Introduction: Our purpose was to determine whether perfusion MR imaging can be used to differentiate benign and malignant meningiomas on the basis of the differences in perfusion of tumor parenchyma and/or peritumoral edema.
Methods: A total of 33 patients with preoperative meningiomas (25 benign and 8 malignant) underwent conventional and dynamic susceptibility contrast perfusion MR imaging. Maximal relative cerebral blood volume (rCBV) and the corresponding relative mean time to enhance (rMTE) (relative to the contralateral normal white matter) in both tumor parenchyma and peritumoral edema were measured. The independent samples t-test was used to determine whether there was a statistically significant difference in the mean rCBV and rMTE ratios between benign and malignant meningiomas.
Results: The mean maximal rCBV values of benign and malignant meningiomas were 7.16+/-4.08 (mean+/-SD) and 5.89+/-3.86, respectively, in the parenchyma, and 1.05+/-0.96 and 3.82+/-1.39, respectively, in the peritumoral edema. The mean rMTE values were 1.16+/-0.24 and 1.30+/-0.32, respectively, in the parenchyma, and 0.91+/-0.25 and 1.24+/-0.35, respectively, in the peritumoral edema. The differences in rCBV and rMTE values between benign and malignant meningiomas were not statistically significant (P>0.05) in the parenchyma, but both were statistically significant (P<0.05) in the peritumoral edema.
Conclusion: Perfusion MR imaging can provide useful information on meningioma vascularity which is not available from conventional MRI. Measurement of maximal rCBV and corresponding rMTE values in the peritumoral edema is useful in the preoperative differentiation between benign and malignant meningiomas.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2440923 | PMC |
| http://dx.doi.org/10.1007/s00234-008-0373-y | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Tumor biomarkers contribute to the diagnosis and clinical management of the O-RADS MRI risk stratification system for epithelial ovarian tumors.
World J Surg Oncol
January 2025
Department of Gynecology, Women's Hospital of Nanjing Medical University, Nanjing Women and Children's Healthcare Hospital, Nanjing, 210004, China.
Background: To assess the effectiveness of tumor biomarkers in distinguishing epithelial ovarian tumors (EOTs) and guiding clinical decisions across each Ovarian-Adnexal Reporting and Data System (O-RADS) MRI risk category, the aim is to prevent unnecessary surgeries for benign lesions, avoid delays in treating malignancies, and benefit individuals requiring fertility preservation or those intolerant to over-extensive surgery.
Methods: A total of 54 benign, 104 borderline, and 203 malignant EOTs (BeEOTs, BEOTs and MEOTs) were enrolled and retrospectively assigned risk scores. The role of tumor biomarkers in diagnosing and managing EOTs within each risk category was evaluated by combining receiver operating characteristic (ROC) curves with clinicopathological characteristics.
Advances in imaging techniques have evolved, allowing for early noninvasive diagnosis and improved management of high-risk patients with hepatocellular carcinoma (HCC). The hallmark imaging features of HCC on multiphasic cross-sectional imaging can be explained by the multistep process of hepatocarcinogenesis and is seen in 60% of cases. However, approximately 40% of cases do not abide by the classic imaging appearance and may pose a diagnostic challenge for radiologists.
View Article and Find Full Text PDFRadiomics and Deep Learning Model for Benign and Malignant Soft Tissue Tumors Differentiation of Extremities and Trunk.
Acad Radiol
January 2025
Department of Radiology, Southeast University Zhongda Hospital, No. 87 Dingjiaqiao Road, Gulou District, Nanjing, Jiangsu Province, China (M.Y., J.J.). Electronic address:
Rationale And Objectives: To develop radiomics and deep learning models for differentiating malignant and benign soft tissue tumors (STTs) preoperatively based on fat saturation T2-weighted imaging (FS-T2WI) of patients.
Materials And Methods: Data of 115 patients with STTs of extremities and trunk were collected from our hospital as the training set, and data of other 70 patients were collected from another center as the external validation set. Outlined Regions of interest included the intratumor and the peritumor region extending outward by 5 mm, then the corresponding radiomics features were extracted respectively.
Added Value of Dynamic Contrast-Enhanced Ultrasound Analysis for Differential Diagnosis of Small (≤20 mm) Solid Pancreatic Lesions.
Ultrasound Med Biol
January 2025
Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China. Electronic address:
Objective: To evaluate the added value of dynamic contrast-enhanced ultrasound (DCE-US) analysis in pre-operative differential diagnosis of small (≤20 mm) solid pancreatic lesions (SPLs).
Methods: In this retrospective study, patients with biopsy or surgerical resection and histopathologically confirmed small (≤20 mm) SPLs were included. One wk before biopsy/surgery, pre-operative B-mode ultrasound and contrast-enhanced ultrasound were performed.
An unsupervised automatic texture classification method for ultrasound images of thyroid nodules.
Phys Med Biol
January 2025
Beijing institute of control and electronic technology, 51 Beilijia, Muxidi, Xicheng District, Beijing 100038, Beijing, 100038, CHINA.
Objective Ultrasound is the predominant modality in medical practice for evaluating thyroid nodules. Currently, diagnosis is typically based on textural information. This study aims to develop an automated texture classification approach to aid physicians in interpreting ultrasound images of thyroid nodules.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!