Revisiting the use of proton magnetic resonance spectroscopy in distinguishing between primary and secondary malignant tumors of the central nervous system

Abstract

Background and purpose Conventional magnetic resonance images (MRI) has limitations in distinguishing primary from secondary brain tumors. Proton magnetic resonance spectroscopy ( 1 H-MRS) allows evaluation of the concentration of metabolites in a brain lesion and, hence, better characterization of the tumor. Considering that an accurate diagnosis determines the choice of treatment, our purpose was to assess the usefulness of spectroscopy data for differentiating between primary and secondary brain neoplasms. Materials and methods We undertook a retrospective analysis of 61 MRI and 1 H-MRS images of patients with histologically confirmed tumors (30 primary tumors and 31 metastatic tumors). The metabolite ratios of Cho/Cr and NAA/Cr at short TE were determined from spectroscopic curves, with a single voxel positioned in the enhancing tumor. Additional variables analyzed along with the metabolites, like as age and gender, allowed the construction of a logistic regression model to predict the tumor’s nature. The statistical analysis was done using the R software (version 4.0.3 R Core Team, 2020). Results The mean NAA/Cr and Cho/Cr ratios were higher in secondary tumors, with a good correlation between NAA/Cr and Cho/Cr (r = 0.61). The mean age of patients with primary tumors was lower than for secondary tumors (43.9 vs 55.9, respectively). Receiver operating characteristic analysis yielded a cut-off value of 0.4 for the NAA/Cr ratio with an accuracy of 73.8%, a sensitivity of 73.3% and a specificity of 74.2% in predicting metastatic tumors. Conclusion The model was reasonable in predicting the nature of the tumor and provides an additional tool for analyzing brain tumors.

Integrative Magnetic Resonance Imaging and Metabolomic Characterization of a Glioblastoma Rat Model

“…However, this association may not be present in high-grade gliomas characterized by extensive necrosis, which tend to result in a low choline peak. In such cases, increased lactate and lipid concentrations typically suppress the peaks of other metabolites, including Cho [55,56].…”

Computed Tomography, Magnetic Resonance Imaging, and Pathological Features of Gliosarcoma

“…Analysis has revealed that there may be similarities between the metabolite levels of different grade gliomas; for example, the rise in creatine may be similar, while the level of creatine in metastatic tumors may be lower. 28–30 …”

“…Analysis has revealed that there may be similarities between the metabolite levels of different grade gliomas; for example, the rise in creatine may be similar, while the level of creatine in metastatic tumors may be lower. [28][29][30] Gliosarcoma can also be differentiated from lymphoma since the signals they produce in plain and enhanced scans differ, and circular enhancement is rare for lymphoma. Lymphoma predominantly exhibits hypointensity or isointensity on T 1 WI and T 2 WI, and clear and intense enhancement can be observed following contrasting.…”

Advancements in Image-Based Models for High-Grade Gliomas Might Be Accelerated

“…61 MRI and 1 H-MRS images of patients with histologically confirmed BTs. [39] CCA might help to distinguish PsP or RN from PD after RT. 16 patients with a primary and 17 with a secondary BT.…”