Background: The purpose of this study was to evaluate the radiologic characteristics and pathology related to the formation of peritumoral edema in meningiomas.
Methods: Seventy-nine patients with meningioma were examined by MRI and cerebral angiography. The predictive factors possibly related to peritumoral edema, such as patient age, sex, tumor location, tumor size, peritumoral rim (CSF cleft), shape of tumor margin, signal intensity of tumor in T2WI, pial blood supply, and pathology, were evaluated. We defined the edema-tumor volume ratio as EI and used this index to evaluate peritumoral edema.
Results: Male sex (P = .009), tumor size (P = .026), signal intensity of tumor in T2WI (P = .016), atypical and malignant tumor (P = .004), and pial blood supply (P = .001) correlated with peritumoral edema on univariate analyses. However, in multivariate analyses, pial blood supply was statistically significant as a factor for peritumoral edema in meningioma (P = .029). Male sex (P = .067, P < .1) and hyperintensity in T2WI (P = .075, P < .1) might have statistical probability in peritumoral edema.
Conclusions: In our results, male sex, hyperintensity on T2WI, and pial blood supply were associated with peritumoral edema in meningioma that influence the clinical prognosis of patients.
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http://dx.doi.org/10.1016/j.surneu.2007.03.027 | DOI Listing |
Sci Rep
December 2024
The Neurosurgery Department of Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, 030012, Shanxi, People's Republic of China.
This study investigated the use of bi-exponential diffusion-weighted imaging (DWI) combined with structural features to differentiate high-grade glioma (HGG) from solitary brain metastasis (SBM). A total of 57 patients (31 HGG, 26 SBM) who underwent pre-surgical multi-b DWI and structural MRI (T1W, T2W, T1W + C) were included. Volumes of interest (VOI) in the peritumoral edema area (PTEA) and enhanced tumor area (ETA) were selected for analysis.
View Article and Find Full Text PDFBMC Cancer
December 2024
Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.
Background: Soft-tissue sarcomas are rare tumors of the soft tissue. Recent diagnostic studies mainly dealt with conventional image analysis and included only a few cases. This study investigated whether low- and high-proliferative soft tissue sarcomas can be differentiated using conventional imaging and radiomics features on MRI.
View Article and Find Full Text PDFNeurosurg Rev
December 2024
Department of Neurosurgery, Neurosurgery Clinic, Birgunj, Nepal.
Intraoperative assessment of tumor margins can be challenging; as neoplastic cells may extend beyond the margins seen on preoperative imaging. Real-time intraoperative ultrasonography (IOUS) has emerged as a valuable tool for delineating tumor boundaries during surgery. However, concerns remain regarding its ability to accurately distinguish between tumor margins, peritumoral edema, and normal brain tissue.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Background: Accurate identification of pathologic grade before operation is helpful for guiding clinical treatment decisions and improving the prognosis for soft tissue sarcoma (STS).
Purpose: To construct and assess a magnetic resonance imaging (MRI)-based radiomics nomogram incorporating intratumoral habitats (subregions of clusters of voxels containing similar features) and peritumoral features for the preoperative prediction of the pathological grade of STS.
Methods: The MRI data of 145 patients with STS (74 low-grade and 71 high-grade) from 4 hospitals were retrospectively collected, including enhanced T1-weighted and fat-suppressed-T2-weighted sequences.
Cancer Imaging
December 2024
Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, 7 Weiwu Road, Zhengzhou, 450000, PR China.
Objective: This study aims to evaluate the effectiveness of deep learning features derived from multi-sequence magnetic resonance imaging (MRI) in determining the O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status among glioblastoma patients.
Methods: Clinical, pathological, and MRI data of 356 glioblastoma patients (251 methylated, 105 unmethylated) were retrospectively examined from the public dataset The Cancer Imaging Archive. Each patient underwent preoperative multi-sequence brain MRI scans, which included T1-weighted imaging (T1WI) and contrast-enhanced T1-weighted imaging (CE-T1WI).
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