Role of mass effect, tumor volume and peritumoral edema volume in the differential diagnosis of primary brain tumor and metastasis

Barış, Mustafa; Çelik, Ahmet; Gezer, Naciye Sinem; Ada, Emel

doi:10.1016/j.clineuro.2016.07.008

Cited by 34 publications

(14 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the perilesional edema in metastasis can vary from minimal to extensive (Sharma et al, 2013). A previous study found a statistically significant difference in the ratio of enhancing tumor to perilesional edema (Maurer et al, 2013;Baris et al, 2016), whereas we found no such difference.…”

Section: Discussioncontrasting

confidence: 98%

See 1 more Smart Citation

Evaluation of Perienhancing Area in Differentiation between Glioblastoma and Solitary Brain Metastasis

Thammaroj

Wongwichit

Boonrod

2020

Asian Pac J Cancer Prev

View full text Add to dashboard Cite

Purpose: Accurate differential diagnosis between glioblastoma and brain metastasis is important. We aimed to differentiate these tumors by evaluation of the perienhancing area. Materials and Methods: Thirty patients with glioblastoma and solitary brain metastasis were included. The diameters of perienhancing and enhancing areas were measured, and the percentage of enhancing area was calculated. We measured Apparent diffusion coefficient (ADC) of perienhancing and enhancing areas. Intratumoral necrotic areas were measured. Results: The enhancing area of glioblastoma was 56.61% and metastasis was 42.55% (p = 0.08). The ADC values of the perienhancing part of GBM was 0.7 and metastasis was 0.79 (p = 0.052). The ADC value of the enhancing part of the GBM was 0.82 and metastasis was 0.8 (p-value = 0.72). The intratumoral necrotic area of glioblastoma (152.25 mm 3) was higher than in metastasis (0 mm 3) (p-value = 0.003) with a cutoff area of 11.8 mm 2. Conclusion: The ADC values of the perienhancing area were lower in glioblastoma with a near-significant p-value. Other perienhancing parameters demonstrated no significant difference between both tumors. The intratumoral necrotic area of glioblastoma is larger than metastasis.

show abstract

Section: Discussioncontrasting

confidence: 98%

“…Glioblastoma and metastasis differ in degrees of perilesional edema. Few previous studies have shown significant differences between the ratio of peritumoral edema and enhancing tumor (Maurer et al, 2013;Baris et al, 2016). Perilesional edema was greater in brain metastasis than in glioblastoma.…”

Section: Introductionmentioning

confidence: 82%

Evaluation of Perienhancing Area in Differentiation between Glioblastoma and Solitary Brain Metastasis

Thammaroj

Wongwichit

Boonrod

2020

Asian Pac J Cancer Prev

View full text Add to dashboard Cite

show abstract

“…T 1 W post‐contrast images, as used in this study, is a commonly acquired sequence in all standard MR protocols, including short presurgical scans. A few previous studies aimed to differentiate between brain tumor types based on a single contrast; however, these studies were conducted on relatively small cohorts, and were limited to the data acquired from a specific MRI system.…”

Section: Discussionmentioning

confidence: 99%

Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis

Artzi

Bressler

Bashat

2019

Magnetic Resonance Imaging

130

107

View full text Add to dashboard Cite

Background Differentiation between glioblastoma and brain metastasis is highly important due to differing medical treatment strategies. While MRI is the modality of choice for the assessment of patients with brain tumors, differentiation between glioblastoma and solitary brain metastasis may be challenging due to their similar appearance on MRI. Purpose To differentiate between glioblastoma and brain metastasis subtypes using radiomics analysis based on conventional post‐contrast T1‐weighted (T1W) MRI. Study Type Retrospective. Subjects Data were acquired from 439 patients: 212 patients with glioblastoma and 227 patients with brain metastasis (breast, lung, and others). Field Strength/Sequence Post‐contrast 3D T1W gradient echo images, acquired with 1.5 and 3.0 T MR systems. Assessment Analysis included image preprocessing, segmentation of tumor area, and features extraction including: patients' clinical information, tumor location, first‐ and second‐order statistical, morphological, wavelet features, and bag‐of‐features. Following dimension reduction, classification was performed using various machine‐learning algorithms including support‐vector machine (SVM), k‐nearest neighbor, decision trees, and ensemble classifiers. Statistical Tests For classification, the data were divided into training (80%) and testing datasets (20%). Following optimization of the classifiers, mean sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated. Results For the testing dataset, the best results for differentiation of glioblastoma from brain metastasis were obtained using the SVM classifier with mean accuracy = 0.85, sensitivity = 0.86, specificity = 0.85, and AUC = 0.96. The best classification results between glioblastoma and brain metastasis subtypes were obtained using SVM classifier with mean accuracy = 0.85, 0.89, 0.75, 0.90; sensitivity = 1.00, 0.60, 0.57, 0.11; specificity = 0.76, 0.92, 0.87, 0.99; and AUC = 0.98, 0.81, 0.83, 0.57 for the glioblastoma, breast, lung, and other brain metastases, respectively. Data Conclusion Differentiation between glioblastoma and brain metastasis showed a high success rate based on postcontrast T1W MRI. Classification between glioblastoma and brain metastasis subtypes may require additional MR sequences with other tissue contrasts. Level of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:519–528.

show abstract

“…Therefore, the early diagnosis, accurate differentiation, and dynamic monitoring progression of primary and metastatic brain tumors are of great importance. However, traditional methods, such as clinical examination, magnetic resonance imaging, and histopathological biopsy, are often limited to meet the requirement for clinical practice (7).…”

Section: Discussionmentioning

confidence: 99%

Next-Generation Sequencing Analysis of ctDNA for the Detection of Glioma and Metastatic Brain Tumors in Adults

Liang

Zhao

et al. 2020

Front. Neurol.

View full text Add to dashboard Cite

Background and aims: The next-generation sequencing technologies and their related assessments of circulating tumor DNA in both glioma and metastatic brain tumors remain largely limited. Methods: Based largely on a protocol approved by the institutional review board at Peking University International Hospital, the current retrospective, single-center study was conducted. Genomic DNA was extracted from blood samples or tumor tissues. With the application of NextSeq 500 instrument (Illumina), Sequencing was performed with an average coverage of 550-fold. Paired-end sequencing was employed utilized with an attempt to achieve improved sensitivity of duplicate detection and therefore to increase the detection reliability of possible fusions. Results: A total of 28 patients (21 men and 7 women) with brain tumors in the present study were involved in the study. The patients enrolled were assigned into two groups, including glioma group ( n = 21) and metastatic brain tumor group ( n = 7). The mean age of metastatic brain tumor group (59.86 ± 8.85 y), (43.65 ± 13.05 y) reported significantly higher results in comparison to that of glioma group (45.3 ± 12.3 years) ( P < 0.05). The mutant genes in metastatic brain tumor group included ALK, MDM2, ATM, BRCA1, FGFR1, MDM4 and KRAS ; however, there were no glioma-related mutant genes including MGMT, IDH1 , IDH2, 1p/19q , and BRAF et al. Interesteringly, only two patient (28.3%) was detected blood ctDNA in metastatic brain tumor group; In contrast, blood ctDNA was found in ten glioma patients (47.6%) including 1p/19q, MDM2, ERBB2, IDH1, CDKN2A, CDK4, PDGFRA, CCNE1, MET . The characterizations of IDH mutations in the glioma included IDH1 mutation (p.R132H) and IDH2 mutation (p.R172K). The mutation rate of IDH in tumor tissues was 37.06 ± 8.32%, which was significantly higher than blood samples ( P < 0.05). Conclusion: The present study demonstrated that the mutant genes among glioma and metastatic brain tumors are shown to be different. Moreover, the ctDNAs in the metastatic brain tumors included ALK and MDM2 , and glioma-related ctDNAs included 1p/19q and MDM2 followed by frequencies of ERBB2, IDH1, CDKN2A, CDK4, PDGFRA, CCNE1, MET . These ctDNAs might be biomarkers and therapeutic responders in brain tumor.

show abstract

Role of mass effect, tumor volume and peritumoral edema volume in the differential diagnosis of primary brain tumor and metastasis

Cited by 34 publications

References 15 publications

Evaluation of Perienhancing Area in Differentiation between Glioblastoma and Solitary Brain Metastasis

Evaluation of Perienhancing Area in Differentiation between Glioblastoma and Solitary Brain Metastasis

Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis

Next-Generation Sequencing Analysis of ctDNA for the Detection of Glioma and Metastatic Brain Tumors in Adults

Contact Info

Product

Resources

About