Differentiating High-Grade Gliomas from Brain Metastases at Magnetic Resonance: The Role of Texture Analysis of the Peritumoral Zone

High-grade gliomas (HGGs) and solitary brain metastases (BMs) have similar imaging appearances, which often leads to misclassification. In HGGs, the surrounding tissues show malignant invasion, while BMs tend to displace the adjacent area. The surrounding edema produced by the two cannot be differentiated by conventional magnetic resonance (MRI) examinations. Forty-two patients with pathology-proven brain tumors who underwent conventional pretreatment MRIs were retrospectively included (HGGs, n = 16; BMs, n = 26). Texture analysis of the peritumoral zone was performed on the T2-weighted sequence using dedicated software. The most discriminative texture features were selected using the Fisher and the probability of classification error and average correlation coefficients. The ability of texture parameters to distinguish between HGGs and BMs was evaluated through univariate, receiver operating, and multivariate analyses. The first percentile and wavelet energy texture parameters were independent predictors of HGGs (75–87.5% sensitivity, 53.85–88.46% specificity). The prediction model consisting of all parameters that showed statistically significant results at the univariate analysis was able to identify HGGs with 100% sensitivity and 66.7% specificity. Texture analysis can provide a quantitative description of the peritumoral zone encountered in solitary brain tumors, that can provide adequate differentiation between HGGs and BMs.

Download Full-text

Proton magnetic resonance spectroscopy in the distinction of high-grade cerebral gliomas from single metastatic brain tumors

Acta Radiologica ◽

10.3109/02841850903482901 ◽

2010 ◽

Vol 51 (3) ◽

pp. 316-325 ◽

Cited By ~ 68

Author(s):

Andres Server ◽

Roger Josefsen ◽

Bettina Kulle ◽

Jan Mæhlen ◽

Till Schellhorn ◽

...

Keyword(s):

Magnetic Resonance ◽

Brain Tumors ◽

Mr Imaging ◽

Brain Metastases ◽

High Grade ◽

Peritumoral Edema ◽

Metastatic Brain Tumors ◽

Predictive Values ◽

Cutoff Value ◽

High Grade Gliomas

Background: Brain metastases and primary high-grade gliomas, including glioblastomas multiforme (GBM) and anaplastic astrocytomas (AA), may be indistinguishable by conventional magnetic resonance (MR) imaging. Identification of these tumors may have therapeutic consequences. Purpose: To assess the value of MR spectroscopy (MRS) using short and intermediate echo time (TE) in differentiating solitary brain metastases and high-grade gliomas on the basis of differences in metabolite ratios in the intratumoral and peritumoral region. Material and Methods: We performed MR imaging and MRS in 73 patients with histologically verified intraaxial brain tumors: 53 patients with high-grade gliomas (34 GBM and 19 AA) and 20 patients with metastatic brain tumors. The metabolite ratios of Cho/Cr, Cho/NAA, and NAA/Cr at intermediate TE and the presence of lipids at short TE were assessed from spectral maps in the tumoral core, peritumoral edema, and contralateral normal-appearing white matter. The differences in the metabolite ratios between high-grade gliomas/GBM/AA and metastases were analyzed statistically. Cutoff values of Cho/Cr, Cho/NAA, and NAA/Cr ratios in the peritumoral edema, as well as Cho/Cr and NAA/Cr ratios in the tumoral core for distinguishing high-grade gliomas/GBM/AA from metastases were determined by receiver operating characteristic (ROC) curve analysis. Results: Significant differences were noted in the peritumoral Cho/Cr, Cho/NAA, and NAA/ Cr ratios between high-grade gliomas/GBM/AA and metastases. ROC analysis demonstrated a cutoff value of 1.24 for peritumoral Cho/Cr ratio to provide sensitivity, specificity, positive (PPV), and negative predictive values (NPV) of 100%, 88.9%, 80.0%, and 100%, respectively, for discrimination between high-grade gliomas and metastases. By using a cutoff value of 1.11 for peritumoral Cho/NAA ratio, the sensitivity was 100%, the specificity was 91.1%, the PPV was 83.3%, and the NPV was 100%. Conclusion: The results of this study demonstrate that MRS can differentiate high-grade gliomas from metastases, especially with peritumoral measurements, supporting the hypothesis that MRS can detect infiltration of tumor cells in the peritumoral edema.

Download Full-text

Multiparametric magnetic resonance imaging to differentiate high-grade gliomas and brain metastases

Journal of Neuroradiology ◽

10.1016/j.neurad.2011.11.002 ◽

2012 ◽

Vol 39 (5) ◽

pp. 301-307 ◽

Cited By ~ 41

Author(s):

Nathalie Mouthuy ◽

Guy Cosnard ◽

Jorge Abarca-Quinones ◽

Nicolas Michoux

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Brain Metastases ◽

High Grade ◽

Resonance Imaging ◽

Multiparametric Magnetic Resonance Imaging ◽

High Grade Gliomas

Download Full-text

Differentiation of Endometriomas from Ovarian Hemorrhagic Cysts at Magnetic Resonance: The Role of Texture Analysis

Medicina ◽

10.3390/medicina56100487 ◽

2020 ◽

Vol 56 (10) ◽

pp. 487

Author(s):

Roxana-Adelina Lupean ◽

Paul-Andrei Ștefan ◽

Csaba Csutak ◽

Andrei Lebovici ◽

Andrei Mihai Măluțan ◽

...

Keyword(s):

Magnetic Resonance ◽

Texture Analysis ◽

Univariate Analysis ◽

Three Dimensional ◽

Correlation Coefficients ◽

Texture Features ◽

Classification Error ◽

Ovarian Cysts ◽

Diagnostic Features ◽

T2 Weighted Images

Background and Objectives: To assess ovarian cysts with texture analysis (TA) in magnetic resonance (MRI) images for establishing a differentiation criterion for endometriomas and functional hemorrhagic cysts (HCs) that could potentially outperform their classic MRI diagnostic features. Materials and Methods: Forty-three patients with known ovarian cysts who underwent MRI were retrospectively included (endometriomas, n = 29; HCs, n = 14). TA was performed using dedicated software based on T2-weighted images, by incorporating the whole lesions in a three-dimensional region of interest. The most discriminative texture features were highlighted by three selection methods (Fisher, probability of classification error and average correlation coefficients, and mutual information). The absolute values of these parameters were compared through univariate, multivariate, and receiver operating characteristic analyses. The ability of the two classic diagnostic signs (“T2 shading” and “T2 dark spots”) to diagnose endometriomas was assessed by quantifying their sensitivity (Se) and specificity (Sp), following their conventional assessment on T1-and T2-weighted images by two radiologists. Results: The diagnostic power of the one texture parameter that was an independent predictor of endometriomas (entropy, 75% Se and 100% Sp) and of the predictive model composed of all parameters that showed statistically significant results at the univariate analysis (100% Se, 100% Sp) outperformed the ones shown by the classic MRI endometrioma features (“T2 shading”, 75.86% Se and 35.71% Sp; “T2 dark spots”, 55.17% Se and 64.29% Sp). Conclusion: Whole-lesion MRI TA has the potential to offer a superior discrimination criterion between endometriomas and HCs compared to the classic evaluation of the two lesions’ MRI signal behaviors.

Download Full-text

Use of fluorescence to guide resection or biopsy of primary brain tumors and brain metastases

Neurosurgical FOCUS ◽

10.3171/2013.12.focus13464 ◽

2014 ◽

Vol 36 (2) ◽

pp. E10 ◽

Cited By ~ 80

Author(s):

Serge Marbacher ◽

Elisabeth Klinger ◽

Lucia Schwyzer ◽

Ingeborg Fischer ◽

Edin Nevzati ◽

...

Keyword(s):

Adverse Effects ◽

Brain Tumors ◽

Brain Metastases ◽

Low Grade ◽

High Grade ◽

Open Resection ◽

Who Grade ◽

Primary Brain Tumors ◽

High Grade Gliomas ◽

Surgical Adjunct

Object The accurate discrimination between tumor and normal tissue is crucial for determining how much to resect and therefore for the clinical outcome of patients with brain tumors. In recent years, guidance with 5-aminolevulinic acid (5-ALA)–induced intraoperative fluorescence has proven to be a useful surgical adjunct for gross-total resection of high-grade gliomas. The clinical utility of 5-ALA in resection of brain tumors other than glioblastomas has not yet been established. The authors assessed the frequency of positive 5-ALA fluorescence in a cohort of patients with primary brain tumors and metastases. Methods The authors conducted a single-center retrospective analysis of 531 patients with intracranial tumors treated by 5-ALA–guided resection or biopsy. They analyzed patient characteristics, preoperative and postoperative liver function test results, intraoperative tumor fluorescence, and histological data. They also screened discharge summaries for clinical adverse effects resulting from the administration of 5-ALA. Intraoperative qualitative 5-ALA fluorescence (none, mild, moderate, and strong) was documented by the surgeon and dichotomized into negative and positive fluorescence. Results A total of 458 cases qualified for final analysis. The highest percentage of 5-ALA–positive fluorescence in open resection was found in glioblastomas (96%, n = 99/103). Among other tumors, 5-ALA–positive fluorescence was detected in 88% (n = 21/32) of anaplastic gliomas (WHO Grade III), 40% (n = 8/19) of low-grade gliomas (WHO Grade II), no (n = 0/3) WHO Grade I gliomas, and 77% (n = 85/110) of meningiomas. Among metastases, the highest percentage of 5-ALA–positive fluorescence was detected in adenocarcinomas (48%, n = 13/27). Low rates or absence of positive fluorescence was found among pituitary adenomas (8%, n = 1/12) and schwannomas (0%, n = 0/7). Biopsies of high-grade primary brain tumors showed positive rates of fluorescence similar to those recorded for open resection. No clinical adverse effects associated with use of 5-ALA were observed. Only 1 patient had clinically silent transient elevation of liver enzymes. Conclusions Study findings suggest that the administration of 5-ALA as a surgical adjunct for resection and biopsy of primary brain tumors and brain metastases is safe. In light of the high rate of positive fluorescence in high-grade gliomas other than glioblastomas, meningiomas, and a variety of metastatic cancers, 5-ALA seems to be a promising tool for enhancing intraoperative identification of neoplastic tissue and optimizing the extent of resection.

Download Full-text

Clinicopathological and Prognostic Significance of CD44s and CD44v6 Expression in Patients with Glioma: A Systematic Review and Meta-analysis

10.21203/rs.3.rs-38156/v1 ◽

2020 ◽

Author(s):

Kai Xie ◽

Xinyi Zhang ◽

Changsheng Xing ◽

Wenting Guan ◽

Luyuan Zhang ◽

...

Keyword(s):

Multivariate Analysis ◽

Brain Metastases ◽

Meta Analysis ◽

Univariate Analysis ◽

Cochrane Library ◽

High Grade ◽

Cd44 Expression ◽

Cd44s Expression ◽

High Grade Gliomas ◽

Cd44v6 Expression

Abstract Background: Cancer stem cell surface marker CD44 has been revealed to promote tumor growth, progression, and metastasis in gliomas. Although the prognostic and clinicopathological value of CD44 standard form (CD44s) and its variant isoform CD44v6 expression in glioma patients has been evaluated in several independent studies, their results remained controversial. Therefore, we performed this meta-analysis to investigate the prognostic and clinicopathological association of CD44s/CD44v6 expression with glioma patients.Methods: A comprehensive literature search was performed in the electronic databases PubMed, EMBASE, Web of Science, the Cochrane Library, China National Knowledge Infrastructure (CNKI), and the Wangfang Data. The statistical analysis was conducted using Stata 15.0 and Review Manager 5.3.Results: A total of 43 studies with 2817 glioma patients were included in this meta-analysis. Pooled results indicated that positive expression of CD44s was significantly associated with poorer overall survival (OS, univariate analysis, HR =1.63, 95% CI= [1.16–2.29], P=0.005; multivariate analysis, HR=2.14, 95%CI= [1.21, 3.78], P=0.009), and reduced progression-free survival (PFS) in the univariate analysis (HR=2.09, 95% CI= [1.59, 2.75], P<0.00001), but not with PFS in the multivariate analysis (P>0.05) or tumor recurrence (P>0.05). CD44 expression was significantly upregulated in glioma tissues when compared with non-tumorous brain tissues (CD44s, OR=31.31, 95% CI= [15.22, 64.43], P<0.00001; CD44v6, OR=13.18, 95% CI= [5.51, 31.51], P<0.00001). In particular, CD44 expression was preferentially expressed in high-grade gliomas (grade III-IV vs. grade I-II, CD44s, OR=4.67, 95% CI= [3.18, 6.87], P<0.00001; CD44v6, OR=2.06, 95% CI= [1.21, 3.51], P=0.008). CD44s expression was lower in brain metastases than that in primary gliomas (OR=0.25, 95% CI= [0.10, 0.60], P=0.002), however, higher expression of CD44v6 was detected in brain metastases when compared with primary gliomas (OR=49.44, 95% CI= [13.06, 187.22], P<0.00001).Conclusions:This meta-analysis revealed the prognostic value of CD44s expression and clinicopathological significance of CD44s/CD44v6 expression in gliomas. Increased CD44s expression can predict worse prognosis of glioma patients. Particularly, CD44s is an independent prognostic factor for poor OS of glioma patients. Both CD44s and CD44v6 were glioma patients predominantly expressed in glioma tissues, especially in high-grade gliomas. Additionally, CD44v6 is a potential diagnostic biomarker for differentiating brain metastases from primary gliomas in individual cases. Therapeutic strategies targeting CD44 in gliomas should be further explored in the future.

Download Full-text

Differentiation of High-grade Gliomas from Brain Metastases Using Tissue Similarity Maps (TSMs) Based Relative Cerebral Blood Volume Values

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405613666170405143615 ◽

2018 ◽

Vol 14 (4) ◽

pp. 594-598 ◽

Cited By ~ 1

Author(s):

Su Hu ◽

Xi-ming Wang ◽

Mo Zhu ◽

Guang-yu Hao ◽

Chen-fei Yao ◽

...

Keyword(s):

Brain Metastases ◽

Blood Volume ◽

Cerebral Blood Volume ◽

High Grade ◽

Relative Cerebral Blood Volume ◽

Similarity Maps ◽

High Grade Gliomas

Download Full-text

Intraoperative Magnetic Resonance Imaging for Low-Grade and High-Grade Gliomas: What Is the Evidence? A Meta-Analysis

World Neurosurgery ◽

10.1016/j.wneu.2021.01.089 ◽

2021 ◽

Author(s):

Yu Tung Lo ◽

Hyunkyung Lee ◽

Cher Shui ◽

Nayan Lamba ◽

Rasika Korde ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Meta Analysis ◽

Low Grade ◽

High Grade ◽

Resonance Imaging ◽

Intraoperative Magnetic Resonance Imaging ◽

High Grade Gliomas

Download Full-text

Radiomics-Derived Data by Contrast Enhanced Magnetic Resonance in RAS Mutations Detection in Colorectal Liver Metastases

Cancers ◽

10.3390/cancers13030453 ◽

2021 ◽

Vol 13 (3) ◽

pp. 453

Author(s):

Vincenza Granata ◽

Roberta Fusco ◽

Antonio Avallone ◽

Alfonso De Stefano ◽

Alessandro Ottaiano ◽

...

Keyword(s):

Multivariate Analysis ◽

Magnetic Resonance ◽

Liver Metastases ◽

Univariate Analysis ◽

Features Selection ◽

Ras Mutation ◽

Mutation Status ◽

Contrast Enhanced ◽

Texture Parameters ◽

Derived Data

Purpose: To assess the association of RAS mutation status and radiomics-derived data by Contrast Enhanced-Magnetic Resonance Imaging (CE-MRI) in liver metastases. Materials and Methods: 76 patients (36 women and 40 men; 59 years of mean age and 36–80 years as range) were included in this retrospective study. Texture metrics and parameters based on lesion morphology were calculated. Per-patient univariate and multivariate analysis were made. Wilcoxon-Mann-Whitney U test, receiver operating characteristic (ROC) analysis, pattern recognition approaches with features selection approaches were considered. Results: Significant results were obtained for texture features while morphological parameters had not significant results to classify RAS mutation. The results showed that using a univariate analysis was not possible to discriminate accurately the RAS mutation status. Instead, considering a multivariate analysis and classification approaches, a KNN exclusively with texture parameters as predictors reached the best results (AUC of 0.84 and an accuracy of 76.9% with 90.0% of sensitivity and 67.8% of specificity on training set and an accuracy of 87.5% with 91.7% of sensitivity and 83.3% of specificity on external validation cohort). Conclusions: Texture parameters derived by CE-MRI and combined using multivariate analysis and patter recognition approaches could allow stratifying the patients according to RAS mutation status.

Download Full-text