Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes

Diagnostic Value of PET Tracers in Differentiating Glioma Tumor Recurrence from Treatment-Related Changes: A Systematic Review and Meta-Analysis

BACKGROUND

It is often difficult to identify treatment-related changes (TRC) from tumor progression (TP) in patients with glioma, and the current application of PET scanning is expected to improve the diagnosis.

PURPOSE

We used a systematic review and meta-analysis to reveal diagnostically more promising tracers by comparing the diagnostic accuracy of different PET tracers in identifying TRC and TP in patients with glioma.

DATA SOURCES

We searched PubMed, Web of Science, and EMBASE databases, and we selected studies that used PET scans to identify TP and TRC in patients with glioma.

STUDY SELECTION

Twenty-eight studies were identified based on the set criteria. The studies involved a total of 10 different tracers and 1405 patients. TP occurred in 67.4% (947) of patients, while TRC occurred in 32.6% (458) of patients.

DATA ANALYSIS

The sensitivity, specificity, diagnostic odds ratio, positive likelihood ratio, and negative likelihood ratio of various PET tracers were calculated and summarized. Moreover, the diagnostic value of various tracers was compared.

DATA SYNTHESIS

This systematic review included 28 studies comparing 10 different PET tracers, including 18F-fluoro-deoxy-glucose FDG (18F-FDG), 11C methionine (11C -MET), 18F-fuoroethyl-L-tyrosine (18F-FET), 3,4-dihydroxy-6-18F-fluoro-L-phenylalanine (18F-FDOPA), 18F-fluorothymidine (18F-FLT), 18F-PSMA-1007, 68Ga-PSMA-11, 18F-choline (18F-CHO), 18F-fluciclovine, and [11]C-Alpha-Methyl-Tryptophan(11C-AMT). The results revealed that 11C-MET exhibited the highest diagnostic value, with an overall sensitivity and specificity of 0.89 [0.85, 0.93] and 0.91 [0.84, 0.99], respectively. Although the number of 18F-FDOPA studies is limited, it exhibited high diagnostic value, with an overall sensitivity and specificity of 1.00 [0.91, 1.00] and 0.92 [0.75, 0.99], respectively.

LIMITATIONS

Most studies consisted of small sample sizes; however, the included studies differed to some extent regarding the reference standard for the final diagnosis and the standard of care. Additionally, most selected studies were retrospective.

CONCLUSIONS

Amino acid-based tracers exhibited the highest diagnostic value in identifying TRC and TP in gliomas, with 11C-MET and 18F-FDOPA having the most notable advantages. Research on other new tracers is limited, therefore, further studies are needed to prove their diagnostic value.

Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous

The standard treatment in glioblastoma includes maximal safe resection followed by concomitant radiotherapy plus chemotherapy and adjuvant temozolomide. The first follow-up study to evaluate treatment response is performed 1 month after concomitant treatment, when contrast-enhancing regions may appear that can correspond to true progression or pseudoprogression. We retrospectively evaluated 31 consecutive patients at the first follow-up after concomitant treatment to check whether the metabolic pattern assessed with multivoxel MRS was predictive of treatment response 2 months later. We extracted the underlying metabolic patterns of the contrast-enhancing regions with a blind-source separation method and mapped them over the reference images. Pattern heterogeneity was calculated using entropy, and association between patterns and outcomes was measured with Cramér's V. We identified three distinct metabolic patterns-proliferative, necrotic, and responsive, which were associated with status 2 months later. Individually, 70% of the patients showed metabolically heterogeneous patterns in the contrast-enhancing regions. Metabolic heterogeneity was not related to the regions' size and only stable patients were less heterogeneous than the rest. Contrast-enhancing regions are also metabolically heterogeneous 1 month after concomitant treatment. This could explain the reported difficulty in finding robust pseudoprogression biomarkers.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.