Objective: To investigate the potential value of quantitative parameters derived from synthetic magnetic resonance imaging (syMRI) for discriminating axillary lymph nodes metastasis (ALNM) in breast cancer patients.
Materials And Methods: A total of 56 females with histopathologically proven invasive breast cancer who underwent both conventional breast MRI and additional syMRI examinations were enrolled in this study, including 30 patients with ALNM and 26 with non-ALNM. SyMRI has enabled quantification of T1 relaxation time (T1), T2 relaxation time (T2) and proton density (PD).
Fish Shellfish Immunol
September 2023
Background: Accurate diagnosis of axillary lymph node metastasis (ALNM) of breast cancer patients is important to guide local and systemic treatment.
Purpose: To evaluate the diagnostic performance of different imaging modalities for ALNM in patients with breast cancer.
Study Type: Systematic review and network meta-analysis (NMA).
Comput Intell Neurosci
March 2022
With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy disclosure and ensuring the safe storage and sharing of image and video data in the cloud platform, the present work proposes an encryption algorithm against neural cryptography based on deep learning.
View Article and Find Full Text PDFObjective: To explore the efficacy of the quantitative parameter histogram analysis of intravoxel incoherent motion (IVIM) for different molecular prognostic factors of breast cancer.
Materials And Methods: A total of 72 patients with breast cancer who were confirmed by surgical pathology and underwent preoperative magnetic resonance imaging (MRI) were analyzed retrospectively. A region of interest (ROI) was drawn in each slice of the IVIM images.
Purpose: To evaluate and compare the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the pathological response of breast cancer to neoadjuvant chemotherapy (NAC).
Methods: We searched PubMed, EMBASE, Cochrane Library, and Web of Science systematically to identify relevant studies from inception to December 2020. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodological quality of the included studies.
Background: To investigate the value of 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) in diagnosing local tumor invasion (T stage), evaluating regional lymph node involvement (N stage), and detecting distant metastasis (M stage) in breast cancer patients.
Methods: A comprehensive computer search and manual search were performed to select any potentially eligible studies that evaluated the diagnostic efficacy of 18F-FDG PET/MRI in the tumor-node-metastasis (TNM) staging of breast cancer. Data from the included studies were extracted to calculate the pooled sensitivity, specificity, and area under the curve (AUC) to evaluate the value of 18F-FDG PET/MRI in TNM staging.
Rationale And Objectives: To assess differences of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) parameters at different postcontrast time points (TPs), and to explore the predictive value of DCE-MRI parameters for axillary lymph node (ALN) metastasis of breast cancer.
Materials And Methods: A total of 107 breast cancer patients were included retrospectively, and 50 phases were collected on DCE-MRI for each patient. DCE-MRI parameters Ktrans, Kep, Ve, TTP, Peak, Washin, Washout, and AUC were extracted from the images at 67.
Acta Crystallogr F Struct Biol Commun
May 2014