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Relevant bibliographies by topics / Breast parenchymal patterns

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Journal articles
Dissertations / Theses
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Academic literature on the topic 'Breast parenchymal patterns'

Author: Grafiati

Published: 19 February 2023

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Journal articles on the topic "Breast parenchymal patterns"

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Bayar, S., S. Tükel, S. Koçak, S. Aydintugˇ, and S. Dizbay Sak. "Mammographic parenchymal, patterns and breast histology." European Journal of Cancer 34 (September 1998): S79. http://dx.doi.org/10.1016/s0959-8049(98)80329-8.

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SAFTLAS, AUDREY F., and MOYSES SZKLO. "MAMMOGRAPHIC PARENCHYMAL PATTERNS AND BREAST CANCER RISK1." Epidemiologic Reviews 9, no. 1 (1987): 146–74. http://dx.doi.org/10.1093/oxfordjournals.epirev.a036300.

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Koo, Bong Sig, Jong Wha Lee, Young Jun Lee, Jun Bae Lee, Byung Soo Kim, and Yang Sook Kim. "Xeromammographic breast parenchymal patterns and their relationship to breast cancer." Journal of the Korean Radiological Society 27, no. 2 (1991): 297. http://dx.doi.org/10.3348/jkrs.1991.27.2.297.

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Sickles, Edward A. "Wolfe Mammographic Parenchymal Patterns and Breast Cancer Risk." American Journal of Roentgenology 188, no. 2 (February 2007): 301–3. http://dx.doi.org/10.2214/ajr.06.0635.

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Pertuz, Said, Antti Sassi, Mirva Karivaara-Mäkelä, Kirsi Holli-Helenius, Anna-Leena Lääperi, Irina Rinta-Kiikka, Otso Arponen, and Joni-Kristian Kämäräinen. "Micro-parenchymal patterns for breast cancer risk assessment." Biomedical Physics & Engineering Express 5, no. 6 (September 23, 2019): 065008. http://dx.doi.org/10.1088/2057-1976/ab42f4.

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Whitehouse, G. H., and S. J. Leinster. "The Variation of Breast Parenchymal Patterns with Age." British Journal of Radiology 58, no. 688 (April 1985): 315–18. http://dx.doi.org/10.1259/0007-1285-58-688-315.

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van Gils, C. H., J. D. M. Otten, A. L. M. Verbeek, and J. Hendriks. "Breast parenchymal patterns and their changes with age." British Journal of Radiology 68, no. 814 (October 1995): 1133–35. http://dx.doi.org/10.1259/0007-1285-68-814-1133.

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Hall, FM. "Mammographic parenchymal patterns and estrogen receptors in breast cancer." American Journal of Roentgenology 145, no. 6 (December 1985): 1316–17. http://dx.doi.org/10.2214/ajr.145.6.1316.

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Oza, Amit M., and Norman F. Boyd. "Mammographic Parenchymal Patterns: A Marker of Breast Cancer Risk." Epidemiologic Reviews 15, no. 1 (1993): 196–208. http://dx.doi.org/10.1093/oxfordjournals.epirev.a036105.

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SAFTLAS, AUDREY F., JOHN N. WOLFE, ROBERT N. HOOVER, LOUISE A. BRINTON, CATHERINE SCHAIRER, MARTINE SALANE, and MOYSES SZKLO. "MAMMOGRAPHIC PARENCHYMAL PATTERNS AS INDICATORS OF BREAST CANCER RISK." American Journal of Epidemiology 129, no. 3 (March 1989): 518–26. http://dx.doi.org/10.1093/oxfordjournals.aje.a115163.

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Dissertations / Theses on the topic "Breast parenchymal patterns"

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Riza, Eleni. "Determinants of mammographic parenchymal patterns and implications for breast cancer aetiology : a study in northern Greece (Ormylia Mammography Screening Programme)." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324626.

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(9824918), Ruth Pape. "Mammographic parenchymal patterns of New South Wales north coast Aboriginal and Torres Strait Islander women." Thesis, 2014. https://figshare.com/articles/thesis/Mammographic_parenchymal_patterns_of_New_South_Wales_north_coast_Aboriginal_and_Torres_Strait_Islander_women/13436219.

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The aim of this thesis was to document the distribution of mammographic parenchymal patterns (MPPs) for Australian Aboriginal and Torres Strait Islander women attending BreastScreen New South Wales North Coast (BSNSWNC); to profile breast cancer risk as it relates to breast density; and to explore the correlations among MPPs, age and breast length as described by the posterior nipple line (PNL). The PNL criterion is defined as a reference line drawn from the nipple at right angles to the anterior aspect of the pectoral muscle contour or to the back of the image whichever comes first (Spuur et al. 2011).

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Book chapters on the topic "Breast parenchymal patterns"

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He, Wenda, and Reyer Zwiggelaar. "Breast Parenchymal Pattern Analysis in Digital Mammography: Associations between Tabár and Birads Tissue Compositions." In Computer Analysis of Images and Patterns, 386–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40246-3_48.

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Wei, Jun, Heang-Ping Chan, Yao Lu, Lubomir Hadjiiski, Chuan Zhou, and Mark A. Helvie. "Breast Parenchymal Pattern (BPP) Analysis: Comparison of Digital Mammograms and Breast Tomosynthesis." In Breast Imaging, 514–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31271-7_66.

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"Overview of the Five Mammographic Parenchymal Patterns." In Breast Cancer - The Art and Science of Early Detection with Mammography, edited by László Tabár, Tibor Tot, and Peter B. Dean. Stuttgart: Georg Thieme Verlag, 2005. http://dx.doi.org/10.1055/b-0034-65104.

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"Distribution of Mammographic Parenchymal Patterns by Age in a Screening Population versus Clinically Referred Women." In Breast Cancer - The Art and Science of Early Detection with Mammography, edited by László Tabár, Tibor Tot, and Peter B. Dean. Stuttgart: Georg Thieme Verlag, 2005. http://dx.doi.org/10.1055/b-0034-65146.

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Anter, Ahmed M., Mohamed Abu ElSoud, and Aboul Ella Hassanien. "Automatic Mammographic Parenchyma Classification According to BIRADS Dictionary." In Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies, 22–37. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6030-4.ch002.

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Internal density of the breast is a parameter that clearly affects the performance of segmentation and classification algorithms to define abnormality regions. Recent studies have shown that their sensitivity is significantly decreased as the density of the breast is increased. In this chapter, enhancement and segmentation process is applied to increase the computation and focus on mammographic parenchyma. This parenchyma is analyzed to discriminate tissue density according to BIRADS using Local Binary Pattern (LBP), Gray Level Co-Occurrence Matrix (GLCM), Fractal Dimension (FD), and feature fusion technique is applied to maximize and enhance the performance of the classifier rate. The different methods for computing tissue density parameter are reviewed, and the authors also present and exhaustively evaluate algorithms using computer vision techniques. The experimental results based on confusion matrix and kappa coefficient show a higher accuracy is obtained by automatic agreement classification.

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Gooren, Louis J. G. "Gynaecomastia." In Oxford Textbook of Endocrinology and Diabetes, 1459–62. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199235292.003.9131.

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Parenchymal and stromal cells with the potential for normal breast development are equally present in prepubertal boys and girls. Men and women do not differ in sensitivity to the hormonal action of sex steroids, and therefore men have the same potential to develop breasts as women. Whether this actually occurs obviously depends on a person’s hormonal milieu. In order to understand the pathophysiology of gynaecomastia it is essential to know that breast tissue is, for its development, under control of both stimulatory hormonal action (oestrogens and progestogens) and inhibitory hormonal action of androgens. Gynaecomastia typically occurs when there is a relative dominance of oestrogenic over androgenic action; many cases of gynaecomastia are not the result of an overproduction of oestrogens per se, but rather due to the failing inhibitory action of androgens (1). In the assessment of gynaecomastia, as much attention must be paid to a potential source of feminizing hormones as to decreased androgen production or interference with the biological action of androgens. Oestrogens stimulate the proliferation and differentiation of parenchymal ductal elements while progesterone supports alveolar development. The biological actions of oestrogens and progesterone do not appear in cases of growth hormone deficiency. Prolactin stimulates the differentiated ducts to produce milk. Testosterone inhibits the growth and differentiation of breast development, probably through an antioestrogenic action (1). Whatever the cause, gynaecomastia shows the same histological developmental pattern. At first, there is florid ductal proliferation, with epithelial hyperplasia and increase in stromal and periductal connective tissue, with increased vascularity and periductal oedema. After approximately one year, there is increased stromal hyalinization, dilation of the ducts, and a marked reduction in epithelial proliferation, a ‘burnt-out’ phase of the condition. The result is inactive fibrotic tissue which no longer responds to endocrine therapy. Gynaecomastia is not an uncommon finding and most cases will not represent a serious medical condition. However, gynaecomastia may signify the presence of a malignancy producing oestrogens, aromatase (the enzyme that converts androgens to oestrogens), or human chorionic gonadotrophin (hCG). Common locations of such tumours are the testis, lungs, liver or the gastrointestinal tract. Consequently, cases of gynaecomastia must be taken seriously and the diagnostic approach must reasonably rule out a malignancy in order to avoid any undue delay in its diagnosis.

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"The Prevalence of Breast Cancer According to Mammographic Parenchymal Pattern and Age." In Breast Cancer - The Art and Science of Early Detection with Mammography, edited by László Tabár, Tibor Tot, and Peter B. Dean. Stuttgart: Georg Thieme Verlag, 2005. http://dx.doi.org/10.1055/b-0034-65148.

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Conference papers on the topic "Breast parenchymal patterns"

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Wu, Yi-Ta, Berkman Sahiner, Heang-Ping Chan, Jun Wei, Lubomir M. Hadjiiski, Mark A. Helvie, Yiheng Zhang, et al. "Comparison of mammographic parenchymal patterns of normal subjects and breast cancer patients." In Medical Imaging, edited by Maryellen L. Giger and Nico Karssemeijer. SPIE, 2008. http://dx.doi.org/10.1117/12.771278.

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Lilge, Lothar, Michelle Simick, and Brian Wilson. "Optical transillumination spectroscopy of breast tissue for correlation of parenchymal density patterns." In Biomedical Optical Spectroscopy and Diagnostics. Washington, D.C.: OSA, 2000. http://dx.doi.org/10.1364/bosd.2000.sud3.

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Oustimov, Andrew, Aimilia Gastounioti, Meng-Kang Hsieh, Lauren Pantalone, Emily F. Conant, and Despina Kontos. "Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk." In SPIE Medical Imaging, edited by Samuel G. Armato and Nicholas A. Petrick. SPIE, 2017. http://dx.doi.org/10.1117/12.2254506.

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Wei, Jun, Heang-Ping Chan, Chuan Zhou, Yi-ta Wu, Berkman Sahiner, Lubomir M. Hadjiiski, and Mark A. Helvie. "Comparison of breast parenchymal pattern on prior mammograms of breast cancer patients and normal subjects." In SPIE Medical Imaging, edited by Nico Karssemeijer and Maryellen L. Giger. SPIE, 2009. http://dx.doi.org/10.1117/12.813565.

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Wei, Jun, Heang-Ping Chan, Chuan Zhou, Mark A. Helvie, Lubomir M. Hadjiiski, and Berkman Sahiner. "Association of a mammographic parenchymal pattern (MPP) descriptor with breast cancer risk: a case-control study." In SPIE Medical Imaging, edited by Nico Karssemeijer and Ronald M. Summers. SPIE, 2010. http://dx.doi.org/10.1117/12.844040.

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Boehm, Holger F., Tanja Fischer, Dororthea Riosk, Stefanie Britsch, and Maximilian Reiser. "Application of the Minkowski-functionals for automated pattern classification of breast parenchyma depicted by digital mammography." In Medical Imaging, edited by Maryellen L. Giger and Nico Karssemeijer. SPIE, 2008. http://dx.doi.org/10.1117/12.754867.

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Nunes, Mirella Laranjeira, Maria Carolina da Trindade Henriques Assunção, Pryscila Correia de Queiroz e. Silva, Rossano Robério Fernandes Araújo, Bruno Pacheco Pereira, Ana Leide Guerra dos Santos, Vidianna Barbosa Sampaio, and João Esberard de Vasconcelos Beltrão Neto. "METASTATIC PURE MUCINOUS BREAST CARCINOMA: A CASE REPORT." In Abstracts from the Brazilian Breast Cancer Symposium - BBCS 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s2051.

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Introduction: Pure mucinous breast carcinoma (PMBC) is rare, representing about 2% of breast cancers. Histologically, it is defined as having 90% or more of a mucinous component. It usually affects women between the ages of 55 and 60 years. Only 1% occurs in women below 35 years. It usually has positive hormone receptors (HRs); however, the positivity of HER-2 is rare. The management is not well established, being extrapolated from data on invasive ductal carcinoma. It usually presents a favorable prognosis, with rare lymph node (LN) involvement and metastasis rate of less than 15%. HR status and nodal involvement are important prognostic factors. Case Report: A 34-year-old female arrived at the clinic with a tumor occupying all quadrants of the left breast for 5 months, along with skin thickening and hyperemia, hardened and enlarged left axillary LN. Ultrasonography showed a lesion with indistinct limits occupying almost the entire mammary parenchyma measuring 11.1×12.8×5.5 cm, and the left LN enlarged in size, the largest measuring 3.1×1.7 cm. Bone scintigraphy and computed tomography (CT) showed suspicious metastatic lesion in the sternum, which could not be proven as metastasis due to the absence of structure to perform a biopsy. A clinical-prognostic staging IV, T4bN1Mx, was determined. Incisional biopsy diagnosed PMBC, histological grade 2. Immunohistochemistry results were HR positive, HER-2 positive (3+), and Ki67 70%. The patient was treated chemotherapy drugs such as Adriamycin, cyclophosphamide, paclitaxel, and trastuzumab. Subsequently, a modified radical mastectomy was performed. The anatomopathology of the surgical specimen showed a complete pathological response. A new CT showed partial remission of sternal metastasis. Adjunctive treatment with trastuzumab, tamoxifen, radiotherapy, and surgical castration were performed. We brought an atypical case due to the presentation of PMBC in young woman, with a more aggressive pattern, with positive HER-2, metastasis, and complete pathological response with chemotherapy.

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