Objective: To evaluate the main technical limitations of automated breast ultrasound and to determine the proportion of examinations excluded.
Materials And Methods: We evaluated 440 automated breast ultrasound examinations performed, over a 12-month period, by technicians using an established protocol.
Results: In five cases (1.1%), the examination was deemed unacceptable for diagnostic purposes, those examinations therefore being excluded.
Conclusion: Automated breast ultrasound is expected to overcome some of the major limitations of conventional ultrasound in breast cancer screening. In Brazil, this new method can be accepted for inclusion in routine clinical practice only after its advantages have been validated in the national context.
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http://dx.doi.org/10.1590/0100-3984.2019.0079 | DOI Listing |
STAR Protoc
January 2025
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China; Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China. Electronic address:
Standard flow cytometry-based assays can determine the cytotoxicity of immune effector cells, but it is challenging to monitor the dynamic processes of cytotoxicity. Here, we present a protocol for continuous observation of natural killer (NK) cell-mediated cytotoxicity with microwell arrays using an automated microscope. We describe steps for isolating and labeling primary NK cells, loading cells onto microwell arrays, monitoring target wells, and image analysis.
View Article and Find Full Text PDFComput Biol Med
January 2025
Fraunhofer Institute for Digital Medicine MEVIS, Bremen/Lübeck/Aachen, Germany.
Due to the increasing workload of pathologists, the need for automation to support diagnostic tasks and quantitative biomarker evaluation is becoming more and more apparent. Foundation models have the potential to improve generalizability within and across centers and serve as starting points for data efficient development of specialized yet robust AI models. However, the training of foundation models themselves is usually very expensive in terms of data, computation, and time.
View Article and Find Full Text PDFDigit Health
January 2025
Department of Computer Science and Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur, Bangladesh.
Objective: Breast cancer detection is critical for timely and effective treatment, and automatic detection systems can significantly reduce human error and improve diagnosis speed. This study aims to develop an accurate and robust framework for classifying breast cancer into benign and malignant categories using a novel machine learning architecture.
Methods: We propose a dense-ResNet attention integration (DRAI) architecture that combines DenseNet and ResNet models with three attention mechanisms to enhance feature extraction from the BreakHis dataset.
Biomolecules
November 2024
Department of Organic Chemistry, Kaunas University of Technology, Radvilėnų pl. 19, 50254 Kaunas, Lithuania.
A series of target 4-substituted-5-(2-(pyridine-2-ylamino)ethyl)-2,4-dihydro-3-1,2,4-triazole-3-thiones and their chloro analogs - were synthesized in a reaction of the selected aldehydes with the corresponding 4-amino-1,2,4-triazole-3-thiones and , which were obtained from 3-(pyridin-2-ylamino)propanoic acid () or 3-((5-chloropyridin-2-yl)amino)propanoic acid (), respectively, with thioacetohydrazide. The antibacterial and antifungal activities of the synthesized hydrazones were screened against the bacteria , , and and the fungi and by agar diffusion and serial dilution methods. 4-Amino-5-(2-((5-chloropyridin-2-yl)amino)ethyl)-2,4-dihydro-3-1,2,4-triazole-3-thione () and 4-(benzylideneamino)-5-(2-(pyridin-2-ylamino)ethyl)-2,4-dihydro-3-1,2,4-triazole-3-thione () were identified as exceptionally active (MIC 0.
View Article and Find Full Text PDFBackground And Hypothesis: Triple-negative breast cancer (TNBC) patients are at increased risk for recurrence compared to other subtypes of breast cancer. Previous evidence showed that adiposity may contribute to worsened cancer control. Current measures of obesity, such as body-mass index (BMI), are poor surrogates of adiposity, while visceral-to-subcutaneous adiposity ratio (VSR), which can be measured from routine computed tomography (CT) imaging, is a direct adiposity measure.
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