An update of the Angiosperm Phylogeny Group (APG) classification of the orders and families of angiosperms is presented. Several new orders are recognized: Boraginales, Dilleniales, Icacinales, ...Metteniusiales and Vahliales. This brings the total number of orders and families recognized in the APG system to 64 and 416, respectively. We propose two additional informal major clades, superrosids and superasterids, that each comprise the additional orders that are included in the larger clades dominated by the rosids and asterids. Families that made up potentially monofamilial orders, Dasypogonaceae and Sabiaceae, are instead referred to Arecales and Proteales, respectively. Two parasitic families formerly of uncertain positions are now placed: Cynomoriaceae in Saxifragales and Apodanthaceae in Cucurbitales. Although there is evidence that some families recognized in APG III are not monophyletic, we make no changes in Dioscoreales and Santalales relative to APG III and leave some genera in Lamiales unplaced (e.g. Peltanthera). These changes in familial circumscription and recognition have all resulted from new results published since APG III, except for some changes simply due to nomenclatural issues, which include substituting Asphodelaceae for Xanthorrhoeaceae (Asparagales) and Francoaceae for Melianthaceae (Geraniales); however, in Francoaceae we also include Bersamaceae, Ledocarpaceae, Rhynchothecaceae and Vivianiaceae. Other changes to family limits are not drastic or numerous and are mostly focused on some members of the lamiids, especially the former Icacinaceae that have long been problematic with several genera moved to the formerly monogeneric Metteniusaceae, but minor changes in circumscription include Aristolochiaceae (now including Lactoridaceae and Hydnoraceae; Aristolochiales), Maundiaceae (removed from Juncaginaceae; Alismatales), Restionaceae (now re‐including Anarthriaceae and Centrolepidaceae; Poales), Buxaceae (now including Haptanthaceae; Buxales), Peraceae (split from Euphorbiaceae; Malpighiales), recognition of Petenaeaceae (Huerteales), Kewaceae, Limeaceae, Macarthuriaceae and Microteaceae (all Caryophyllales), Petiveriaceae split from Phytolaccaceae (Caryophyllales), changes to the generic composition of Ixonanthaceae and Irvingiaceae (with transfer of Allantospermum from the former to the latter; Malpighiales), transfer of Pakaraimaea (formerly Dipterocarpaceae) to Cistaceae (Malvales), transfer of Borthwickia, Forchhammeria, Stixis and Tirania (formerly all Capparaceae) to Resedaceae (Brassicales), Nyssaceae split from Cornaceae (Cornales), Pteleocarpa moved to Gelsemiaceae (Gentianales), changes to the generic composition of Gesneriaceae (Sanango moved from Loganiaceae) and Orobanchaceae (now including Lindenbergiaceae and Rehmanniaceae) and recognition of Mazaceae distinct from Phrymaceae (all Lamiales).
Mammographic densities and breast cancer risk Boyd, N F; Lockwood, G A; Byng, J W ...
Cancer epidemiology, biomarkers & prevention,
12/1998, Letnik:
7, Številka:
12
Journal Article
Recenzirano
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 radiographic appearance of the female breast varies from woman to woman depending on the relative amounts of fat and connective and epithelial tissues present. Variations in the mammographic ...density of breast tissue are referred to as the parenchymal pattern of the breast. Fat is radiologically translucent or clear (darker appearance), and both connective and epithelial tissues are radiologically dense (lighter appearance). Previous studies have generally supported an association between parenchymal patterns and breast cancer risk (greater risk with increasing densities), but there has been considerable heterogeneity in risk estimates reported.
Our objective was to determine the level of breast cancer risk associated with varying mammographic densities by quantitatively classifying breast density with conventional radiological methods and novel computer-assisted methods.
From the medical records of a cohort of 45,000 women assigned to mammography in the Canadian National Breast Cancer Screening Study (NBSS), a multicenter, randomized trial, mammograms from 354 case subjects and 354 control subjects were identified. Case subjects were selected from those women in whom histologically verified invasive breast cancer had developed 12 months or more after entering the trial. Control subjects were selected from those of similar age who, after a similar period of observation, had not developed breast cancer. The mammogram taken at the beginning of the NBSS was the image used for measurements. Mammograms were classified into six categories of density, either by radiologists or by computer-assisted measurements. All radiological classification and computer-assisted measurements were made using one craniocaudal view from the breast contralateral to the cancer site in case subjects and the corresponding breast of control subjects. All P values represent two-sided tests of statistical significance.
For all subjects, there was a 43% increase in the relative risk (RR) between the lower and the next higher category of density, as determined by radiologists, and there was a 32% increase as determined by the computer-assisted method. For all subjects, the RR in the most extensive category relative to the least was 6.05 (95% confidence interval CI = 2.82-12.97) for radiologists and 4.04 (95% CI = 2.12-7.69) for computer-assisted methods. Statistically significant increases in breast cancer risk associated with increasing mammographic density were found by both radiologists and computer-assisted methods for women in the age category 40-49 years (P = .005 for radiologists and P = .003 for computer-assisted measurements) and the age category 50-59 years (P = .002 for radiologists and P = .001 for computer-assisted measurements).
These results show that increases in the level of breast tissue density as assessed by mammography are associated with increases in risk for breast cancer.
Information derived from mammographic parenchymal patterns provides one of the strongest indicators of the risk of developing breast cancer. To address several limitations of subjective ...classification of mammographic parenchyma into coarse density categories, we have been investigating more quantitative, objective methods of analysing the film-screen mammogram. These include measures of the skewness of the image brightness histogram, and of image texture characterized by the fractal dimension. Both measures were found to be strongly correlated with radiologists' subjective classifications of mammographic parenchyma (Spearman correlation coefficients, Rs = -0.88 and -0.76 for skewness and fractal dimension measurements, respectively). Further, neither measure was strongly dependent on simulated changes in mammographic technique. Correlation with subjective classification of mammographic density was better when both the skewness and fractal measures were used in combination than when either was used alone. This suggests that each feature provides some independent information.
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.
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.
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.
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.
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.
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).
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.
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.
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.
PDF
