Publications by authors named "Zongmeng Wang"
Article Synopsis
- The study aimed to explore how histogram analysis of synthetic MRI images can help predict axillary lymph node (ALN) status in patients with invasive ductal carcinoma (IDC) before and after contrast enhancement.
- A total of 212 IDC patients underwent various MRI examinations, and 13 tumor features were analyzed using different statistical methods to assess their effectiveness in predicting ALN metastasis.
- The findings revealed that a combined model using synthetic T1-Gd quantitative maps and clinical data provided the best prediction accuracy for ALN metastases, suggesting that SyMRI could be a valuable noninvasive tool for preoperative assessments.
Objective: The general trend in meningioma treatment is shifting from surgery to active surveillance. However, the natural history of meningioma still needs to be clarified, and a simple, practical method is needed to identify fast-growing tumors. The authors aimed to determine whether diffusion-weighted imaging (DWI) could be a valuable imaging modality for predicting meningioma growth.
View Article and Find Full Text PDFObjective: To investigate the value of histogram analysis of T1 mapping and diffusion-weighted imaging (DWI) in predicting the grade, subtype, and proliferative activity of meningioma.
Methods: This prospective study comprised 69 meningioma patients who underwent preoperative MRI including T1 mapping and DWI. The histogram metrics, including mean, median, maximum, minimum, 10th percentiles (C10), 90th percentiles (C90), kurtosis, skewness, and variance, of T1 and apparent diffusion coefficient (ADC) values were extracted from the whole tumour and peritumoural oedema using FeAture Explorer.