Adenoid cystic carcinomas (ACCs) are rare malignant neoplasms of exocrine glands, most commonly found in salivary glands. This report describes a 67-year-old woman with metastatic ACC to the breast, only the third reported case of its kind. The salivary gland ACC was first diagnosed 5 years prior. Routine mammogram identified a Breast Imaging and Reporting Systems (BIRADS) 4 lesion. Core breast biopsy demonstrated findings consistent with metastatic ACC to the breast. The patient ultimately underwent local excision but suffered a recurrence of disease less than 2 months later despite chemotherapy. She passed away 15 months after excision due to complications associated with a small bowel obstruction and decompensated respiratory status from pulmonary metastases. While metastatic salivary ACC to the breast is rare, it is important to be able to distinguish metastatic salivary ACC to the breast from primary ACC of the breast as the treatment considerations for the two disease processes differ significantly.
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http://dx.doi.org/10.1136/bcr-2017-223345 | DOI Listing |
J Imaging
December 2024
Department of Computing, Electronics and Mechatronics, Universidad de las Américas Puebla, Sta. Catarina Martir, San Andrés Cholula 72810, Mexico.
Breast cancer is one of the leading causes of death for women worldwide, and early detection can help reduce the death rate. Infrared thermography has gained popularity as a non-invasive and rapid method for detecting this pathology and can be further enhanced by applying neural networks to extract spatial and even temporal data derived from breast thermographic images if they are acquired sequentially. In this study, we evaluated hybrid convolutional-recurrent neural network (CNN-RNN) models based on five state-of-the-art pre-trained CNN architectures coupled with three RNNs to discern tumor abnormalities in dynamic breast thermographic images.
View Article and Find Full Text PDFMed Phys
December 2024
Faculty of Applied Sciences, Macao Polytechnic University, Macao, China.
Background: Amide proton transfer weighted (APTw) imaging has demonstrated extensive clinical applications in diagnosing, treating evaluating, and prognosis prediction of breast cancer. There is a pressing need to automatically segment breast lesions on APTw original images to facilitate downstream quantification, which is however challenging.
Purpose: To build a segmentation model on the original images of APTw imaging sequence by leveraging the varying contrasts between breast lesions and their surrounding glandular and fat tissues displayed on the original images of APTw imaging at different frequency offsets.
Am J Transl Res
November 2024
Department of General Practice, Pingjiang New Town Community Health Service Center Sujin Street, Gusu District, Suzhou 215000, Jiangsu, China.
Background: Cancer represents a highly intricate disease, characterized by the uncontrolled proliferation and invasion of aberrant cells, leading to widespread global morbidity and mortality. This study investigates the influence of CD19, a marker specific to B-cells, within the tumor microenvironment (TME) across a spectrum of cancer types.
Methodology: To explore the role of CD19, we employed a wide array of bioinformatics tools and databases, including UALCAN, GEPIA2, univariate Cox regression, KM plotter, HPA, GSCA, cBioPortal, TISIDB, and DAVID.
Ann Epidemiol
December 2024
School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China; School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, VIC, Australia; Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Carlton, VIC, Australia; Bijie Institute of Shanghai University of Traditional Chinese Medicine, Bijie, China; Doctoral Workstation, Bijie District Center for Disease Control and Prevention, Bijie, China. Electronic address:
Background: From a global perspective, China is one of the countries with higher incidence and mortality rates for cancer.
Objective: Our objective is to create an online cancer risk prediction tool for middle-aged and elderly Chinese adults by leveraging machine learning algorithms and self-reported data.
Method: Drawing from a cohort of 19,798 participants aged 45 and above from the China Health and Retirement Longitudinal Study (2011 - 2018), we employed nine machine learning algorithms (LR: Logistic Regression, Adaboost: Adaptive Boosting, SVM: Support Vector Machine, RF: Random Forest, GNB: Gaussian Naive Bayes, GBM: Gradient Boosting Machine, LGBM: Light Gradient Boosting Machine, XGBoost: eXtreme Gradient Boosting, KNN: K - Nearest Neighbors), which are mainly used for classification and regression tasks, to construct predictive models for various cancers.
Endocr Relat Cancer
November 2024
T van Ginhoven, Department of Surgical Oncology and Gastrointestinal Surgery, Erasmus MC Cancer Institute, Erasmus Medical Center, Rotterdam, Netherlands.
Up to 30% of adrenocortical carcinoma (ACC) patients have metastasised disease upon initial presentation and systemic treatments currently fail to sufficiently improve survival. Palliative primary tumour resection can be considered for symptomatic relief, but its potential survival benefit remains a topic of debate. This systematic review therefore aims to assess the effect of primary tumour resection on overall survival in patients with metastatic ACC.
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