Proton magnetic resonance spectroscopic imaging in glioblastoma recurrence diagnosis [Neurosurgery Wiki]

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====== Proton magnetic resonance spectroscopic imaging in glioblastoma recurrence diagnosis ======

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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]].

===== Key Metabolites in MRSI =====

- **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.
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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 ====
[[Choline to N-Acetylaspartate Ratio in Glioblastoma Recurrence Diagnosis]]
===== Clinical Applications =====


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. 

===== Advantages of MRSI =====


- **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.

===== Limitations =====


- **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. 

===== Systematic Reviews =====
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
((Sidibe I, Tensaouti F, Roques M, Cohen-Jonathan-Moyal E, Laprie A. Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review. Biomedicines. 2022 Jan 26;10(2):285. doi: 10.3390/biomedicines10020285. PMID: 35203493; PMCID: PMC8869397.)).

===== Prospective diagnostic accuracy studies =====

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
((Kazda T, Bulik M, Pospisil P, Lakomy R, Smrcka M, Slampa P, Jancalek R. Advanced MRI increases the diagnostic accuracy of recurrent glioblastoma: Single institution thresholds and validation of MR spectroscopy and diffusion weighted MR imaging. Neuroimage Clin. 2016 Feb 26;11:316-321. doi: 10.1016/j.nicl.2016.02.016. PMID: 27298760; PMCID: PMC4893011.)).

===== Retrospective cohort studies =====

A study of  Lu et al. aimed to evaluate the [[predictive value]] of metabolic parameters in preoperative non-enhancing [[peritumoral region]]s (NEPTRs) for [[glioblastoma recurrence]], using multivoxel hydrogen proton magnetic resonance spectroscopy ([[Proton magnetic resonance spectroscopic imaging]]). 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
((Lu W, Feng J, Zou Y, Liu Y, Gao P, Zhao Y, Wu X, Ma H. Proton magnetic resonance spectroscopic imaging parameters in non-enhancing peritumoral regions can predict the recurrence of glioblastoma. Sci Rep. 2024 Nov 26;14(1):29258. doi: 10.1038/s41598-024-80610-z. PMID: 39587278.)).
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This study demonstrates that [[metabolic ratio]]s (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.