European Radiology: The value of multiparametric z-spectrum MRI in clinical glioma stratification

Gliomas are the most common primary brain tumors in the central nervous system and are associated with high rates of disability and mortality
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Patients with glioma have poor overall survival, even with adjuvant radiochemotherapy after surgical resection

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Gliomas are the most common primary brain tumors in the central nervous system and are associated with high rates of disability and mortality

The World Health Organization (WHO) tumor grade has been used as the primary criterion for judging the malignant degree of glioma
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At this stage , the use of non-invasive magnetic resonance imaging (MRI) to predict the grade and molecular features of gliomas is an area of ​​increasing clinical interest

Recently , a study published in the journal European Radiology explored the ability of fitted Z-spectrum contrast maps and their combinations to simultaneously predict glioma grade, IDH genotype, and 1p/19q coding break status for a noninvasive assessment .

This study retrospectively included 113 glioma patients
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DSW differed significantly by grade, IDH genotype, and 1p/19q coding deletion status
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Figure 1.
ROC curve analysis of fitted Z-spectrum parameters and their combined models in differentiating glioma subtypes .
 

Figure 1.
ROC curve analysis of fitted Z-spectrum parameters and their combined models in differentiating glioma subtypes .

Figure 1.

This study demonstrates the feasibility of fitting multiple Z-spectrum MRI components, including APT, CEST@2ppm, NOE, MTR, and DSW, and enabling discrimination between LGGs and GBMs, IDH genotypes, and 1p/19q coding deletion status .

Original source :

Changliang Su , Shijie Xu , Danlin Lin ,et al .
Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients .
DOI : 10.
1007/s00330-021-08175-3

Changliang Su Shijie Xu Danlin Lin ,et al Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients 10.

1007/s00330-021-08175-3 10.
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