Potential of MR spectroscopy for assessment of glioma grading

Bulik, Martin; Jancalek, Radim; Vaníček, Jiří; Škoch, Antonín; Mechl, Marek

doi:10.1016/j.clineuro.2012.11.002

Cited by 189 publications

(147 citation statements)

References 56 publications

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“…Further, MRSI is limited by heterogeneities in the tumor. 11 With the exception of a uniform magnetic field, accurate and reliable measurements also require not only excellent scanning done by a skilled MR imaging technologist, but also careful placement of ROIs to avoid areas of calcification, cysts, hemorrhage, and adjacent bone structures. As for APTWI scanning, these disadvantages are not a major problem.…”

Section: Discussionmentioning

confidence: 99%

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Amide Proton Transfer Imaging Allows Detection of Glioma Grades and Tumor Proliferation: Comparison with Ki-67 Expression and Proton MR Spectroscopy Imaging

Liu

Zhao

et al. 2017

AJNR Am J Neuroradiol

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Section: Discussionmentioning

confidence: 99%

“…10 MRSI can detect regions within gliomas that contain aggressive growth or upgrading because of strong correlations between choline and NAA levels and the Ki-67 histopathologic proliferation index. 11 Therefore, MRSI can provide important supplementary information for the management of gliomas.…”

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confidence: 99%

Amide Proton Transfer Imaging Allows Detection of Glioma Grades and Tumor Proliferation: Comparison with Ki-67 Expression and Proton MR Spectroscopy Imaging

Liu

Zhao

et al. 2017

AJNR Am J Neuroradiol

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“…1). The regional metabolite distributions of Cho and NAA and their ratios were computed inside the VOI with a resolution of 10 mm 3 . The CNIs were interpolated for each voxel inside the VOI to generate different CNI thresholds for metabolic delineation.…”

Section: Data Processingmentioning

confidence: 99%

“…12 Proton MR spectroscopy ( 1 H-MRS) can identify chemical shifts in glioma cell metabolism and has been used in preoperative tumor differentiation, grading, and radiotherapy planning. 3,22,33,35 It provides cellular metabolic information on tumors, including choline (Cho), N-acetylaspartate (NAA), creatine (Cr), lactate, 41 citrate, 2 and lipid levels. In the past decade, this imaging modality has been widely used to differentiate tumors and glioma grades both ex vivo 35 and in vivo.…”

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confidence: 99%

Metabolic approach for tumor delineation in glioma surgery: 3D MR spectroscopy image–guided resection

Zhang

Zhuang

Yao

et al. 2016

JNS

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G liomas are the most common primary brain tumors, accounting for 80% of malignant central nervous system tumors, and can be categorized into 4 grades according to their biological behavior. Patients with low-grade gliomas (LGGs) typically survive more than 5 years. 21 Those with high-grade gliomas (HGGs) have a survival time of approximately 1-3 years. An epidemiology study using primary brain tumor data collected from 1985 to 2005 showed that the 1-year survival rate of patients with malignant glioma is 53.9%, while that of paabbreviatioNs Cho = choline; CNI = choline-NAA index; CSI = chemical shift imaging; DICOM = digital imaging and communications in medicine; DTI = diffusion tensor imaging; EOR = extent of resection; fMRI = functional MR imaging; GTR = gross-total resection; 1 H-MRS = proton MR spectroscopy; HGG = high-grade glioma; LGG = low-grade glioma; MPRAGE = magnetization-prepared rapid gradient-echo; NAA = N-acetylaspartate; OS = overall survival; PFS = progression-free survival; PT = pyramidal tract; ROI = region of interest; STR = subtotal resection; VOI = volume of interest. obJective The extent of resection is one of the most essential factors that influence the outcomes of glioma resection. However, conventional structural imaging has failed to accurately delineate glioma margins because of tumor cell infiltration. Three-dimensional proton MR spectroscopy ( 1 H-MRS) can provide metabolic information and has been used in preoperative tumor differentiation, grading, and radiotherapy planning. Resection based on glioma metabolism information may provide for a more extensive resection and yield better outcomes for glioma patients. In this study, the authors attempt to integrate 3D 1 H-MRS into neuronavigation and assess the feasibility and validity of metabolically based glioma resection. methods Choline (Cho)-N-acetylaspartate (NAA) index (CNI) maps were calculated and integrated into neuronavigation. The CNI thresholds were quantitatively analyzed and compared with structural MRI studies. Glioma resections were performed under 3D 1 H-MRS guidance. Volumetric analyses were performed for metabolic and structural images from a low-grade glioma (LGG) group and high-grade glioma (HGG) group. Magnetic resonance imaging and neurological assessments were performed immediately after surgery and 1 year after tumor resection. results Fifteen eligible patients with primary cerebral gliomas were included in this study. Three-dimensional 1 H-MRS maps were successfully coregistered with structural images and integrated into navigational system. Volumetric analyses showed that the differences between the metabolic volumes with different CNI thresholds were statistically significant (p < 0.05). For the LGG group, the differences between the structural and the metabolic volumes with CNI thresholds of 0.5 and 1.5 were statistically significant (p = 0.0005 and 0.0129, respectively). For the HGG group, the differences between the structural and metabolic volumes with CNI thresholds of 0.5 and 1.0 were statistically ...

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“…M agnetic resonance spectroscopy (MRS) is an imaging technique based on the detection of radiofrequency signals generated by spins of magnetic resonance active nuclei (such as 1 H, 31 P, 13 C, and 19 F) precessing in an external magnetic field (B 0 ). In clinical practice, MRS produces spectra from the patient with an anatomical/spatial reference.…”

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confidence: 99%