To investigate the value of preoperative MRI features and ADC histogram analysis for evaluating tumor-infiltrating CD8+ T cells in meningiomas. In this single-center cross-sectional study, we conducted a retrospective analysis of clinical, imaging, and pathological data from 84 patients with meningioma and performed immunohistochemical staining to quantitatively evaluate CD8+ T cells. Using X-Tile software, we divided the patients into high-and low-CD8+ T cells groups based on cut-off values. Furthermore, we compared the clinical and MRI features between the two groups and assessed the predictive value of significant parameters by plotting ROC curves. Additionally, Spearman's analysis was used to examine the association between ADC histogram parameters and CD8+ T cells. The level of tumor-infiltrating CD8+ T cells was found to have a negative correlation with recurrence in patients with meningiomas (r=-0.235, p = 0.031). No statistically significant differences were found in clinical and conventional MRI features between the two groups (all p > 0.05). Conversely, among the ADC histogram parameters, the coefficient of variation (CV), Perc.01, Perc.05, Perc.10, and Perc.25 showed statistically significant differences between the two groups (all p < 0.05) and combined ADC histogram parameters had the highest AUC (0.791; 95%CI (0.689-0.872)). Additionally, we observed a positive correlation between Perc.01, Perc.05, Perc.10 and CD8+ T cells (p < 0.05), the CV and variance was negatively correlated with the levels of CD8+ T cells (p < 0.05). ADC histogram analysis can be used as an imaging tool to preoperatively assess CD8+ T cells in patients with meningioma, and found a certain correlation between them.
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http://dx.doi.org/10.1007/s10143-025-03197-7 | DOI Listing |
Immun Inflamm Dis
January 2025
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Objective: This study aimed to evaluate the activity of extraocular muscles (EOMs) in patients with thyroid-associated ophthalmopathy (TAO) using turbo spin echo imaging. By analyzing tissue heterogeneity, apparent diffusion coefficient (ADC) histogram analysis offers enhanced insights into edema within the EOMs.
Methods: Eighty-eight patients with TAO were retrospectively evaluated and allocated into active (n = 24, clinical activity score [CAS] ≥ 3) and inactive (n = 64, CAS < 3) groups.
Acad Radiol
January 2025
Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, PR China (L.K., B.W., Q.C., L.M., W.C., Y.C., Y.G., H.W.). Electronic address:
Rationale And Objectives: To investigate the feasibility of amide proton transfer-weighted (APTw) and diffusion-weighted MRI in evaluating the response of bladder cancer (BCa) to neoadjuvant immunochemotherapy.
Materials And Methods: From June 2021 to July 2023, participants with pathologically confirmed BCa were prospectively recruited to undergo MRI examinations, including APTw and diffusion-weighted MRI before and after neoadjuvant immunochemotherapy. Histogram analysis features (mean, median, and entropy) were extracted from pre- and post-treatment APTw and apparent diffusion coefficient (ADC) maps, respectively.
Neurosurg Rev
January 2025
Department of Radiology, Lanzhou University Second Hospital, Lanzhou, 730030, China.
To investigate the value of preoperative MRI features and ADC histogram analysis for evaluating tumor-infiltrating CD8+ T cells in meningiomas. In this single-center cross-sectional study, we conducted a retrospective analysis of clinical, imaging, and pathological data from 84 patients with meningioma and performed immunohistochemical staining to quantitatively evaluate CD8+ T cells. Using X-Tile software, we divided the patients into high-and low-CD8+ T cells groups based on cut-off values.
View Article and Find Full Text PDFCurr Med Imaging
January 2025
School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan611731, China.
Background And Objective: Lung cancer remains a leading cause of cancer-related mortality worldwide, necessitating early and accurate detection methods. Our study aims to enhance lung cancer detection by integrating VGGNet-16 form of Convolutional Neural Networks (CNNs) and Support Vector Machines (SVM) into a hybrid model (SVMVGGNet-16), leveraging the strengths of both models for high accuracy and reliability in classifying lung cancer types in different 4 classes such as adenocarcinoma (ADC), large cell carcinoma (LCC), Normal, and squamous cell carcinoma (SCC).
Methods: Using the LIDC-IDRI dataset, we pre-processed images with a median filter and histogram equalization, segmented lung tumors through thresholding and edge detection, and extracted geometric features such as area, perimeter, eccentricity, compactness, and circularity.
J Comput Assist Tomogr
January 2025
From the Diagnostic Radiology Department, Faculty of Medicine, Mansoura University-Egypt, Mansoura, Egypt.
Objective: The aim of the study is to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging in assessing treatment response in cervical cancer patients.
Methods: A retrospective analysis was done for 50 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy and underwent magnetic resonance imaging and diffusion-weighted imaging. Treatment response was classified into 4 categories according to RECIST criteria 6 months after therapy completion.
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