a phosphor like Gd2O2S:Tb, which has a slow luminescence, but otherwise excellent imaging properties, may not be as useful as a more rapid phosphor like CsI:Tl.

Analysis of mammographic density and breast cancer risk from digitized mammograms

To evaluate the association between mammographic density and breast cancer risk, a simple, observer-assisted technique called interactive thresholding was developed that allows reliable quantitative assessment of mammographic density with use of a computer workstation. Use of this technique helps confirm that mammographic density is one of the strongest risk factors for breast cancer and is present in a large proportion of breast cancer cases. The strong relationship between mammographic density and breast cancer risk suggests that the causes of breast cancer may be better understood by identifying the factors associated with mammographically dense tissue and determining how such tissue changes as these factors vary. Furthermore, because it can be modified, mammographic density may also be a good vehicle for the development and monitoring of potential preventive strategies. Areas of ongoing investigation include evaluating a potential genetic component of mammographic density by comparing density measurements in twins and understanding changes in density relative to age, menopausal status, exogenous hormone use, and exposure to environmental carcinogens. In addition, work is ongoing to establish measurements from imaging modalities other than mammography and to relate these measurements directly to breast cancer risk.

The relationship of anthropometric measures to radiological features of the breast in premenopausal women

We studied 273 premenopausal women recruited from mammography units who had different degrees of density of the breast parenchyma on mammography, in whom we measured height, weight and skinfold thicknesses. Mammograms were digitized to high spatial resolution by a scanning densitometer and images analysed to measure the area of dense tissue and the total area of the breast. Per cent density and the area of non-dense tissue were calculated from these measurements. We found that the mammographic measures had different associations with body size. Weight and the Quetelet index of obesity were strongly and positively associated with the area of non-dense tissue and with the total area of the breast, but less strongly and negatively correlated with the area of dense tissue. We also found a strong inverse relationship between the areas of radiologically dense and non-dense breast tissue. Statistical models containing anthropometric variables explained up to 8% of the variance in dense area, but explained up to 49% of the variance in non-dense area and 43% of variance in total area. These results suggest that aetiological studies in breast cancer that use mammographic density should consider dense and non-dense tissues separately. In addition to per cent density, methods should be examined that combine information from these two tissues.

Mammographic densities and breast cancer risk

Variations between individuals in the radiographic appearance, or mammographic pattern, of the female breast arise because of differences in the relative amounts and X-ray attenuation characteristics of fat and connective and epithelial tissue. Studies using quantitative methods of assessment have consistently shown these variations to be strongly related to risk of breast cancer. Individuals with extensive areas of radiologically dense breast tissue on the mammogram have been found to have a risk of breast cancer that is four to six times higher than women with little or no density. In this paper, we propose a model for the relationship of mammographic densities to risk of breast cancer. We propose that the risk of breast cancer associated with mammographically dense breast tissue is due to the combined effects of two processes: cell proliferation (mitogenesis), induced by growth factors and sex hormones and influenced by reproductive risk factors for breast cancer; and damage to the DNA of dividing cells (mutagenesis) by mutagens generated by lipid peroxidation. We review the evidence that each of these processes is associated with mammographic densities and propose further work that we believe should be done to clarify these relationships.

X-ray characterization of breast phantom materials

A pulse-height spectroscopic technique is used to measure the linear attenuation coefficients of commercially available composite phantom materials designed to simulate the attenuation characteristics of breast fat and breast glandular tissue. The manufacturers have specified the composition of these materials with the goal of matching the linear attenuation coefficients of breast tissues, calculated using the mixture rule. Over the energy range 18 to 100 keV, measurements from these materials are in close agreement with manufacturers' predictions and with previously measured linear attenuation coefficients of breast tissue samples.

Developing and supporting school health programs. Role for family physicians

PROBLEM BEING ADDRESSED

School staff are anxious about the demands on their time associated with a perceived increase in health problems among their students.

OBJECTIVE OF PROGRAM

To respond to these concerns by developing a health committee in two elementary schools and one high school. The health committee could perform needs assessments and, with the results of these assessments and a careful literature review, could develop health policies and procedures appropriate to the school environment and to evolving community expectations.

MAIN COMPONENTS OF PROGRAM

A committee of four family physicians (nonremunerated parents of students), one of whom served as Chair, four school administrators, and one part-time remunerated nurse practitioner explored aspects of illness in the schools. They studied approaches to acute and chronic student illness; emergency response; management of children with special needs; environmental safety; health promotion; and the availability and quality of resources for learning about health for teachers, administrators, parents, and students.

CONCLUSION

Opportunities exist for family physicians to expand their involvement in child and adolescent health in schools. Involvement should be collaborative and multidisciplinary and reflect community interests and needs.

Computed Tomography Artefacts: An Experimental Investigation of Causative Factors

N Strumas, O Antonyshyn, MJ Yaffe, G Mawdsley, P Cooper. Computed tomography artefacts: An experimental investigation of causative factors. Can J Plast Surg 1998;6(1):23-29.

The factors that produce computed tomography (CT) artefacts associated with craniofacial fixation devices were analyzed. The effects of attenuation, motion, partial volume and implant shape were evaluated. By using a CT phantom model with an engine to produce reproducible motion, a vitallium rod, fixation plate and blank were scanned sequentially. for each experimental condition, the degree of artefact produced was quantified by measuring the standard deviation of the CT number at standardized regions of interest, and a comparative analysis was performed. Motion produced the greatest degree of artefact. Both the frequency and direction of motion were important, with high frequency motion in the plane of the CT slice producing the greatest degree of CT artefact. Partial volume artefacts increased as the volume of material in the plane of section increased. The amount of artefact produced was dependent on the volume of material x-rays passed through the object rather than on the geometric configuration. Attenuation effects were evaluated. Results revealed that the amount of artefact was greatest between highly attenuating objects.

Breast cancer risk and measured mammographic density

It has been well established that there is a positive correlation between the dense appearance of breast stroma and parenchyma on a mammogram and the risk of breast cancer. Subjective assessment by radiologists indicated relative risks on the order of 4 to 6 for the group of women whose mammograms showed a density of over 75% or more of the projected area compared to those with an absence of density. In order to obtain a more quantitative, continuous and reproducible means of estimating breast density, which is sensitive to small changes, we have developed quantitative methods for the analysis of mammographic density, which can be applied to digitized mammograms. These techniques have been validated in a nested case-control study on 708 women aged 40-59 years (on entry) who participated in a national mammographic screening study. An interactive image segmentation method and two completely automated techniques based on image texture and grey scale histogram measures have been developed and evaluated. While our methods all show statistically significant risk factors for dense breasts, the interactive method currently provides the highest risk values (relative risk 4.0, 95% confidence interval (CI) = 2.12-7.56) compared to a measure based on the shape of the image histogram (relative risk 3.35, 95% CI = 1.57-7.12) or the fractal dimension of the mammogram (relative risk 2.54, 95% CI = 1.14-5.68). All methods were highly consistent between images of the left and right breast and between the two standard views (cranio-caudal and medio-lateral oblique) of each breast, so that studies can be done by sampling only one of the four views per examination. There is a large number of factors in addition to breast density which affect the appearance of the mammogram. In particular, the assessment of density is made difficult where the breast is not uniformly compressed, e.g. at the periphery. We have designed and are currently evaluating an image processing algorithm that effectively corrects for this problem and have considered methods for controlling some of the variables of image acquisition in prospective studies. Measurements of breast density may be helpful in assigning risk groups to women. Such measurements might guide the frequency of mammographic screening, aid the study of breast cancer aetiology, and be useful in monitoring possible risk-modifying interventions. Using our techniques, we have been able to show that reduction of the proportion of fat in the diet can result in reductions of breast density, although the direct connection to risk has not yet been made. The relationship between breast density and hormone-related and genetic factors is also of great interest. It is often not possible or ethical to obtain mammograms on some groups of women for whom information on density would be very useful. This includes younger women as well as groups in which it would be desirable to obtain such information at frequent intervals. For this reason, we are exploring the use of imaging approaches such as ultrasound and magnetic resonance imaging, which do not require ionizing radiation, to make measurements analogous to those now being performed by using X-ray mammograms.

Automated analysis of mammographic densities and breast carcinoma risk

BACKGROUND

There is considerable evidence that one of the strongest risk factors for breast carcinoma can be assessed from the mammographic appearance of the breast. However, the magnitude of the risk factor and the reliability of the prediction depend on the method of classification. Subjective classification requires specialized observer training and suffers from inter- and intraobserver variability. Furthermore, the categoric scales make it difficult to distinguish small differences in mammographic appearance. To address these limitations, automated analysis techniques that characterize mammographic density on a continuous scale have been considered, but as yet, these have been evaluated only for their ability to reproduce subjective classifications of mammographic parenchyma.

METHODS

In this study, using a nested case-control design, the authors evaluated the direct association between breast carcinoma risk and quantitative image features derived from automated analysis of digitized film mammograms. Two parameters, one describing the distribution of breast tissue density as reflected by brightness of the mammogram (regional skewness) and the other characterizing texture (fractal dimension), were calculated for images from 708 subjects identified from the Canadian National Breast Screening Study.

RESULTS

These parameters were evaluated for their ability to distinguish cases (those women who developed breast carcinoma) from controls. It was found that both the skewness and fractal parameters were significantly related to risk of developing breast carcinoma.

CONCLUSIONS

Although the relative risk estimates were moderate (typically > 2.0) and less than those from subjective classification or for an interactive computer method the authors have previously described, they are comparable to other risk factors for the disease. The observer independence and reproducibility of the automated methods may facilitate their more widespread use.

Thickness-equalization processing for mammographic images

A digital postprocessing technique was used to compensate for the limitations of laser film or cathode-ray-tube devices used to display digital mammograms. An algorithm identified and equalized for the large change in digital signal caused by the reduction in thickness at the margin of the compressed breast. The resulting images reflected only breast composition, and so the number of gray levels needed to display the processed image was greatly reduced, which facilitated presentation and analysis.