Jia Ying

Data-driven imaging marker for cerebral consequences of Post-Acute Sequelae of COVID19 - prospective validation and [18F]FEPPA PET correlation

Chuan Huang, Jia Ying, P. Vaska, Ramin V. Parsey et autres

Motivation: Recognizing neurological symptoms in Post-Acute Sequelae of COVID-19 (PASC), this study investigates neuroinflammatory markers to develop reliable neuroimaging diagnostics. Goal(s): To validate CoreFA, a data-driven imaging marker, for detecting white matter changes and to explore its correlation with [18F]FEPPA PET neuroinflammatory …

Cross-field strength and multi-vendor reliability of MagDensity for MRI-based quantitative breast density analysis

Jia Ying, Renee Cattell, Chuan Huang

PURPOSE: Breast density (BD) is a significant risk factor for breast cancer, yet current assessment methods lack automation, quantification, and cross-platform consistency. This study aims to evaluate the reliability and cross-platform consistency of MagDensity, a novel magnetic resonance imaging (MRI)-based quantitative BD …

us (code pays fourni par la source)

Cross-Field Strength and Multi-Vendor Validation of MagDensity for MRI-based Quantitative Breast Density Analysis

Jia Ying, Renee Cattell, Chuan Huang

Abstract Purpose Breast density (BD) is a significant risk factor for breast cancer, yet current assessment methods lack automation, quantification, and cross-platform consistency. This study aims to evaluate MagDensity, a novel magnetic resonance imaging (MRI)-based quantitative BD measure, for its validity and …

us (code pays fourni par la source)

Infrapatellar fat pad is predictive of incident knee osteoarthritis one year prior to diagnosis: data from the osteoarthritis initiative

Jia Ying, Keyan Yu, Tianyun Zhao, Xiaodong Zhang et autres

The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee osteoarthritis (OA). However, whether the IPFP can serve as an independent biomarker for OA development is yet unknown. Radiomics is a powerful tool that can extract high-dimensional quantitative …

Prediction model for knee osteoarthritis using magnetic resonance–based radiomic features from the infrapatellar fat pad: data from the osteoarthritis initiative

Keyan Yu, Jia Ying, Tianyun Zhao, Lijie Zhong et autres

Background: The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee osteoarthritis (OA). Magnetic resonance (MR) signal heterogeneity of the IPFP is related to pathologic changes. In this study, we aimed to investigate whether the IPFP radiomic features …

cn, us (code pays fourni par la source)

Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility

Jia Ying, Renee Cattell, Tianyun Zhao, Zhao Jiang et autres

Abstract Presence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-breast segmentation is desirable. In this study, we aimed to develop …

us, cn (code pays fourni par la source)

Preoperative prediction of lymph node metastasis using deep learning-based features

Renee Cattell, Jia Ying, Jie Ding, Shenglan Chen et autres

Abstract Lymph node involvement increases the risk of breast cancer recurrence. An accurate non-invasive assessment of nodal involvement is valuable in cancer staging, surgical risk, and cost savings. Radiomics has been proposed to pre-operatively predict sentinel lymph node (SLN) status; however, radiomic …

us, cn (code pays fourni par la source)