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

被引:27
作者
Csutak, Csaba [1 ,2 ]
Stefan, Paul-Andrei [1 ,3 ]
Lenghel, Lavinia Manuela [1 ,2 ]
Morosanu, Cezar Octavian [4 ]
Lupean, Roxana-Adelina [5 ]
Simonca, Larisa [6 ]
Mihu, Carmen Mihaela [1 ,5 ]
Lebovici, Andrei [1 ,2 ]
机构
[1] Cty Emergency Hosp, Radiol & Imaging Dept, Clinicilor St 5, Cluj Napoca 400006, Romania
[2] Iuliu Hatieganu Univ Med & Pharm, Surg Specialties Dept, Radiol, Clinicilor St 3-5, Cluj Napoca 400006, Romania
[3] Iuliu Hatieganu Univ Med & Pharm, Anat & Embryol Morphol Sci Dept, Victor Babes St 8, Cluj Napoca 400012, Romania
[4] North Bristol Trust, Dept Neurosurg, Southmead Hosp, Southmead Rd, Bristol BS2 8BJ, Avon, England
[5] Iuliu Hatieganu Univ Med & Pharm, Morphol Sci Dept, Histol, Louis Pasteur St 4, Cluj Napoca 400349, Romania
[6] Bristol Royal Hosp Children, Dept Paediat Surg, Upper Maudlin St, Bristol BS2 8BJ, Avon, England
关键词
glioblastoma; computer-aided diagnosis; magnetic resonance imaging; texture analysis; APPARENT DIFFUSION-COEFFICIENT; COMPUTER-AIDED DIAGNOSIS; HIGH-B-VALUE; GLIOBLASTOMA-MULTIFORME; TUMOR HETEROGENEITY; MR-IMAGES; DISCRIMINATION; CLASSIFICATION; SPECTROSCOPY; BIOMARKERS;
D O I
10.3390/brainsci10090638
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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.
引用
收藏
页码:1 / 17
页数:17
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