Prediction model for regional or distant recurrence in endometrial cancer based on classical pathological and immunological parameters.

BACKGROUND: Adjuvant therapy increases disease-free survival in endometrial cancer (EC), but has no impact on overall survival and negatively influences the quality of life. We investigated the discriminatory power of classical and immunological predictors of recurrence in a cohort of EC patients and confirmed the findings in an independent validation cohort. METHODS: We reanalysed the data from 355 EC patients and tested our findings in an independent validation cohort of 72 patients with EC. Predictors were selected and Harrell's C-index for concordance was used to determine discriminatory power for disease-free survival in the total group and stratified for histological subtype. RESULTS: Predictors for recurrence were FIGO stage, lymphovascular space invasion and numbers of cytotoxic and memory T-cells. For high risk cancer, cytotoxic or memory T-cells predicted recurrence as well as a combination of FIGO stage and lymphovascular space invasion (C-index 0.67 and 0.71 vs 0.70). Recurrence was best predicted when FIGO stage, lymphovascular space invasion and numbers of cytotoxic cells were used in combination (C-index 0.82). Findings were confirmed in the validation cohort. CONCLUSIONS: In high-risk EC, clinicopathological or immunological variables can predict regional or distant recurrence with equal accuracy, but the use of these variables in combination is more powerful.

Volumetric breast density characteristics as determined from digital mammograms.

In this paper we present the results of an automated and entirely reproducible algorithm that estimates the breast volume, dense tissue volume and the volumetric breast density from digital mammograms. The algorithm was applied to 55, 087 digital images (CC view only) from 15 351 individual women, acquired between 2008 and 2011 at the Sunnybrook Health Sciences Centre in Toronto, Canada. The algorithm is based on a prior calibration of the digital image signal versus tissue thickness and composition, and the thickness of the compressed breast is estimated using an empirical model that corrects the thickness readout of the mammography system as a function of compression force. The mean volumetric density and breast volumes for our study group were 30% and 687 cm(3), respectively. The left and right volumetric density and breast volume were strongly correlated, with a Pearson correlation of 0.92 and 0.91, respectively. The volumetric density decreased from 45% to 25% as age increased from 35 to 75 years, with an increase to 30% at 80 years. For a given woman, the volumetric density decreased at an average rate of -2 density percentage points per year while the breast volume increased by 2% per year.

Long-term results of screening with magnetic resonance imaging in women with BRCA mutations.

BACKGROUND: The addition of breast magnetic resonance imaging (MRI) to screening mammography for women with BRCA mutations significantly increases sensitivity, but there is little data on clinical outcomes. We report screening performance, cancer stage, distant recurrence rate, and breast cancer-specific mortality in our screening study. METHODS: From 1997 to 2009, 496 women aged 25 to 65 years with a known BRCA1/2 mutation, of whom 380 had no previous cancer history, were enrolled in a prospective screening trial that included annual MRI and mammography. RESULTS: In 1847 screening rounds, 57 cancers were identified (53 screen-detected, 1 interval, and 3 incidental at prophylactic mastectomy), of which 37 (65%) were invasive. Sensitivity of MRI vs mammography was 86% vs 19% over the entire study period (P<0.0001), but was 74% vs 35% from 1997 to 2002 (P=0.02) and 94% vs 9% from 2003 to 2009 (P<0.0001), respectively. The relative sensitivities of MRI and mammography did not differ by mutation, age, or invasive vs non-invasive disease. Of the incident cancers, 97% were Stage 0 or 1. Of 28 previously unaffected women diagnosed with invasive cancer, 1 BRCA1 mutation carrier died following relapse of a 3 cm, node-positive breast cancer diagnosed on her first screen at age 48 (annual breast cancer mortality rate=0.5%). Three patients died of other causes. None of the 24 survivors has had a distant recurrence at a median follow-up of 8.4 years since diagnosis. CONCLUSION: Magnetic resonance imaging surveillance of women with BRCA1/2 mutations will detect the majority of breast cancers at a very early stage. The absence of distant recurrences of incident cancers to date is encouraging. However, longer follow-up is needed to confirm the safety of breast surveillance.

Status of cellular immunity lacks prognostic significance in vulvar squamous carcinoma.

OBJECTIVE: It is generally recognized that the immune system has an important role in regulating cancer development. Evidence indicating a prognostic role of the immune system in vulvar carcinoma is scarce. This study investigated the presence and prognostic significance of several aspects of the immune system in vulvar squamous carcinoma. METHODS: The number of intratumoral CD8(+) and Foxp3(+) T-lymphocytes, next to HLA class I (HLA-A, HLA-B/C and ß(2)-m) and indoleamine 2,3-dioxygenase (IDO) expression was determined by immunohistochemistry in a consecutively selected cohort of 286 vulvar squamous carcinoma patients, all treated in the University Medical Center Groningen, the Netherlands. Associations between immunohistochemistry expression and the influence on survival were determined. RESULTS: The number of tumor-infiltrating CD8(+) T-lymphocytes was significantly lower in tumors with loss of HLA-A (p=0.004), HLA-B/C (p=0.024) or ß(2)-m (p=0.025) expression compared with tumors with expression of HLA class I. No association was found between the number of intratumoral CD8(+) T-lymphocytes and Foxp3(+) T-lymphocytes, HLA class I and IDO expression and survival of vulvar squamous carcinoma patients. CONCLUSION: Our results indicate that the immune system does not seem to have a major influence on prognosis of patients with vulvar squamous carcinoma.

Can breast MRI computer-aided detection (CAD) improve radiologist accuracy for lesions detected at MRI screening and recommended for biopsy in a high-risk population?

AIM: To evaluate the sensitivity and specificity of magnetic resonance imaging (MRI) computer-aided detection (CAD) for breast MRI screen-detected lesions recommended for biopsy in a high-risk population. MATERIAL AND METHODS: Fifty-six consecutive Breast Imaging Reporting and Data System (BI-RADS) 3-5 lesions with histopathological correlation [nine invasive cancers, 13 ductal carcinoma in situ (DCIS) and 34 benign] were retrospectively evaluated using a breast MRI CAD prototype (CAD-Gaea). CAD evaluation was performed separately and in consensus by two radiologists specializing in breast imaging, blinded to the histopathology. Thresholds of 50, 80, and 100% and delayed enhancement were independently assessed with CAD. Lesions were rated as malignant or benign according to threshold and delayed enhancement only and in combination. Sensitivities, specificities, and negative predictive values (NPV) were determined for CAD assessments versus pathology. Initial MRI BI-RADS interpretation without CAD versus CAD assessments were compared using paired binary diagnostic tests. RESULTS: Threshold levels for lesion enhancement were: 50% to include all malignant (and all benign) lesions; and 100% for all invasive cancer and high-grade DCIS. Combined use of threshold and enhancement patterns for CAD assessment was best (73% sensitivity, 56% specificity and 76% NPV for all cancer). Sensitivities and NPV were better for invasive cancer (100%/100%) than for all malignancies (54%/76%). Radiologists' MRI interpretation was more sensitive than CAD (p=0.05), but less specific (p=0.001) for cancer detection. CONCLUSION: The breast MRI CAD system used could not improve the radiologists' accuracy for distinguishing all malignant from benign lesions, due to the poor sensitivity for DCIS detection.

Presence of tumor-infiltrating lymphocytes is an independent prognostic factor in type I and II endometrial cancer.

OBJECTIVE: Presence of tumor-infiltrating lymphocytes (TIL) is of prognostic importance in a variety of malignancies. This study aims to determine the prognostic value of CD8(+) cytotoxic T-lymphocytes (CTL), FoxP3(+) regulatory T-lymphocytes (Treg) and CD45R0(+) memory T-lymphocytes in endometrial cancer. METHODS: The number of tumor-infiltrating CD8(+), FoxP3(+), and CD45R0(+) T-lymphocytes was determined by immunohistochemistry on tissue microarrays containing tumor material from 368 FIGO stage I-IV endometrial cancer patients. Results from immunohistochemistry were correlated with clinicopathological parameters and survival. RESULTS: High numbers of intra-tumoral CD8(+) T-lymphocytes, a high CD8(+)/FoxP3(+) ratio and the presence of CD45R0(+) T-lymphocytes were strongly associated with well-known favorable prognostic factors in endometrial cancer. Furthermore, high numbers of CD8(+) T-lymphocytes and a high CD8(+)/FoxP3(+) ratio were associated with a better disease free survival (DFS). High numbers of CD8(+) T-lymphocytes and the presence of CD45R0(+) T-lymphocytes were associated with a prolonged overall survival (OS). In multivariate analysis, high numbers of CD8(+) T-lymphocytes had an independent prognostic impact for overall survival in the entire cohort (HR 0.48, 95% C.I. 0.26-0.89, p=0.019) and in type II endometrial cancer (HR 0.17, 95% C.I. 0.08-0.36, p<0.001). A high CD8(+)/FoxP3(+) ratio was independently associated with improved survival in type I endometrial cancer (HR 0.44, 95% C.I. 0.23-0.84, p=0.013). CD45R0(+) lymphocytes were an independent factor for improved OS (HR 0.42, 95% C.I. 0.19-0.93, p=0.033). CONCLUSION: This study shows that the presence of TIL is an independent prognostic factor in endometrial cancer and indicates an important role for the immune system in endometrial cancer.

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.

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.

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.

Symmetry of projection in the quantitative analysis of mammographic images.

Mammographic parenchymal patterns are among the strongest indicators of the risk of developing breast cancer. Risk evaluation through breast patterns may have an important role in studies of the aetiology of breast cancer and for monitoring changes in the breast in evaluating potential risk-modifying interventions. Typically, patterns are assessed by an experienced radiologist according to Wolfe grade, or on a coarse quantitative scale according to percent density. Parenchymal characterization methods, to overcome variability of classification by human observer, are under investigation. These include image segmentation using semi-automatic thresholding and automatic classification through textural and density measures. An important practical question relates to the extent to which information about mammographic pattern is carried by any one of the four views obtained in a typical examination. Specifically, variations of right-left breast symmetry and variations between the two standard views of each breast were tested. The mammograms of 30 premenopausal women, comprising 90 images [30 each of the right cranial-caudal (RCC), left cranial-caudal (LCC) and right medial-lateral oblique (RMLO)] were evaluated. Parameters included both subjective (radiologist classification and interactive image thresholding) and objective (fractal and skewness indices) quantitative measurements of parenchymal pattern. For the parameters tested, a high degree of correlations was observed for measurements on the RCC, LCC and RMLO views. Pearson correlation coefficients between 0.86-0.96 were found for the comparisons of quantitative parameters. The strong correlations suggest that, in the study and application of mammographic density classification, representative information is provided in a single view.

Automated analysis of mammographic densities.

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.

Mammographic features of pure mucinous carcinoma of the breast with pathological correlation.

OBJECTIVE: To determine the mammographic features of pure mucinous carcinoma of the breast and correlate them with the pathologic features. PATIENTS AND METHODS: The authors analysed 23 tumours identified as pure mucinous carcinoma of the breast in 22 patients, aged 40 to 92 (mean 64.9) years at the time of mammography (which took place between November 1975 and July 1992). The review covered mammographic features, clinical findings, pathological features and nodal status. RESULTS: Twenty (87%) of the lesions were palpable, and 4 (17%) were mammographically occult. At mammography, eight cases (35%) presented as ill-defined masses without calcifications, five (22%) as well-defined masses without calcifications, four (17%) as ill-defined masses with calcifications, one (4%) as a focal asymmetric opacity and one (4%) as pleomorphic calcifications only. Eleven (65%) of the 17 mammographically identified masses were irregular in shape, 4 (24%) were oval, and 2 (12%) were lobular. In 11 (61%) of the 18 cases involving masses or an opacity, the lesions were denser than normal breast parenchyma; in the others the lesions were isodense. All of the hyperdense lesions were greater than 1.9 cm in greatest diameter, as determined mammographically, whereas only one of the isodense lesions was greater than 1.9 cm in greatest diameter. In 17 (77%) of the 22 cases in which the border of the lesions could be evaluated histologically, the lesions had well-defined, pushing borders; the others had ill-defined, irregularly outlined borders. Calcifications were seen histologically in seven cases (30%) and were correlated with mammographically suspicious pleomorphic calcifications in three. Fourteen (82%) of the 17 patients who underwent axillary node dissection were free of nodal disease. CONCLUSIONS: The most common mammographic appearance of pure mucinous carcinoma was an ill-defined mass and the second most common was a well-defined mass. No spiculated lesions were observed in this patient group. Microcalcifications were seen in some cases but were less common than in breast cancers in general. Lesions more than 1.9 cm in greatest diameter tended to be hyperdense. A substantial proportion of pure mucinous carcinomas may be mammographically occult.

Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study.

BACKGROUND: 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. PURPOSE: 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. 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. RESULTS: 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). CONCLUSION: 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.

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.

Treating acute urinary tract infections. An RCT of 3-day versus 7-day norfloxacin.

A randomized, controlled trial was carried out to compare two courses of treatment in women with acute urinary tract infection in general practice. The 3-day course of treatment was found to be as effective as, and cheaper than, the 7-day therapy.

Evaluation of mammographic image quality: pilot study comparing five methods.

A radiograph is considered of high quality when it allows a radiologist to identify abnormalities with high sensitivity and specificity. Although many methods for assessing image quality have been devised, it is not clear which is most meaningful or how well these methods correlate with one another. A pilot study was undertaken to compare five methods of evaluating mammographic image quality. Each of the methods was used to form separate rankings of 11 mammographic system configurations. In two of the methods, observers (three radiologists and three physicists) subjectively ranked the "image quality" of radiographs of phantoms obtained with each configuration. The third method ranked the systems according to contrast as measured densitometrically with an aluminum step wedge, and the fourth, in terms of lowest to highest mean glandular radiation doses to the breast. In the final method, observers based their rankings on mammograms of patients. The intra- and interobserver variabilities of each ranking method were assessed, as well as the correlations between methods, by using standard nonparametric statistical tests. Intraobserver consistency was high with any of the image quality ranking methods; however, image quality rankings based on either of the two phantoms provided better agreement among observers than did rankings based on images of patients. Surprisingly, no significant degree of correlation was found between any two image quality evaluation methods. Our work may have two implications for the American College of Radiology Mammography Accreditation Program: (1) small variations in phantom scores do not necessarily correlate with subjective variation in image quality in radiographs of patients, and (2) when small numbers of radiographs are used, the assessment of the quality of mammograms of patients may vary considerably among radiologists.

Characterisation of mammographic parenchymal pattern by fractal dimension.

A consistent, quantitative, observer-independent method of characterising mammographic parenchymal pattern is described. The method is based on the calculation of the 'fractal dimension' of digitised mammograms. The degree of correlation between the parenchymal pattern classifications by a fractal-based system and those of radiologists is assessed. For a set of 70 mammograms, average weighted proportion agreement among three radiologists in calling Wolfe grades was 85%, while agreement between the radiologists and our fractal classifier was 84%. The method developed may prove to be useful in establishing an index of risk for breast cancer and, ultimately, in determining intervals between examinations for individuals in a mammographic screening programme.