scholarly journals Neuroendocrine carcinoma of the breast: a case report

2021 ◽  
pp. 306-311
Author(s):  
Iulia Gîvan ◽  
George Ciulei ◽  
Angela Cozma ◽  
Mădălina Indre ◽  
Vlad Țâru ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Manifestations ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
Breast Carcinomas ◽  
Hormone Production ◽  
Carcinoma Of The Breast ◽  
Clinical Syndromes ◽  
Health Organization

Neuroendocrine breast carcinomas represent a rare subtype of breast cancer. Their definition, prevalence and prognosis remain controversial in the literature. Regarding the presentation, there are no differences from other breast carcinomas and clinical syndromes related to hormone production are extremely rare. Refinement of the classification of neuroendocrine neoplasms of the breast is needed in order to improve the reproducibility of their diagnostic criteria and to define their clinical significance. This article presents the case of a 44-year-old female patient diagnosed with invasive breast carcinoma with neuroendocrine features, according to the 2012 World Health Organization (WHO) definition, with focus on presentation, clinical manifestations, diagnostic approach and differential diagnosis.

Classification and Prognostic Stratification of Bronchopulmonary Neuroendocrine Neoplasms

2019 ◽  
Vol 110 (5) ◽  
pp. 393-403 ◽  
Author(s):  
Naomi Oka ◽  
Atsuko Kasajima ◽  
Björn Konukiewitz ◽  
Akira Sakurada ◽  
Yoshinori Okada ◽  
...  
Keyword(s):  
Disease Free Survival ◽  
Mitotic Count ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
Prognostic Impact ◽  
Ki67 Index ◽  
Prognostic Stratification ◽  
Net G3 ◽  
Health Organization

The accuracy and reproducibility of the World Health Organization (WHO) 2015 classification of bronchopulmonary neuroendocrine neoplasms (BP-NENs) is disputed. The aim of this study is to classify and grade BP-NENs using the WHO 2019 classification of digestive system NENs (DiS-NEN-WHO 2019), and to analyze its accuracy and prognostic impact. Two BP-NEN cohorts from Japan and Germany, 393 tumors (88% surgically resected), were reviewed and the clinicopathological data of the resected tumors (n = 301) correlated to patients’ disease-free survival (DFS). The DiS-NEN-WHO 2019 stratified the 350 tumors into 91 (26%) neuroendocrine tumors (NET) G1, 52 (15%) NET G2, 15 (4%) NET G3, and 192 (55%) neuroendocrine carcinomas (NEC). NECs, but not NETs, were immunohistochemically characterized by abnormal p53 (100%) and retinoblastoma 1 (83%) expression. The Ki67 index, which was on average 4 times higher than mitotic count (p < 0.0001), was prognostically more accurate than the mitotic count. NET G3 patients had a worse outcome than NET G1 (p < 0.01) and NET G2 patients (p = 0.02), respectively. No prognostic difference was detected between NET G3 and NEC patients after 5 year DFS. It is concluded that stratifying BP-NEN patients according to the DiS-NEN-WHO 2019 classification results in 3 prognostically well-defined NET groups, if grading is solely based on Ki67 index. Mitotic count alone may underestimate malignant potential of NETs.

scholarly journals Co-existence of gastric adenocarcinoma and neuroendocrine carcinoma: a rare entity

2017 ◽  
Vol 7 (2) ◽  
pp. 1221-1223 ◽  
Author(s):  
Nirajan Mainali ◽  
Niraj Nepal ◽  
Prabesh Kumar Choudhary ◽  
Amrita Sinha ◽  
Saroj Rajbanshi ◽  
...  
Keyword(s):  
Neuroendocrine Carcinoma ◽  
Partial Gastrectomy ◽  
Endoscopic Biopsy ◽  
World Health ◽  
Neuroendocrine Neoplasms ◽  
World Health Organization Classification ◽  
Well Differentiated ◽  
Health Organization ◽  
Histopathology Examination

A mixed adenoneuroendocrine carcinoma is a tumor composed of both adenocarcinoma and neuroendocrine carcinoma components, with each comprising  at least one-third of the lesion, as defined by the World Health Organization classification of neuroendocrine neoplasms in 2010.. A 67-years-old male was admitted to the hospital with symptoms suggesting gastric cancer. Histopathology examination from endoscopic biopsy revealed adenocarcinoma. Later partial gastrectomy specimen examination the lesion show presence of well differentiated adenocarcinoma along with neuro endocrine carcinoma.

scholarly journals Analisis Klasifikasi Kanker Payudara Menggunakan Algoritma Naive Bayes

2020 ◽  
Vol 4 (3) ◽  
pp. 117
Author(s):  
Hardian Oktavianto ◽  
Rahman Puji Handri
Keyword(s):  
Breast Cancer ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
World Health ◽  
Average Percentage ◽  
Average Value ◽  
Treatment Measures ◽  
Bayes Algorithm ◽  
Health Organization

Breast cancer is one of the highest causes of death among women, this disease ranks second cause of death after lung cancer. According to the world health organization, 1 million women get a diagnosis of breast cancer every year and half of them die, in general this is due to early treatment and slow treatment resulting in new cancers being detected after entering the final stage. In the field of health and medicine, machine learning-based classification has been carried out to help doctors and health professionals in classifying the types of cancer, to determine which treatment measures should be performed. In this study breast cancer classification will be carried out using the Naive Bayes algorithm to group the types of cancer. The dataset used is from the Wisconsin breast cancer database. The results of this study are the ability of the Naive Bayes algorithm for the classification of breast cancer produces a good value, where the average percentage of correctly classified data reaches 96.9% and the average percentage of data is classified as incorrect only 3.1%. While the level of effectiveness of classification with naive bayes is high, where the average value of precision and recall is around 0.96. The highest precision and recall values are when the test data uses a percentage split of 40% with the respective values reaching 0.974 and 0.973.

scholarly journals What is New in 2019 World Health Organization (WHO) Classification of Tumors of the Digestive System: Review of Selected Updates on Neuroendocrine Neoplasms, Appendiceal Tumors, and Molecular Testing

2020 ◽  
Author(s):  
Naziheh Assarzadegan ◽  
Elizabeth Montgomery
Keyword(s):  
World Health Organization ◽  
Digestive System ◽  
English Literature ◽  
World Health ◽  
Response To Treatment ◽  
Neuroendocrine Neoplasms ◽  
Molecular Testing ◽  
Classification Of Tumors ◽  
Health Organization

Context.— The 5th edition of the World Health Organization classification of digestive system tumors discusses several advancements and developments in understanding the etiology, pathogenesis, and diagnosis of several digestive tract tumors. Objective.— To provide a summary of the updates with a focus on neuroendocrine neoplasms, appendiceal tumors, and the molecular advances in tumors of the digestive system. Data Sources.— English literature and personal experiences. Conclusions.— Some of the particularly important updates in the 5th edition are the alterations made in the classification of neuroendocrine neoplasms, understanding of pathogenesis of appendiceal tumors and their precursor lesions, and the expanded role of molecular pathology in establishing an accurate diagnosis or predicting prognosis and response to treatment.

scholarly journals Pleomorphic Invasive Lobular Carcinoma of the Breast With Extracellular Mucin and HER2 Amplification

2020 ◽  
Vol 14 ◽  
pp. 117822342097638
Author(s):  
Matthew J Burky ◽  
Emily M Ray ◽  
David W Ollila ◽  
Siobhan M. O’Connor ◽  
Johann D. Hertel ◽  
...  
Keyword(s):  
Invasive Lobular Carcinoma ◽  
Lobular Carcinoma ◽  
Mucinous Carcinoma ◽  
World Health ◽  
Her2 Positive ◽  
Carcinoma Of The Breast ◽  
World Health Organization Classification ◽  
Palpable Mass ◽  
Health Organization

Invasive lobular carcinoma with extracellular mucin is an uncommon pattern of invasive breast carcinoma. The 5th Edition of the World Health Organization Classification of Breast Tumors states that it is unknown whether these tumors are a subtype of mucinous carcinoma or invasive lobular carcinoma. Invasive lobular carcinoma with extracellular mucin frequently presents as a palpable mass and may be more likely to be grade 2 to 3 and HER2-positive than classic invasive lobular carcinoma. This case of pleomorphic invasive lobular carcinoma with extracellular mucin was detected by imaging only and was HER2-amplified, suggesting that a subset of these tumors may be clinically occult with an aggressive phenotype. Invasive lobular carcinoma with extracellular mucin is infrequently encountered and awareness of this entity is helpful in avoiding misdiagnosis.

Classification of Breast Cancer Using a Hybrid and Enhanced Recurrent Residual Convolutional Neural Network (ERResCNN)

2021 ◽  
Vol 19 (2) ◽  
pp. 66-76
Author(s):  
S. Prakash ◽  
K. Sangeetha
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Normal Breast ◽  
World Health ◽  
Complex Task ◽  
Segmentation Methods ◽  
Health Organization ◽  
Prevention And Cure ◽  
Breast Tissues

Females are affected by BC (Breast Cancer) more than any other type of cancer. BC has caused more deaths than any other diseases such as tuberculosis or malaria according to WHO (World Health Organization). The mortality rates due to BC in women are high making it a candidate for early detection for prevention and cure. Diagnosing BC is a complex task as it is interleaved with normal breast tissues. Image processing methods have been proposed for detecting BC, yet better segmentation methods are required. Fuzzy based approaches provide optimal results in segmenting BC images. Hence, this work uses Fuzzy approach combined with ResCNN (Recurrent Residual Convolution Neural Network) which is the optimized by a modified GA (Genetic Algorithm). The proposed ERResCNN classifying results in detecting BC from images is accurate and efficient in comparison to other methods.

scholarly journals Classification of Breast Cancer Malignancy Using Cytological Images of Fine Needle Aspiration Biopsies

2008 ◽  
Vol 18 (1) ◽  
pp. 75-83 ◽  
Author(s):  
Łukasz Jeleń ◽  
Thomas Fevens ◽  
Adam Krzyżak
Keyword(s):  
Breast Cancer ◽  
Fine Needle Aspiration ◽  
Needle Aspiration ◽  
World Health ◽  
Support Vector ◽  
Fine Needle ◽  
Malignancy Grade ◽  
Precise Diagnosis ◽  
Health Organization

Classification of Breast Cancer Malignancy Using Cytological Images of Fine Needle Aspiration BiopsiesAccording to the World Health Organization (WHO), breast cancer (BC) is one of the most deadly cancers diagnosed among middle-aged women. Precise diagnosis and prognosis are crucial to reduce the high death rate. In this paper we present a framework for automatic malignancy grading of fine needle aspiration biopsy tissue. The malignancy grade is one of the most important factors taken into consideration during the prediction of cancer behavior after the treatment. Our framework is based on a classification using Support Vector Machines (SVM). The SVMs presented here are able to assign a malignancy grade based on preextracted features with the accuracy up to 94.24%. We also show that SVMs performed best out of four tested classifiers.

Sixth Edition: the New Standard

2008 ◽  
Vol 13 (1) ◽  
pp. 1-12
Author(s):  
Christopher R. Brigham ◽  
Robert D. Rondinelli ◽  
Elizabeth Genovese ◽  
Craig Uejo ◽  
Marjorie Eskay-Auerbach
Keyword(s):  
Review Process ◽  
Peer Review Process ◽  
World Health ◽  
International Classification Of Functioning ◽  
Revision Process ◽  
Sixth Edition ◽  
Impairment Ratings ◽  
Health Organization ◽  
Impairment Severity

Abstract The AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), Sixth Edition, was published in December 2007 and is the result of efforts to enhance the relevance of impairment ratings, improve internal consistency, promote precision, and simplify the rating process. The revision process was designed to address shortcomings and issues in previous editions and featured an open, well-defined, and tiered peer review process. The principles underlying the AMA Guides have not changed, but the sixth edition uses a modified conceptual framework based on the International Classification of Functioning, Disability, and Health (ICF), a comprehensive model of disablement developed by the World Health Organization. The ICF classifies domains that describe body functions and structures, activities, and participation; because an individual's functioning and disability occur in a context, the ICF includes a list of environmental factors to consider. The ICF classification uses five impairment classes that, in the sixth edition, were developed into diagnosis-based grids for each organ system. The grids use commonly accepted consensus-based criteria to classify most diagnoses into five classes of impairment severity (normal to very severe). A figure presents the structure of a typical diagnosis-based grid, which includes ranges of impairment ratings and greater clarity about choosing a discreet numerical value that reflects the impairment.

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