Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Polymorphisms of estrogen receptor-α gene in Brazilian women with high breast density after menopause

The association of genetic polymorphism in the estrogen receptor alpha (ERα) gene and risk for diseases including breast cancer (BC) has been the subject of great interest. Objective: Checking on women with high breast density after menopause, the frequency of the Pvull and Xbal polymorphisms of the ERα gene and the correlation between them and the known risk factors for breast cancer. Method: Observational study with 308 women between 45 and 65 years old with high breast density, without hormonal therapy, menstruation for a year or more, breast and ovarian cancer history. It was characterized in clinical history and physical examination: menarche, menopause, parity, family history of BC, smoking, alcohol intake and body mass index. Results: The allelic and genotypic frequencies for ERα-Pvull and Xbal: p=43.99%; p=56.01%; pp=32.14%; Pp=47.73% and PP=20.13%; X=41.56%; x=58.44%; xx=33.44%; Xx=50.00% and XX=16.56%, respectively. The most frequent risk factors for BC: menarche before 12 years old (35.38%), nulliparity or first child after 28 years old (41.66%), family history of BC (19.16%) and overweight/obesity (62.01%). Conclusion: Allelic and genotypic distribution similar to literature. The risk factors for BC were more prevalent in women with high breast density but without significant associations with these polymorphisms. © 2013 Informa UK Ltd. All rights reserved.

Effects of soy isoflavones on mammographic density and breast parenchyma in postmenopausal women: A randomized, double-blind, placebo-controlled clinical trial

OBJECTIVE: This study aims to evaluate the effects of soy isoflavones on breast tissue in postmenopausal women. METHODS: In this randomized, double-blind, placebo-controlled study, 80 women (aged ≥45 y and with amenorrhea >12 mo) with vasomotor symptoms were randomized to receive either 250 mg of standardized soy extract corresponding to isoflavone 100 mg/day (n = 40) or placebo (n = 40) for 10 months. Breasts were evaluated through mammographic density and breast parenchyma using ultrasound (US) at baseline and 10-month follow-up. Independent t test, analysis of variance, Mann-Whitney U test, and χ2 trend test were used in statistical analysis. RESULTS: Baseline clinical characteristics showed no significant differences between the isoflavone group and the placebo group, with mean (SD) age of 55.1 (6.0) and 56.2 (7.7) years, mean (SD) menopause duration of 6.6 (4.8) and 7.1 (4.2) years, and mean (SD) body mass index of 29.7 (5.0) and 28.5 (4.9) kg/m2, respectively (P > 0.05). The study was completed by 32 women on isoflavone and 34 women on placebo. The groups did not differ in mammographic density or breast parenchyma by US (P > 0.05). Within each group, the baseline and final moments did not differ in mammography or US parameters significantly (P > 0.05). CONCLUSIONS: The use of soy isoflavone extract for 10 months does not affect breast density, as assessed by mammography and US, in postmenopausal women. © 2013 by The North American Menopause Society.

Radiographers practice concerning breast compression in mammography: gradual versus no gradual

Purpose: Evaluate the type of breast compression (gradual or no gradual) that provides less discomfort to the patient. Methods and Materials: The standard projections were simulated [craniocaudal/(CC) and mediolateral-oblique/(MLO)] with the two breast compressions in 90 volunteers women aged between 19 and 86. The women were organised in groups according to the breast density. The intensity of discomfort was evaluated using the scale that have represented several faces (0-10) proposed by Wong Baker in the end of each simulation. It was also applied an interview using focus group to debate the score that were attributed during pain evaluation and to identify the criteria that were considered to do the classification. Results: The women aged between 19-29y (with higher breast density) classified the pain during no gradual compression as 4 and the gradual compression as 2 for both projections. The MLO projection was considered the most uncomfortable. During the focus group interview applied to this group was highlighted that compression did not promoted pain but discomfort. They considered that the high expectations of pain did not correspond to the discomfort that they felt. Similar results were identified for the older women (30-50y; > 50y). Conclusion: The radiographers should considerer the technique for breast compression. The gradual compression was considered for the majority of the women as the most comfortable regardless of breast density. The MLO projection was considered as uncomfortable due to the positioning (axila and inclusion of pectoral muscle) and due to the higher breast compression compared to the CC projection.

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

Mammographic density in asymptomatic menopausal women: correlation with clinical and sonographic findings

OBJECTIVE: To evaluate mammographic breast density in asymptomatic menopausal women in correlation with clinical and sonographic findings. MATERIALS AND METHODS: Mammograms and clinical and sonographic findings of 238 asymptomatic patients were retrospectively reviewed in the period from February/2022 to June/2006. The following variables were analyzed: mammographic density patterns, sonographic findings, patients' age, parity, body mass index and use of hormone replacement therapy. RESULTS: Age, parity and body mass index showed a negative correlation with breast density pattern, while use of hormone replacement therapy showed a positive correlation. Supplementary breast ultrasonography was performed in 103 (43.2%) patients. Alterations which could not be visualized at mammography were found in 34 (33%) of them, most frequently in women with breast density patterns 3 and 4. CONCLUSION: The authors concluded that breast density patterns were influenced by age, parity, body mass index and time of hormone replacement therapy. Despite not having found any malignant abnormality in the studied cases, the authors have observed a predominance of benign sonographic abnormalities in women with high breast density patterns and without mammographic abnormalities, proving the relevance of supplementary ultrasonography to identify breast lesions in such patients.

Polymorphism in CYP17, GSTM1 and the progesterone receptor genes and its relationship with mammographic density

Radiologic breast density is one of the predictive factors for breast cancer and the extent of the density is directly related to postmenopause. However, some patients have dense breasts even during postmenopause. This condition may be explained by the genes that codify for the proteins involved in the biosynthesis, as well as the activity and metabolism of steroid hormones. They are polymorphic, which could explain the variations of individual hormones and, consequently, breast density. The constant need to find markers that may assist in the primary prevention of breast cancer as well as in selecting high risk patients motived this study. We determined the influence of genetic polymorphism of CYP17 (cytochrome P450c17, the gene involved in steroid hormone biosynthesis), GSTM1 (glutathione S-transferase M1, an enzyme involved in estrogen metabolism) and PROGINS (progesterone receptor), for association with high breast density. One hundred and twenty-three postmenopausal patients who were not on hormone therapy and had no clinical or mammographic breast alterations were included in the present study. The results of this study reveal that there was no association between dense breasts and CYP17 or GSTM1. There was a trend, which was not statistically significant (P = 0.084), towards the association between PROGINS polymorphism and dense breasts. However, multivariate logistic regression showed that wild-type PROGINS and mutated CYP17, taken together, resulted in a 4.87 times higher chance of having dense breasts (P = 0.030). In conclusion, in the present study, we were able to identify an association among polymorphisms, involved in estradiol biosyntheses as well as progesterone response, and radiological mammary density.

Failure on clinical image quality criteria in digital mammography: how can radiographers do better?

Purpose: To assess image quality using PGMI (perfect, good, moderate, inadequate) scale in digital mammography examinations acquired in DR systems. Identify the main failures and propose corrective actions. Evaluate the most typical breast density. Methods and Materials: Clinical image quality criteria were evaluated considering mammograms acquired in 13 DR systems and classified according to PGMI scale using the criteria described in European Commission guidelines for radiographers. The breast density was assessed according to ACR recommendations. The data were collected on the acquisition system monitor to reproduce the daily practice of the radiographer. Results: The image quality criteria were evaluated in 3044 images. The criteria were fully achieved in 41% of the images that were classified as P (perfect), 31 % of the images were classified as M (moderate), 20% G (good) and 9% I (inadequate). The main cause of inadequate image quality was absence of all breast tissue in the image, skin folders in the pectoral muscle and in the infra-mammary angle. The higher number of failures occurred in MLO projections (809 out of 1022). The most represented (36%) breast type was type 2 (25-50% glandular tissue). Conclusion: Incorrect radiographic technique was frequently detected suggesting potential training needs and poor communication between the team members (radiographer and radiologists). Further correlations are necessary to identify the main causes for the failures, namely specific education and training in digital mammography and workload.

Factores asociados a recaída en pacientes con cáncer de mama de una institución de Bogotá

Introducción: El cáncer de seno es la primera causa de cáncer entre las mujeres, además es la primera causa de muerte por cáncer entre las hispanas y la segunda entre otras razas, sin contar con el gran impacto social y económico que conlleva esta patología. Esto motiva la realización de estudios propios, que permitan ampliar nuestro conocimiento y aportar a la literatura colombiana, una publicación que refleje los factores asociados a la recaída en el cáncer de mama. Métodos: Estudio observacional analítico retrospectivo de casos y controles en el que se tomaron 267 historias clínicas de pacientes con diagnóstico de cáncer de seno, clasificadas según estadio clínico y expresión molecular del tumor, se analizaron los factores más fuertemente asociados a la recaída. Resultados: La población total consistió en 267 mujeres de las cuales 58 presentaron recaída, con un relación caso – control, 1:3. Al evaluar los grupos se evidencia homogeneidad en cuanto a edad, tipo de neoplasia, paridad e histología con lo que concluimos que estos grupos son comparables. Se presentó una tasa de mortalidad de 13,8 % en las pacientes que presentaron recaída tumoral vs un 0% de mortalidad en aquellas pacientes sin recaída. Adicionalmente se evidencia una relación entre la presencia del receptor HER 2 y recaída tumoral, que aunque no es estadísticamente significativa (p = 0.112) es importante tener en cuenta por su significancia clínica. Por su parte la presencia de receptor de estrógenos y progestágenos no es un predictor de recaída. La realización de cirugía se muestra como un factor de protección (OAR: 0.046 p = 0.008). Finalmente se encontró una asociación estadísticamente significativa como variables de asociación a recaída tumoral: la edad (p=0.009), el estadio clínico en el momento del diagnóstico (p= <0.001) y la clasificación molecular del tumor (p= 0.016). Conclusiones: Se identificaron como factores asociados a recaída tumoral en pacientes con cáncer de mama de una institución de Bogotá, Colombia a: la edad, el estadio clínico en el momento del diagnóstico y la clasificación molecular del tumor, confirmando la agresividad de los tumores triple negativos. Todos los hallazgos son compatibles a lo descrito en la literatura mundial. Esto permite definir la necesidad de generar en nuestro país estrategias de salud pública, que permitan la educación a todos los grupos etarios para el tamizaje en población joven que está siendo afectada, la detección en estadios tempranos del cáncer de mama, asociados a priorización del manejo y mejoras en la ruta de atención de las pacientes que permitan impactar positivamente en el desenlace y calidad de vida de las mujeres con esta patología. Adicionalmente estos resultados impulsan a la continua investigación de nuevas tecnologías y medicamentos que permitan combatir los tumores más agresivos molecularmente hablando.

Automatic mass segmentation in mammographic images

Aquesta tesi està emmarcada dins la detecció precoç de masses, un dels símptomes més clars del càncer de mama, en imatges mamogràfiques. Primerament, s'ha fet un anàlisi extensiu dels diferents mètodes de la literatura, concloent que aquests mètodes són dependents de diferent paràmetres: el tamany i la forma de la massa i la densitat de la mama. Així, l'objectiu de la tesi és analitzar, dissenyar i implementar un mètode de detecció robust i independent d'aquests tres paràmetres. Per a tal fi, s'ha construït un patró deformable de la massa a partir de l'anàlisi de masses reals i, a continuació, aquest model és buscat en les imatges seguint un esquema probabilístic, obtenint una sèrie de regions sospitoses. Fent servir l'anàlisi 2DPCA, s'ha construït un algorisme capaç de discernir aquestes regions són realment una massa o no. La densitat de la mama és un paràmetre que s'introdueix de forma natural dins l'algorisme.

Efeito do raloxifeno sobre a densidade mamográfica em mulheres na pós-menopausa

PURPOSE: to evaluate changes in mammographic breast density in postmenopausal women using raloxifene. METHODS: in this clinical trial, 80 women (mean age=61.1 years) were studied prospectively. Forty patients received 60 mg/day raloxifene, and 40 women comprised the non-treated group (control), paired by age and time of menopause. The treated group was composed of patients with osteoporosis of the lumbar spine. Those with history of breast surgery and users of hormone therapy up to six months prior to the study were excluded. The breast density was assessed qualitatively (subjective) and quantitatively (objective) in two moments, initial and final, after a 6-month follow-up. The 320 mammograms (craniocaudal and oblique) were interpreted qualitatively by the Breast Imaging Reporting and Data System (BI-RADS) classification and quantitatively by digital scanning and computer-assisted segmentation. For statistical analysis t-test, Wilcoxon Mann-Whitney, Spearman correlation and the kappa index were used. RESULTS: on the initial statistical comparison, the groups were considered homogenous for the variables: analyzed age, time of menopause, parity, breast feeding, previous hormonal therapy and body mass index. Baseline breast density, by qualitative and quantitative methods, correlated negatively with the age in both groups (p<0.05). Concerning the other variables, there was no correlation. After six months, no alteration was observed in the mammographic breast density in 38 women of raloxifene group and 38 of the control group, by qualitative method. However, by quantitative method, no alteration was observed in 30 women of the raloxifene group and 27 controls (p>0.05). It was observed a weak agreement rate (kappa=0.25) between the BI-RADS classification and digital scanning/computer-assisted segmentation. CONCLUSIONS: in post-menopausal women with osteoporosis, submitted to raloxifene treatment for six months, no alterations were observed on the mammographic breast density.

Avaliação do tecido mamário em mulheres na pós-menopausa usuárias de isoflavona da soja

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Alterações mamográficas em mulheres que vivem com HIV-aids

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)