• Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review
• Dose-painting multicenter phase III trial in newly diagnosed glioblastoma: the SPECTRO-GLIO trial comparing arm A standard radiochemotherapy to arm B radiochemotherapy with simultaneous integrated boost guided by MR spectroscopic imaging
• Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients
• Evaluation of the lactate-to-N-acetyl-aspartate ratio defined with magnetic resonance spectroscopic imaging before radiation therapy as a new predictive marker of the site of relapse in patients with glioblastoma multiforme
• 3-Dimensional magnetic resonance spectroscopic imaging at 3 Tesla for early response assessment of glioblastoma patients during external beam radiation therapy
• Recurrent glioblastoma multiforme versus radiation injury: a multiparametric 3-T MR approach
• Metabolic response of glioblastoma to superselective intra-arterial cerebral infusion of bevacizumab: a proton MR spectroscopic imaging study
• Proton magnetic resonance spectroscopic imaging in newly diagnosed glioblastoma: predictive value for the site of postradiotherapy relapse in a prospective longitudinal study

Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging technique that assesses the metabolic profile of brain tissues, offering valuable insights into the diagnosis and monitoring of glioblastoma recurrence. By measuring concentrations of metabolites such as choline (Cho), N-acetylaspartate (NAA), and creatine (Cr), MRSI aids in distinguishing between tumor recurrence and treatment-induced changes like radiation necrosis.

– Choline (Cho): Elevated levels indicate increased cellular membrane turnover, commonly associated with tumor proliferation.

– N-acetylaspartate (NAA): Reduced levels suggest neuronal loss or dysfunction, often observed in tumor regions.

– Creatine (Cr): Serves as a reference metabolite for energy metabolism, typically stable across different tissues.

Chemical Shift Imaging: Provides information about the metabolic composition of tissues. Elevated levels of choline and decreased N-acetylaspartate (NAA) may indicate recurrent tumors.

Choline to N-Acetylaspartate Ratio in Glioblastoma Recurrence Diagnosis

1. Differentiating Tumor Recurrence from Radiation Injury: MRSI can help distinguish recurrent GBM from radiation-induced changes. Recurrent tumors often exhibit increased Cho/Cr and Cho/NAA ratios, whereas radiation injuries may show different metabolic patterns.

2. Guiding Radiotherapy Planning: Incorporating MRSI into radiotherapy planning allows for targeted dose escalation to metabolically active tumor regions, potentially improving local control and patient outcomes.

3. Monitoring Treatment Response: MRSI enables the assessment of metabolic changes over time, providing insights into treatment efficacy and early detection of recurrence.

– Non-Invasive: Offers a non-invasive method to assess tumor metabolism without the need for biopsy.

– Metabolic Insights: Provides detailed information on tumor biochemistry, complementing anatomical imaging.

– Early Detection: Facilitates the early identification of tumor recurrence before structural changes become apparent.

– Technical Complexity: Requires specialized equipment and expertise for acquisition and interpretation.

– Spatial Resolution: May have lower spatial resolution compared to conventional MRI, potentially limiting the detection of small lesions.

In summary, proton MRSI is a valuable tool in the management of glioblastoma, enhancing the ability to differentiate between tumor recurrence and treatment effects, guiding therapy, and monitoring disease progression.

Of 7350 records for MR spectroscopy, GBM, glioma, recurrence, diffusion, perfusion, pseudoprogression, radiomics, and advanced imaging, they screened 574 papers. A total of 228 were eligible, and analyzed 72 of them, in order to establish the role of each imaging modality and the usefulness and limitations of radiomics analysis ¹⁾.

A prospective single-institutional study aims to determine and validate thresholds for the main metabolite concentrations obtained by MR spectroscopy (MRS) and the values of the apparent diffusion coefficient (ADC) to enable distinguishing tumor recurrence from pseudoprogression. Thirty-nine patients after the standard treatment of a glioblastoma underwent advanced imaging by MRS and ADC at the time of suspected recurrence – the median time to progression was 6.7 months. The highest significant sensitivity and specificity to call the glioblastoma recurrence was observed for the total choline (tCho) to total N-acetyl aspartate (tNAA) concentration ratio with the threshold ≥ 1.3 (sensitivity 100.0% and specificity 94.7%). The ADC mean value higher than 1313 × 10(- 6) mm(2)/s was associated with pseudoprogression (sensitivity 98.3%, specificity 100.0%). The combination of MRS focused on the tCho/tNAA concentration ratio and the ADCmean value represents imaging methods applicable to early non-invasive differentiation between a glioblastoma recurrence and a pseudoprogression. However, the institutional definition and validation of thresholds for differential diagnostics are needed for the elimination of setup errors before the implementation of these multimodal imaging techniques into clinical practice, as well as into clinical trials ²⁾.

A study of Lu et al. aimed to evaluate the predictive value of metabolic parameters in preoperative non-enhancing peritumoral regions (NEPTRs) for glioblastoma recurrence, using multivoxel hydrogen proton magnetic resonance spectroscopy (1H-MRS). Clinical and imaging data from patients with recurrent glioblastoma were analyzed. Through co-registration of preoperative and post-recurrence MRI, they identified future tumor recurrence regions (FTRRs) and future non-tumor recurrence regions (FNTRRs) within the NEPTRs. Metabolic parameters were recorded separately for each region. Cox regression analysis was applied to assess the association between metabolic parameters and glioblastoma recurrence. Compared to FNTRRs, FTRRs exhibited a higher Cho/Cr ratio, higher Cho/NAA ratio, and lower NAA/Cr ratio. Both Cho/NAA and Cho/Cr ratios were recognized as risk factors in univariate and multivariate analyses (P < 0.05). The Cox regression model indicated that Cho/NAA > 1.99 and Cho/Cr > 1.73 are independent risk factors for early glioblastoma recurrence. Based on these cut-off values, patients were stratified into low-risk and high-risk groups, with a statistically significant difference in recurrence rates between the two groups (P < 0.01). The Cho/NAA and Cho/Cr ratios in NEPTRs are independent predictors of future glioblastoma recurrence. Specifically, Cho/NAA > 1.99 and/or Cho/Cr > 1.73 in NEPTRs may indicate a higher risk of early postoperative recurrence at these regions ³⁾.

This study demonstrates that metabolic ratios (Cho/NAA and Cho/Cr) in NEPTRs are independent predictors of glioblastoma recurrence and proposes clinically relevant cut-off values for risk stratification. While the findings are promising, limitations such as small sample size, lack of external validation, and potential confounding factors highlight the need for further research. The integration of metabolic and molecular data, along with validation in larger cohorts, could significantly enhance the clinical utility of these predictors.