Breast cancer detection among young survivors of pediatric Hodgkin lymphoma with screening magnetic resonance imaging

BACKGROUND Female survivors of pediatric Hodgkin lymphoma (HL) who have received chest radiotherapy are at increased risk of breast cancer. Guidelines for early breast cancer screening among these survivors are based on little data regarding clinical outcomes. This study reports outcomes of breast cancer screening with MRI and mammography (MMG) after childhood HL. METHODS We evaluated the results of breast MRI and MMG screening among 96 female survivors of childhood HL treated with chest radiotherapy. Outcomes measured included imaging sensitivity and specificity, breast cancer characteristics, and incidence of additional imaging and breast biopsy. RESULTS Median age at first screening was 30 years, and the median number of MRI screening rounds was 3. Ten breast cancers were detected in 9 women at a median age of 39 years (range, 24-43 years). Half were invasive and half were preinvasive. The median size of invasive tumors was 8 mm (range, 3-15 mm), and none had lymph node involvement. Sensitivity and specificity of the screening modalities were as follows: for MRI alone, 80% and 93.5%, respectively; MMG alone, 70% and 95%, respectively; both modalities combined, 100% and 88.6%, respectively. All invasive tumors were detected by MRI. Additional investigations were required in 52 patients, (54%), and 26 patients (27%) required breast biopsy, with 10 patients requiring more than 1 biopsy. CONCLUSIONS Screening including breast MRI with MMG has high sensitivity and specificity in pediatric HL survivors, with breast cancers detected at an early stage, although it is associated with a substantial rate of additional investigations. Cancer 2014;120:2507–2513. © 2014 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. Screening female survivors of pediatric Hodgkin Lymphoma for breast cancer with MRI and mammography detected tumors at an earlier stage than prior studies of mammography alone, although a substantial proportion of women required additional tests for benign imaging findings. The 5-year cumulative incidence of invasive or preinvasive tumors after initiating screening was 10.8%

Selection of Wavelet Based Optimal Denoising Method in fMRI Signals

2020 Innovations in Intelligent Systems and Applications Conference, ASYU 2020 -- 15 October 2020 through 17 October 2020 -- -- 1653052-s2.0-85097957219Functional magnetic resonance images (fMRI) contains high amount of noise due to their structures. This high noise limits the correct interpretation of the information contained in the signal. In order to interpret the data correctly, it is necessary to eliminate the noise with effective and efficient noise reduction techniques while protecting the information in the signal. The aim of this study is to find an optimal methodology for denoising. For this purpose, Cubic Spline, Discrete Wavelet Transform (DWT) and Maximal Overlap Discrete Wavelet Transform (MODWT) are used as wavelet based noise reduction methods. These methods are applied on a real fMRI signal and compared with different parameters and their performance was evaluated. © 2020 IEEE

Estimating the semen quality from life style using fuzzy radial basis functions

Infertility is a major problem that directly affects many people worldwide. In recent years, fertility rates decreased up to 15% in young men. Changing live conditions, stress level, environmental factors, nutritional habits play an important role on infertility. This paper suggests a novel method estimating semen quality from lifestyle, environmental factors and daily habits using the radial basis function neural networks. The accuracy of the suggested method measured as 90%. The result shows that the proposed method can be applied as a practical, fast and cheap alternative method to the laboratory tests. © 2018 International Association of Computer Science and Information Technology

Spatial Smoothing Effect on Group-Level Functional Connectivity during Resting and Task-Based fMRI

Spatial smoothing is a preprocessing step applied to neuroimaging data to enhance data quality by reducing noise and artifacts. However, selecting an appropriate smoothing kernel size can be challenging as it can lead to undesired alterations in final images and functional connectivity networks. However, there is no sufficient information about the effects of the Gaussian kernel size on group-level results for different cases yet. This study investigates the influence of kernel size on functional connectivity networks and network parameters in whole-brain rs-fMRI and tb-fMRI analyses of healthy adults. The analysis includes {0, 2, 4, 6, 8, 10} mm kernels, commonly used in practical analyses, covering all major brain networks. Graph theoretical measures such as betweenness centrality, global/local efficiency, clustering coefficient, and average path length are examined for each kernel. Additionally, principal component analysis (PCA) and independent component analysis (ICA) parameters, namely kurtosis and skewness, are evaluated for the functional images. The findings demonstrate that kernel size directly affects node connections, resulting in modifications to functional network structures and PCA/ICA parameters. However, network metrics exhibit greater resilience to these changes. © 2023 by the author

Rs-fMRI'da nucleus accumbens sinyal değişimlerinin olasiliksal analizi

2019 Medical Technologies Congress, TIPTEKNO 2019 -- 3 October 2019 through 5 October 2019 -- -- 154293Rs-fmri provides to establish the default mode network that comprises the connections of the neural networks of the brain and the relations of these connections with each other in the state of rest. However, unexpected signal alterations and changes may also occur in fmri signals in areas outside the default network. In this study, the magnitude and probability of random fluctuations in these signals were estimated by Bayesian-based change point analysis in Nucleus Accumbens signals that are not expected to be activated in resting state. The data set was acquired from 23 healthy and voluntary university students using 3T MRI scanners. With the proposed method, signals containing unexpected activation from rs-fmri signals can be estimated in linear time. © 2019 IEEE

Probabilistic analysis of nucleus accumbens signal alterations in Rs-fMRI [Rs-fMRI'da nucleus accumbens sinyal de?işimlerinin olasiliksal analizi]

2019 Medical Technologies Congress, TIPTEKNO 2019 -- 3 October 2019 through 5 October 2019 -- -- 1542932-s2.0-85075606638Rs-fmri provides to establish the default mode network that comprises the connections of the neural networks of the brain and the relations of these connections with each other in the state of rest. However, unexpected signal alterations and changes may also occur in fmri signals in areas outside the default network. In this study, the magnitude and probability of random fluctuations in these signals were estimated by Bayesian-based change point analysis in Nucleus Accumbens signals that are not expected to be activated in resting state. The data set was acquired from 23 healthy and voluntary university students using 3T MRI scanners. With the proposed method, signals containing unexpected activation from rs-fmri signals can be estimated in linear time. © 2019 IEEE