Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

Cuellar-Baena, Sandra; Morais, L.M.T.S.; Cendes, F.; Faria, A.V.; Castellano, Gabriela

doi:10.1590/s0100-879x2011000400012

Cited by 1 publication

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“…The LCmodel as defined by Provencher was used to analyze in vivo proton spectrum [7]. This software can calculates the best fit to the experimental spectrum as a linear combination of model spectra.…”

Section: Mrs Data Analysismentioning

confidence: 99%

Quantitative metabolic characteristics in the peritumoral region of gliomas at 7T

Yan¹,

et al. 2021

THC

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BACKGROUND: The determination of tumor peripheral is of great significance in clinical diagnosis and treatment. OBJECTIVE: In this study, we aim to obtain the metabolic condition in tumor peripheral of gliomas in vivo at 7T. METHODS: C6 glioma cells were implanted into the right basal ganglia of Sprague-Dawley (SD) rats under stereotactic guided to create the glioma models. The models were sequentially undergone MRI and MRS examination on an 7T MR scanner designed for animals 7 days after the operation. Neuro metabolites were investigated from the center of the tumor, solid part of the tumor, peritumoral region, and contralateral white matter, and be quantified using the LCmodel software. Glial fibrillary acidic protein (GFAP) immunohistochemistry and conventional hematoxylin and eosin (HE) staining were performed after the imaging protocol. RESULTS: Our results found that the inositol (Ins) and taurine (Tau) significantly defected in tumor peripheral compared to both tumor solid and normal tissues (P< 0.05). In contrast, the glutamate and glutamine (Glx) escalated and peaked at the tumor peripheral (P< 0.05). CONCLUSIONS: This study revealed that Ins, Tau, and Glx have the potential to provide specific biomarkers for the location of tumor peripheral of glioma.

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Section: Mrs Data Analysismentioning

confidence: 99%

Quantitative metabolic characteristics in the peritumoral region of gliomas at 7T

Yan¹,

et al. 2021

THC

View full text Add to dashboard Cite

show abstract

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

Cited by 1 publication

References 10 publications

Quantitative metabolic characteristics in the peritumoral region of gliomas at 7T

Quantitative metabolic characteristics in the peritumoral region of gliomas at 7T

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