Static and dynamic 18F–FET PET for the characterization of gliomas defined by IDH and 1p/19q status

Multiparametric radiomics signature for predicting molecular genotypes in adult-type diffuse gliomas utilizing 18F-FET PET/MRI

PURPOSE

This study aimed to investigate the utility of radiomic features derived from multiparametric O-(2-18 F-fluoroethyl)-L-tyrosine (18F-FET) positron emission tomography (PET)/ magnetic resonance imaging (MRI) for the prediction of molecular genotypes in adult-type diffuse gliomas.

METHODS

This retrospective study analyzed 97 adult-type diffuse glioma patients, divided into 70% training and 30% testing cohorts. Each participant underwent hybrid PET/MRI scans, including FLAIR, 3D T1-CE, apparent diffusion coefficient (ADC), and 18F-FET PET. After the multimodal images were spatially aligned, tumor segmentation was performed on the 18F-FET PET and then applied to other MRI sequences. A total of 994 radiomic features were extracted from these specified modalities. The Naive Bayesian algorithm with five-fold validation was trained to develop prediction models for the IDH, TERT, and MGMT genotypes and to calculate the radiomics score (Rad-Score). The predictive performance of these models was evaluated via receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

The combined model demonstrated superior performance compared to single-modality and MRI (FLAIR + T1-CE + ADC) models in predicting certain genotype statuses in the testing cohort (IDH AUC = 0.97, MGMT AUC = 0.86, TERT AUC = 0.90). The comparisons of the Rad-Score in multimodal models for identifying IDH, TERT, and MGMT showed significant differences (all P < 0.001). Performance of the radiomics signature surpassed that of clinical and conventional radiological factors. DCA indicated that all multimodal models provided good net clinical benefits.

CONCLUSIONS

Multiparametric 18F-FET PET/MRI comprehensively analyzes the structural, proliferative, and metabolic information of adult-type diffuse gliomas, enabling precise preoperative diagnosis of molecular genotypes. This has the potential to aid in the development of personalized clinical treatment plans.

CLINICAL TRIAL NUMBER

Not applicable.

An External, Independent Validation of an O-(2-[18F]Fluoroethyl)-l-Tyrosine PET Automatic Segmentation Network on a Single-Center, Prospective Dataset of Patients with Glioblastoma

The goal of this study was to conduct an external, independent validation of an O-(2-[18F]fluoroethyl)-l-tyrosine ([18F]FET) PET automatic segmentation network on a cohort of patients with glioblastoma. Methods: Twenty-four patients with glioblastoma were included in this study who underwent a total of 52 [18F]FET PET scans (preradiotherapy, n = 23; preradiotherapy retest, n = 9; follow-up, n = 20). Biologic tumor volume (BTV) delineation was performed by an expert nuclear medicine physician and an automatic segmentation network. Physician and automated quantitative metrics (BTV, mean tumor-to-background ratio [TBRmean], lesion SUVmean, and background SUVmean) were assessed with Pearson correlation and Bland-Altman analysis (bias, limits of agreement [LoA]). Automated and physician segmentation overlap was assessed with spatial and distance-based metrics. Results: BTV and TBRmean Pearson correlation was excellent for all time points (range, 0.92-0.98). In 2 patients with frontal lobe lesions, the network segmented the transverse sinus. Bland-Altman analysis showed network underestimation of physician-derived BTVs (absolute bias, 2.7 cm3, LoA, -13.1-18.5 cm3; relative bias, 27.9%, LoA, -95.3%-151.2%) and deviations for TBRmean were small (absolute bias, 0.03, LoA, -0.25-0.30; relative bias, 0.83%, LoA -14.27%-15.93%). Median Dice similarity coefficient, surface Dice similarity coefficient, Hausdorff distance, 95th percentile Hausdorff distance, and mean absolute surface distance were 0.83, 0.95, 10.94 mm, 3.62 mm, and 0.88 mm, respectively. Conclusion: Automated quantitative analysis was highly correlated with physician assessment; however, volume underestimation and erroneous segmentations may impact radiotherapy treatment planning and response assessment. Further training on a representative local dataset would likely be required for multicenter implementation.

Clinical Value of 18 F-(2S,4R)-4-Fluoroglutamine PET/CT in Glioma

PROPOSE

The aim of this study was to evaluate the clinical application value of 18 F-FGln PET/CT in glioma.

PATIENTS AND METHODS

Patients with suspected gliomas by MRI were included in this study. Static and/or dynamic brain 18 F-FGln PET/CT was performed. The PET parameters SUV max , SUV mean , MTV, and TLG were evaluated.

RESULTS

Twenty-three patients were included in the analysis. Nineteen of 23 patients were positive for 18 F-FGln PET. The SUV max of high- and low-grade gliomas were 4.75 ± 2.21 and 1.00 ± 0.66 ( P < 0.001), respectively. FGln-PET SUV max , SUV mean , and TLG all showed statistically significant correlations with glioma grade, with correlation coefficients ( r ) of 0.667 ( P < 0.001), 0.693 ( P < 0.001), and 0.487 ( P = 0.021), respectively. Additionally, the SUV max , SUV mean , and TLG exhibited higher distinguishing performance for glioma grade by receiver operating characteristic curve analysis. The areas under the receiver operating characteristic curve of SUV max , SUV mean , and TLG were 0.976 (95% confidence interval [CI], 0.918-1) ( P = 0.002), 0.976 (95% CI, 0.918-1) ( P = 0.002), and 0.835 (95% CI, 0.628-1.000) ( P = 0.026), respectively. For glioma isocitrate dehydrogenase (IDH) mutation status, the SUV max of IDH wildtype and mutant glioma were 2.95 ± 1.99 and 6.13 ± 2.16 ( P = 0.005), respectively. The SUV mean and SUV max had good-to-satisfactory performance for IDH status with the area under the receiver operating characteristic curve of SUV max and SUV mean of 0.885 (95% CI, 0.734-1.000) ( P = 0.009) and 0.942 (95% CI, 0.828-1) ( P = 0.002).

CONCLUSIONS

Although we do not assert that 18 F-FGln PET/CT imaging is satisfactory in the differential diagnosis of glioma, we revealed its potential for identifying the stage of gliomas and the IDH mutation status and propose that glutamine-based PET imaging enables the assessment of metabolic nutrient uptake of gliomas to assist clinical diagnosis and treatment of patients.

Who will benefit from vorasidenib? Review of data from the literature and open questions

The clinical efficacy of isocitrate dehydrogenase (IDH) inhibitors in the treatment of patients with grade 2 IDH-mutant (mIDH) gliomas is a significant therapeutic advancement in neuro-oncology. It expands treatment options beyond traditional radiation therapy and cytotoxic chemotherapy, which may lead to significant long-term neurotoxic effects while extending patient survival. The INDIGO study demonstrated that vorasidenib, a pan-mIDH inhibitor, improved progression-free survival for patients with grade 2 mIDH gliomas following surgical resection or biopsy compared to placebo and was well tolerated. However, these encouraging results leave a wake of unanswered questions: Will higher-grade mIDH glioma patients benefit? When is the appropriate timing to start and stop treatment? Where does this new treatment option fit in with other treatment modalities? In this study, we review the limited data available to start addressing these questions, provide a framework of how to discuss these gaps with current patients, and highlight what is needed from the neuro-oncology community for more definitive answers.

Pre-operative dual-time-point [18F]FET PET differentiates CDKN2A/B loss and PIK3CA mutation status in adult-type diffuse glioma: a single-center prospective study

PURPOSE

While [18F]FET PET plays a complementary role in glioma imaging, it needs to be more comprehensively understood for improved characterization of glioma prior to surgery given the evolving landscape of molecular neuropathology. Thus, we investigated the utility of pre-operative dual-time-point [18F]FET PET in correlation with next-generation sequencing (NGS) data in patients with adult-type diffuse glioma (ADG).

METHODS

Adult patients who were suspected to have primary glioma were prospectively recruited between June 2021 and January 2024. They underwent pre-operative dual-time-point static PET/CT at 20 min (early) and 80 min (delay) after [18F]FET injection. Semi-quantitative parameters of the hottest lesion (SUVmax) of tumour and the hottest lesion-to-normal brain ratio (TBRmax) were assessed from each summed image. Furthermore, the percentage changes (△) of SUVmax and TBRmax between two images were calculated. Histopathology of glioma was determined according to the 2021 WHO classification and NGS data.

RESULTS

This study investigated a dozen genes in 76 patients, of whom 51 had isocitrate dehydrogenase (IDH)-wild-type glioblastoma, 13 had IDH-mutant astrocytoma, and 12 had IDH-mutant oligodendroglioma. Every tumour was [18F]FET-avid having TBRmax more than 1.6. Patients with CDKN2A/B loss had significantly higher values of SUVmax (5.7 ± 1.6 vs. 4.7 ± 1.3, p = 0.004; 5.0 ± 1.4 vs. 4.4 ± 1.2, p = 0.026) and TBRmax (6.5 ± 1.8 vs. 5.1 ± 1.7, p = 0.001; 5.3 ± 1.5 vs. 4.3 ± 1.3, p = 0.004) in both scans than patients without CDKN2A/B loss, even after adjustment for age, MRI enhancement, tumor grade and type of pathology. Furthermore, patients with PIK3CA mutation (16.2 ± 11.8 vs. 6.7 ± 11.6, p = 0.007) had significantly higher △SUVmax than patients without PIK3CA mutation, even after adjustment for age, MRI enhancement, tumor grade, and type of pathology.

CONCLUSION

Among the dozen genes investigated in this prospective study in patients with ADG, we found out that CDKN2A/B loss and PIK3CA mutation status could be differentiated by pre-operative dual-time-point [18F]FET PET/CT.

The role of amino acid PET in radiotherapy target volume delineation for adult-type diffuse gliomas: A review of the literature

PURPOSE

To summarise existing literature examining amino acid positron emission tomography (AA-PET) for radiotherapy target volume delineation in patients with gliomas.

METHODS

Systematic search of MEDLINE and EMBASE databases.

RESULTS

Twenty studies met inclusion criteria. Studies comparing MRI- and AA-PET- derived target volumes consistently found these to be complementary. Across studies, AA-PET was a strong predictor of the site of subsequent relapse. In studies examining AA-PET-guided radiotherapy at standard doses, including one study using reduced margins, survival outcomes were similar to historical cohorts whose volumes were generated using MRI alone. Four prospective single-arm trials examining AA-PET-guided dose-escalated radiotherapy reported mixed results. The two trials that used both a higher biologically-effective dose and boost-volumes defined using both MRI and AA-PET reported promising outcomes.

CONCLUSION

AA-PET is a promising complementary tool to MRI for radiotherapy target volume delineation, with potential benefits requiring further validation including margin reduction and facilitation of dose-escalation.

PET imaging of gliomas: Status quo and quo vadis?

PET imaging, particularly using amino acid tracers, has become a valuable adjunct to anatomical MRI in the clinical management of patients with glioma. Collaborative international efforts have led to the development of clinical and technical guidelines for PET imaging in gliomas. The increasing readiness of statutory health insurance agencies, especially in European countries, to reimburse amino acid PET underscores its growing importance in clinical practice. Integrating artificial intelligence and radiomics in PET imaging of patients with glioma may significantly improve tumor detection, segmentation, and response assessment. Efforts are ongoing to facilitate the clinical translation of these techniques. Considerable progress in computer technology developments (eg quantum computers) may be helpful to accelerate these efforts. Next-generation PET scanners, such as long-axial field-of-view PET/CT scanners, have improved image quality and body coverage and therefore expanded the spectrum of indications for PET imaging in Neuro-Oncology (eg PET imaging of the whole spine). Encouraging results of clinical trials in patients with glioma have prompted the development of PET tracers directing therapeutically relevant targets (eg the mutant isocitrate dehydrogenase) for novel anticancer agents in gliomas to improve response assessment. In addition, the success of theranostics for the treatment of extracranial neoplasms such as neuroendocrine tumors and prostate cancer has currently prompted efforts to translate this approach to patients with glioma. These advancements highlight the evolving role of PET imaging in Neuro-Oncology, offering insights into tumor biology and treatment response, thereby informing personalized patient care. Nevertheless, these innovations warrant further validation in the near future.

A New Tool for Extracting Static and Dynamic Parameters from [18F]F-DOPA PET/CT in Pediatric Gliomas

Background/Objectives: PET imaging with [18F]F-DOPA has demonstrated high potential for the evaluation and management of pediatric brain gliomas. Manual extraction of PET parameters is time-consuming, lacks reproducibility, and varies with operator experience. Methods: In this study, we tested whether a semi-automated image processing framework could overcome these limitations. Pediatric patients with available static and/or dynamic [18F]F-DOPA PET studies were evaluated retrospectively. We developed a Python software to automate clinical index calculations, including preprocessing to delineate tumor volumes from structural MRI, accounting for lesions with low [18F]F-DOPA uptake. A total of 73 subjects with treatment-naïve low- and high-grade gliomas, who underwent brain MRI within two weeks of [18F]F-DOPA PET, were included and analyzed. Static analysis was conducted on all subjects, while dynamic analysis was performed on 32 patients. Results: For 68 subjects, the Intraclass Correlation Coefficient for T/S between manual and ground truth segmentation was 0.91. Using our tool, ICC improved to 0.94. Our method demonstrated good reproducibility in extracting static tumor-to-striatum ratio (p = 0.357); however, significant differences were observed in tumor slope (p < 0.05). No significant differences were found in time-to-peak (p = 0.167) and striatum slope (p = 0.36). Conclusions: Our framework aids in analyzing [18F]F-DOPA PET images of pediatric brain tumors by automating clinical score extraction, simplifying segmentation and Time Activity Curve extraction, reducing user variability, and enhancing reproducibility.

Contribution of [18F]FET PET in the Management of Gliomas, from Diagnosis to Follow-Up: A Review

Gliomas, the most common type of primary malignant brain tumors in adults, pose significant challenges in diagnosis and management due to their heterogeneity and potential aggressiveness. This review evaluates the utility of O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) positron emission tomography (PET), a promising imaging modality, to enhance the clinical management of gliomas. We reviewed 82 studies involving 4657 patients, focusing on the application of [18F]FET in several key areas: diagnosis, grading, identification of IDH status and presence of oligodendroglial component, guided resection or biopsy, detection of residual tumor, guided radiotherapy, detection of malignant transformation in low-grade glioma, differentiation of recurrence versus treatment-related changes and prognostic factors, and treatment response evaluation. Our findings confirm that [18F]FET helps delineate tumor tissue, improves diagnostic accuracy, and aids in therapeutic decision-making by providing crucial insights into tumor metabolism. This review underscores the need for standardized parameters and further multicentric studies to solidify the role of [18F]FET PET in routine clinical practice. By offering a comprehensive overview of current research and practical implications, this paper highlights the added value of [18F]FET PET in improving management of glioma patients from diagnosis to follow-up.

Preparation and Preclinical Evaluation of 18F-Labeled Olutasidenib Derivatives for Non-Invasive Detection of Mutated Isocitrate Dehydrogenase 1 (mIDH1)

Mutations of isocitrate dehydrogenase 1 (IDH1) are key biomarkers for glioma classification, but current methods for detection of mutated IDH1 (mIDH1) require invasive tissue sampling and cannot be used for longitudinal studies. Positron emission tomography (PET) imaging with mIDH1-selective radioligands is a promising alternative approach that could enable non-invasive assessment of the IDH status. In the present work, we developed efficient protocols for the preparation of four 18F-labeled derivatives of the mIDH1-selective inhibitor olutasidenib. All four probes were characterized by cellular uptake studies with U87 glioma cells harboring a heterozygous IDH1 mutation (U87-mIDH) and the corresponding wildtype cells (U87-WT). In addition, the most promising probe was evaluated by PET imaging in healthy mice and mice bearing subcutaneous U87-mIDH and U87-WT tumors. Although all four probes inhibited mIDH1 with variable potencies, only one of them ([18F]mIDH-138) showed significantly higher in vitro uptake into U87-mIDH compared to U87-WT cells. In addition, PET imaging with [18F]mIDH-138 in mice demonstrated good in vivo stability and low non-specific uptake of the probe, but also revealed significantly higher uptake into U87-WT compared to U87-mIDH tumors. Finally, application of a two-tissue compartment model (2TCM) to the PET data indicated that preferential tracer uptake into U87-WT tumors results from higher specific binding rather than from differences in tracer perfusion. In conclusion, these results corroborate recent findings that mIDH1-selective inhibition may not directly correlate with mIDH1-selective target engagement and indicate that in vivo engagement of wildtype and mutated IDH1 may be governed by factors that are not faithfully reproduced by in vitro assays, both of which could complicate development of PET probes.

Radiosynthesis and biological evaluation of [18F]AG-120 for PET imaging of the mutant isocitrate dehydrogenase 1 in glioma

Glioma are clinically challenging tumors due to their location and invasiveness nature, which often hinder complete surgical resection. The evaluation of the isocitrate dehydrogenase mutation status has become crucial for effective patient stratification. Through a transdisciplinary approach, we have developed an 18F-labeled ligand for non-invasive assessment of the IDH1R132H variant by using positron emission tomography (PET) imaging. In this study, we have successfully prepared diastereomerically pure [18F]AG-120 by copper-mediated radiofluorination of the stannyl precursor 6 on a TRACERlab FX2 N radiosynthesis module. In vitro internalization studies demonstrated significantly higher uptake of [18F]AG-120 in U251 human high-grade glioma cells with stable overexpression of mutant IDH1 (IDH1R132H) compared to their wild-type IDH1 counterpart (0.4 vs. 0.013% applied dose/µg protein at 120 min). In vivo studies conducted in mice, exhibited the excellent metabolic stability of [18F]AG-120, with parent fractions of 85% and 91% in plasma and brain at 30 min p.i., respectively. Dynamic PET studies with [18F]AG-120 in naïve mice and orthotopic glioma rat model reveal limited blood-brain barrier permeation along with a low uptake in the brain tumor. Interestingly, there was no significant difference in uptake between mutant IDH1R132H and wild-type IDH1 tumors (tumor-to-blood ratio[40-60 min]: ~1.7 vs. ~1.3). In conclusion, our preclinical evaluation demonstrated a target-specific internalization of [18F]AG-120 in vitro, a high metabolic stability in vivo in mice, and a slightly higher accumulation of activity in IDH1R132H-glioma compared to IDH1-glioma. Overall, our findings contribute to advancing the field of molecular imaging and encourage the evaluation of [18F]AG-120 to improve diagnosis and management of glioma and other IDH1R132H-related tumors.

Tata Memorial Centre Evidence Based Use of Nuclear medicine diagnostic and treatment modalities in cancer

ABSTRACT

PET/CT and radioisotope therapy are diagnostic and therapeutic arms of Nuclear Medicine, respectively. With the emergence of better technology, PET/CT has become an accessible modality. Diagnostic tracers exploring disease-specific targets has led the clinicians to look beyond FDG PET. Moreover, with the emergence of theranostic pairs of radiopharmaceuticals, radioisotope therapy is gradually making it's way into treatment algorithm of common cancers in India. We therefore would like to discuss in detail the updates in PET/CT imaging and radionuclide therapy and generate a consensus-driven evidence based document which would guide the practitioners of Oncology.

18F-Fluoroethyl-L Tyrosine Positron Emission Tomography Radiomics in the Differentiation of Treatment-Related Changes from Disease Progression in Patients with Glioblastoma

The follow-up of glioma patients after therapeutic intervention remains a challenging topic, as therapy-related changes can emulate true progression in contrast-enhanced magnetic resonance imaging. 18F-fluoroethyl-tyrosine (18F-FET) is a radiopharmaceutical that accumulates in glioma cells due to an increased expression of L-amino acid transporters and, contrary to gadolinium, does not depend on blood-brain barrier disruption to reach tumoral cells. It has demonstrated a high diagnostic value in the differentiation of tumoral viability and pseudoprogression or any other therapy-related changes, especially when combining traditional visual analysis with modern radiomics. In this review, we aim to cover the potential role of 18F-FET positron emission tomography in everyday clinical practice when applied to the follow-up of patients after the first therapeutical intervention, early response evaluation, and the differential diagnosis between therapy-related changes and progression.

Delineation and agreement of FET PET biological volumes in glioblastoma: results of the nuclear medicine credentialing program from the prospective, multi-centre trial evaluating FET PET In Glioblastoma (FIG) study-TROG 18.06

PURPOSE

The O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET in Glioblastoma (FIG) trial is an Australian prospective, multi-centre study evaluating FET PET for glioblastoma patient management. FET PET imaging timepoints are pre-chemoradiotherapy (FET1), 1-month post-chemoradiotherapy (FET2), and at suspected progression (FET3). Before participant recruitment, site nuclear medicine physicians (NMPs) underwent credentialing of FET PET delineation and image interpretation.

METHODS

Sites were required to complete contouring and dynamic analysis by ≥ 2 NMPs on benchmarking cases (n = 6) assessing biological tumour volume (BTV) delineation (3 × FET1) and image interpretation (3 × FET3). Data was reviewed by experts and violations noted. BTV definition includes tumour-to-background ratio (TBR) threshold of 1.6 with crescent-shaped background contour in the contralateral normal brain. Recurrence/pseudoprogression interpretation (FET3) required assessment of maximum TBR (TBRmax), dynamic analysis (time activity curve [TAC] type, time to peak), and qualitative assessment. Intraclass correlation coefficient (ICC) assessed volume agreement, coefficient of variation (CoV) compared maximum/mean TBR (TBRmax/TBRmean) across cases, and pairwise analysis assessed spatial (Dice similarity coefficient [DSC]) and boundary agreement (Hausdorff distance [HD], mean absolute surface distance [MASD]).

RESULTS

Data was accrued from 21 NMPs (10 centres, n ≥ 2 each) and 20 underwent review. The initial pass rate was 93/119 (78.2%) and 27/30 requested resubmissions were completed. Violations were found in 25/72 (34.7%; 13/12 minor/major) of FET1 and 22/74 (29.7%; 14/8 minor/major) of FET3 reports. The primary reasons for resubmission were as follows: BTV over-contour (15/30, 50.0%), background placement (8/30, 26.7%), TAC classification (9/30, 30.0%), and image interpretation (7/30, 23.3%). CoV median and range for BTV, TBRmax, and TBRmean were 21.53% (12.00-30.10%), 5.89% (5.01-6.68%), and 5.01% (3.37-6.34%), respectively. BTV agreement was moderate to excellent (ICC = 0.82; 95% CI, 0.63-0.97) with good spatial (DSC = 0.84 ± 0.09) and boundary (HD = 15.78 ± 8.30 mm; MASD = 1.47 ± 1.36 mm) agreement.

CONCLUSION

The FIG study credentialing program has increased expertise across study sites. TBRmax and TBRmean were robust, with considerable variability in BTV delineation and image interpretation observed.

Evaluation of isocitrate dehydrogenase mutation in 2021 world health organization classification grade 3 and 4 glioma adult-type diffuse gliomas with 18F-fluoromisonidazole PET

PURPOSE

This study aimed to investigate the uptake characteristics of 18F-fluoromisonidazole (FMISO), in mutant-type isocitrate dehydrogenase (IDH-mutant, grade 3 and 4) and wild-type IDH (IDH-wildtype, grade 4) 2021 WHO classification adult-type diffuse gliomas.

MATERIALS AND METHODS

Patients with grade 3 and 4 adult-type diffuse gliomas (n = 35) were included in this prospective study. After registering 18F-FMISO PET and MR images, standardized uptake value (SUV) and apparent diffusion coefficient (ADC) were evaluated in hyperintense areas on fluid-attenuated inversion recovery (FLAIR) imaging (HIA), and in contrast-enhanced tumors (CET) by manually placing 3D volumes of interest. Relative SUVmax (rSUVmax) and SUVmean (rSUVmean), 10th percentile of ADC (ADC10pct), mean ADC (ADCmean) were measured in HIA and CET, respectively.

RESULTS

rSUVmean in HIA and rSUVmean in CET were significantly higher in IDH-wildtype than in IDH-mutant (P = 0.0496 and 0.03, respectively). The combination of FMISO rSUVmean in HIA and ADC10pct in CET, that of rSUVmax and ADC10pct in CET, that of rSUVmean in HIA and ADCmean in CET, were able to differentiate IDH-mutant from IDH-wildtype (AUC 0.80). When confined to astrocytic tumors except for oligodendroglioma, rSUVmax, rSUVmean in HIA and rSUVmean in CET were higher for IDH-wildtype than for IDH-mutant, but not significantly (P = 0.23, 0.13 and 0.14, respectively). The combination of FMISO rSUVmean in HIA and ADC10pct in CET was able to differentiate IDH-mutant (AUC 0.81).

CONCLUSION

PET using 18F-FMISO and ADC might provide a valuable tool for differentiating between IDH mutation status of 2021 WHO classification grade 3 and 4 adult-type diffuse gliomas.

Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using 18F-FET PET

Molecular markers are of increasing importance for classifying, treating, and determining the prognosis for central nervous system tumors. Isocitrate dehydrogenase (IDH) is a critical regulator of glucose and amino acid metabolism. Our objective was to investigate metabolic reprogramming of glioma using compartmental uptake (CU) characteristics in O-(2-18F-fluoroethyl)-l-tyrosine (FET) PET and to evaluate its diagnostic potential for IDH genotyping. Methods: Between 2017 and 2022, patients with confirmed glioma were preoperatively investigated using static 18F-FET PET. Metabolic tumor volume (MTV), MTV for 60%-100% uptake (MTV60), and T2-weighted and contrast-enhancing lesion volumes were automatically segmented using U-Net neural architecture and isocontouring. Volume intersections were determined using the Dice coefficient. Uptake characteristics were determined for metabolically defined compartments (central [80%-100%] and peripheral [60%-75%] areas of 18F-FET uptake). CU ratio was defined as the fraction between the peripheral and central compartments. Mean target-to-background ratio was calculated. Comparisons were performed using parametric and nonparametric tests. Receiver-operating-characteristic curves, regression, and correlation were used for statistical analysis. Results: In total, 52 participants (male, 27, female, 25; mean age ± SD, 51 ± 16 y) were evaluated. MTV60 was greater and distinct from contrast-enhancing lesion volume (P = 0.046). IDH-mutated tumors presented a greater volumetric CU ratio and SUV CU ratio than IDH wild-type tumors (P < 0.05). Volumetric CU ratio determined IDH genotype with excellent diagnostic performance (area under the curve [AUC], 0.88; P < 0.001) at more than 5.49 (sensitivity, 86%, specificity, 90%), because IDH-mutated tumors presented a greater peripheral metabolic compartment than IDH wild-type tumors (P = 0.045). MTV60 and MTV were not suitable for IDH classification (P > 0.05). SUV CU ratio (AUC, 0.72; P = 0.005) and target-to-background ratio (AUC, 0.68; P = 0.016) achieved modest diagnostic performance-inferior to the volumetric CU ratio. Furthermore, the classification of loss of heterozygosity of chromosomes 1p and 19q (AUC, 0.75; P = 0.019), MGMT promoter methylation (AUC, 0.70; P = 0.011), and ATRX loss (AUC, 0.73; P = 0.004) by amino acid PET was evaluated. Conclusion: We proposed parametric 18F-FET PET as a noninvasive metabolic biomarker for the evaluation of CU characteristics, which differentiated IDH genotype with excellent diagnostic performance, establishing a critical association between spatial metabolic heterogeneity, mitochondrial tricarboxylic acid cycle, and genomic features with critical implications for clinical management and the diagnostic workup of patients with central nervous system cancer.

Differentiation of astrocytoma between grades II and III using a combination of methionine positron emission tomography and magnetic resonance spectroscopy

Objective

This study aimed to establish a method for differentiating between grades II and III astrocytomas using preoperative imaging.

Methods

We retrospectively analyzed astrocytic tumors, including 18 grade II astrocytomas (isocitrate dehydrogenase (IDH)-mutant: IDH-wildtype = 8:10) and 56 grade III anaplastic astrocytomas (37:19). We recorded the maximum methionine (MET) uptake ratios (tumor-to-normal: T/N) on positron emission tomography (PET) and three MRS peak ratios: choline (Cho)/creatine (Cr), N-acetyl aspartate (NAA)/Cr, and Cho/NAA, between June 2015 and June 2020. We then evaluated the cut-off values to differentiate between grades II and III. We compared the grading results between contrast enhancement effects on MR and combinational diagnostic methods (CDM) on a scatter chart using the cutoff values of the T/N ratio and MRS parameters.

Results

The IDH-mutant group showed significant differences in the Cho/NAA ratio between grades II and III using univariate analysis; however, multiple regression analysis results negated this. The IDH-wildtype group showed no significant differences between the groups. Contrast enhancement effects also showed no significant differences in IDH status. Accordingly, regardless of the IDH status, no statistically independent factors differentiated between grades II and III. However, CDMs showed higher sensitivity and negative predictive value in distinguishing them than MRI contrast examinations for both IDH statuses. We demonstrated a significantly higher diagnostic rate of grade III than of grade II with CDM, which was more striking in the IDH-mutant group than in the wild-type group.

Conclusions

CDM could be valuable in differentiating between grade II and III astrocytic tumors.

Risk Estimation in Non-Enhancing Glioma: Introducing a Clinical Score

The preoperative grading of non-enhancing glioma (NEG) remains challenging. Herein, we analyzed clinical and magnetic resonance imaging (MRI) features to predict malignancy in NEG according to the 2021 WHO classification and developed a clinical score, facilitating risk estimation. A discovery cohort (2012-2017, n = 72) was analyzed for MRI and clinical features (T2/FLAIR mismatch sign, subventricular zone (SVZ) involvement, tumor volume, growth rate, age, Pignatti score, and symptoms). Despite a "low-grade" appearance on MRI, 81% of patients were classified as WHO grade 3 or 4. Malignancy was then stratified by: (1) WHO grade (WHO grade 2 vs. WHO grade 3 + 4) and (2) molecular criteria (IDH^mut WHO grade 2 + 3 vs. IDH^wt glioblastoma + IDH^mut astrocytoma WHO grade 4). Age, Pignatti score, SVZ involvement, and T2/FLAIR mismatch sign predicted malignancy only when considering molecular criteria, including IDH mutation and CDKN2A/B deletion status. A multivariate regression confirmed age and T2/FLAIR mismatch sign as independent predictors (p = 0.0009; p = 0.011). A "risk estimation in non-enhancing glioma" (RENEG) score was derived and tested in a validation cohort (2018-2019, n = 40), yielding a higher predictive value than the Pignatti score or the T2/FLAIR mismatch sign (AUC of receiver operating characteristics = 0.89). The prevalence of malignant glioma was high in this series of NEGs, supporting an upfront diagnosis and treatment approach. A clinical score with robust test performance was developed that identifies patients at risk for malignancy.

Mutated Isocitrate Dehydrogenase (mIDH) as Target for PET Imaging in Gliomas

Gliomas are the most common primary brain tumors in adults. A diffuse infiltrative growth pattern and high resistance to therapy make them largely incurable, but there are significant differences in the prognosis of patients with different subtypes of glioma. Mutations in isocitrate dehydrogenase (IDH) have been recognized as an important biomarker for glioma classification and a potential therapeutic target. However, current clinical methods for detecting mutated IDH (mIDH) require invasive tissue sampling and cannot be used for follow-up examinations or longitudinal studies. PET imaging could be a promising approach for non-invasive assessment of the IDH status in gliomas, owing to the availability of various mIDH-selective inhibitors as potential leads for the development of PET tracers. In the present review, we summarize the rationale for the development of mIDH-selective PET probes, describe their potential applications beyond the assessment of the IDH status and highlight potential challenges that may complicate tracer development. In addition, we compile the major chemical classes of mIDH-selective inhibitors that have been described to date and briefly consider possible strategies for radiolabeling of the most promising candidates. Where available, we also summarize previous studies with radiolabeled analogs of mIDH inhibitors and assess their suitability for PET imaging in gliomas.

A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon's Perspective

Amino acid PET imaging has been used for a few years in the clinical and surgical management of gliomas with satisfactory results in diagnosis and grading for surgical and radiotherapy planning and to differentiate recurrences. Biological tumor volume (BTV) provides more meaningful information than standard MR imaging alone and often exceeds the boundary of the contrast-enhanced nodule seen in MRI. Since a gross total resection reflects the resection of the contrast-enhanced nodule and the majority of recurrences are at a tumor's margins, an integration of PET imaging during resection could increase PFS and OS. A systematic review of the literature searching for "PET" [All fields] AND "glioma" [All fields] AND "resection" [All fields] was performed in order to investigate the diffusion of integration of PET imaging in surgical practice. Integration in a neuronavigation system and intraoperative use of PET imaging in the primary diagnosis of adult high-grade gliomas were among the criteria for article selection. Only one study has satisfied the inclusion criteria, and a few more (13) have declared to use multimodal imaging techniques with the integration of PET imaging to intentionally perform a biopsy of the PET uptake area. Despite few pieces of evidence, targeting a biologically active area in addition to other tools, which can help intraoperatively the neurosurgeon to increase the amount of resected tumor, has the potential to provide incremental and complementary information in the management of brain gliomas. Since supramaximal resection based on the extent of MRI FLAIR hyperintensity resulted in an advantage in terms of PFS and OS, PET-based biological tumor volume, avoiding new neurological deficits, deserves further investigation.

Multiparametric Characterization of Intracranial Gliomas Using Dynamic [18F]FET-PET and Magnetic Resonance Spectroscopy

Both static and dynamic O-(2-[18F]fluoroethyl)-l-tyrosine-(FET)-PET and 1H magnetic resonance spectroscopy (MRS) are useful tools for grading and prognostication in gliomas. However, little is known about the potential of multimodal imaging comprising both procedures. We therefore acquired NAA/Cr and Cho/Cr ratios in multi-voxel MRS as well as FET-PET parameters in 67 glioma patients and determined multiparametric parameter combinations. Using receiver operating characteristics, differentiation between low-grade and high-grade glioma was possible by static FET-PET (area under the curve (AUC) 0.86, p = 0.001), time-to-peak (TTP; AUC 0.79, p = 0.049), and using the Cho/Cr ratio (AUC 0.72, p = 0.039), while the multimodal analysis led to improved discrimination with an AUC of 0.97 (p = 0.001). In order to distinguish glioblastoma from non-glioblastoma, MRS (NAA/Cr ratio, AUC 0.66, p = 0.031), and dynamic FET-PET (AUC 0.88, p = 0.001) were superior to static FET imaging. The multimodal analysis increased the accuracy with an AUC of 0.97 (p < 0.001). In the survival analysis, PET parameters, but not spectroscopy, were significantly correlated with overall survival (OS, static PET p = 0.014, TTP p = 0.012), still, the multiparametric analysis, including MRS, was also useful for the prediction of OS (p = 0.002). In conclusion, FET-PET and MRS provide complementary information to better characterize gliomas before therapy, which is particularly interesting with respect to the increasing use of hybrid PET/MRI for brain tumors.

Two Decades of Brain Tumour Imaging with O-(2-[18F]fluoroethyl)-L-tyrosine PET: The Forschungszentrum Jülich Experience

Simple Summary

PET using radiolabelled amino acids has become an essential tool for diagnosing brain tumours in addition to MRI. O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) is one of the most successful tracers in the field. We analysed our database of 6534 FET PET examinations regarding the diagnostic needs and preferences of the referring physicians for FET PET in the clinical decision-making process. The demand for FET PET increased considerably in the last decade, especially for differentiating tumour progress from treatment-related changes in gliomas. Accordingly, referring physicians rated the diagnostics of recurrent glioma and recurrent brain metastases as the most relevant indication for FET PET. The analysis and survey results confirm the high relevance of FET PET in the clinical diagnosis of brain tumours and support the need for approval for routine use.

Abstract

O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) is a widely used amino acid tracer for positron emission tomography (PET) imaging of brain tumours. This retrospective study and survey aimed to analyse our extensive database regarding the development of FET PET investigations, indications, and the referring physicians’ rating concerning the role of FET PET in the clinical decision-making process. Between 2006 and 2019, we performed 6534 FET PET scans on 3928 different patients against a backdrop of growing demand for FET PET. In 2019, indications for the use of FET PET were as follows: suspected recurrent glioma (46%), unclear brain lesions (20%), treatment monitoring (19%), and suspected recurrent brain metastasis (13%). The referring physicians were neurosurgeons (60%), neurologists (19%), radiation oncologists (11%), general oncologists (3%), and other physicians (7%). Most patients travelled 50 to 75 km, but 9% travelled more than 200 km. The role of FET PET in decision-making in clinical practice was evaluated by a questionnaire consisting of 30 questions, which was filled out by 23 referring physicians with long experience in FET PET. Fifty to seventy per cent rated FET PET as being important for different aspects of the assessment of newly diagnosed gliomas, including differential diagnosis, delineation of tumour extent for biopsy guidance, and treatment planning such as surgery or radiotherapy, 95% for the diagnosis of recurrent glioma, and 68% for the diagnosis of recurrent brain metastases. Approximately 50% of the referring physicians rated FET PET as necessary for treatment monitoring in patients with glioma or brain metastases. All referring physicians stated that the availability of FET PET is essential and that it should be approved for routine use. Although the present analysis is limited by the fact that only physicians who frequently referred patients for FET PET participated in the survey, the results confirm the high relevance of FET PET in the clinical diagnosis of brain tumours and support the need for its approval for routine use.

The Use of 18F-FET-PET-MRI in Neuro-Oncology: The Best of Both Worlds—A Narrative Review

Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up.

MGMT promoter methylation status shows no effect on [18F]FET uptake and CBF in gliomas: a stereotactic image-based histological validation study

OBJECTIVES

To investigate the effects of O⁶-methylguanine DNA methyltransferase (MGMT) promoter methylation status of gliomas on O-(2-¹⁸F-fluoroethyl)-L-tyrosine ([¹⁸F]FET) uptake and cerebral blood flow (CBF) of arterial spin labeling (ASL), evaluated by hybrid PET/MR. Stereotactic biopsy was used to validate the findings.

METHODS

A set of whole tumor and reference volumes of interest (VOIs) based on PET/FLAIR imaging were delineated and transferred to the corresponding [¹⁸F]FET PET and CBF maps in 57 patients with newly diagnosed gliomas. The mean and max tumor-to-brain ratio (TBR) and normalized CBF (nCBF) were calculated. The predictive efficacy of [¹⁸F]FET PET and CBF in determining MGMT promoter methylation status of glioma were evaluated by whole tumor analysis and stereotactic biopsy. The correlation between PET/MR parameters and MGMT promoter methylation were analyzed using histological specimens acquired from multiple stereotactic biopsies.

RESULTS

Based on the analysis of whole tumor volume and biopsy site, TBRmean, TBRmax, nCBFmean, and nCBFmax showed no statistically significant differences between gliomas with and without MGMT promoter methylation (all p > 0.05). Furthermore, stereotactic biopsy demonstrated that TBRmean, TBRmax, nCBFmean, and nCBFmax showed no correlation with MGMT promoter methylation (r = -0.117, p = 0.579; r = -0.161, p = 0.443; r = -0.271, p = 0.191; r = -0.300, p = 0.145; respectively).

CONCLUSIONS

MGMT promoter methylation status shows no effect on [¹⁸F]FET uptake and CBF of ASL in gliomas. Stereotactic biopsy validates it and further reveals there is no correlation of [¹⁸F]FET PET uptake and CBF with the percentages of MGMT promoter methylation.

KEY POINTS

• Based on whole tumor VOI assessment, MGMT promoter methylation status shows no effect on [¹⁸F]FET uptake and CBF of ASL in gliomas. • For WHO grade IV glioblastomas, [¹⁸F]FET PET and ASL parameters based on hybrid PET/MR fail to predict the MGMT promoter methylation status. • Stereotactic image-based histology reveals that there is no correlation of [¹⁸F]FET PET uptake and CBF with the status and percentages of MGMT promoter methylation in gliomas.

PET Imaging in Neuro-Oncology: An Update and Overview of a Rapidly Growing Area

Simple Summary

Positron emission tomography (PET) is a functional imaging technique which plays an increasingly important role in the management of brain tumors. Owing different radiotracers, PET allows to image different metabolic aspects of the brain tumors. This review outlines currently available PET radiotracers and their respective indications in neuro-oncology. It specifically focuses on the investigation of gliomas, meningiomas, primary central nervous system lymphomas as well as brain metastases. Recent advances in the production of PET radiotracers, image analyses and translational applications to peptide radionuclide receptor therapy, which allow to treat brain tumors with radiotracers, are also discussed. The objective of this review is to provide a comprehensive overview of PET imaging’s potential in neuro-oncology as an adjunct to brain magnetic resonance imaging (MRI).

Abstract

PET plays an increasingly important role in the management of brain tumors. This review outlines currently available PET radiotracers and their respective indications. It specifically focuses on ¹⁸F-FDG, amino acid and somatostatin receptor radiotracers, for imaging gliomas, meningiomas, primary central nervous system lymphomas as well as brain metastases. Recent advances in radiopharmaceuticals, image analyses and translational applications to therapy are also discussed. The objective of this review is to provide a comprehensive overview of PET imaging’s potential in neuro-oncology as an adjunct to brain MRI for all medical professionals implicated in brain tumor diagnosis and care.

18F-FDOPA PET for the Noninvasive Prediction of Glioma Molecular Parameters: A Radiomics Study

The assessment of gliomas by 18F-FDOPA PET imaging as an adjunct to MRI showed high performance by combining static and dynamic features to noninvasively predict the isocitrate dehydrogenase (IDH) mutations and the 1p/19q codeletion, which the World Health Organization classified as significant parameters in 2016. The current study evaluated whether other 18F-FDOPA PET radiomics features further improve performance and the contributions of each of these features to performance. Methods: Our study included 72 retrospectively selected, newly diagnosed glioma patients with 18F-FDOPA PET dynamic acquisitions. A set of 114 features, including conventional static features and dynamic features, as well as other radiomics features, were extracted and machine-learning models trained to predict IDH mutations and the 1p/19q codeletion. Models were based on a machine-learning algorithm built from stable, relevant, and uncorrelated features selected by hierarchic clustering followed by a bootstrapped feature selection process. Models were assessed by comparing area under the curve using a nested cross-validation approach. Feature importance was assessed using Shapley additive explanations values. Results: The best models were able to predict IDH mutations (logistic regression with L2 regularization) and the 1p/19q codeletion (support vector machine with radial basis function kernel) with an area under the curve of 0.831 (95% CI, 0.790-0.873) and 0.724 (95% CI, 0.669-0.782), respectively. For the prediction of IDH mutations, dynamic features were the most important features in the model (time to peak, 35.5%). In contrast, other radiomics features were the most useful for predicting the 1p/19q codeletion (up to 14.5% of importance for the small-zone low-gray-level emphasis). Conclusion:18F-FDOPA PET is an effective tool for the noninvasive prediction of glioma molecular parameters using a full set of amino-acid PET radiomics features. The contribution of each feature set shows the importance of systematically integrating dynamic acquisition for prediction of the IDH mutations as well as developing the use of radiomics features in routine practice for prediction of the 1p/19q codeletion.

Glioma Imaging by O-(2-18F-Fluoroethyl)-L-Tyrosine PET and Diffusion-Weighted MRI and Correlation With Molecular Phenotypes, Validated by PET/MR-Guided Biopsies

Gliomas exhibit high intra-tumoral histological and molecular heterogeneity. Introducing stereotactic biopsy, we achieved a superior molecular analysis of glioma using O-(2-18F-fluoroethyl)-L-tyrosine (FET)-positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging (DWI). Patients underwent simultaneous DWI and FET-PET scans. Correlations between biopsy-derived tumor tissue values, such as the tumor-to-background ratio (TBR) and apparent diffusion coefficient (ADC)/exponential ADC (eADC) and histopathological diagnoses and those between relevant genes and TBR and ADC values were determined. Tumor regions with human telomerase reverse transcriptase (hTERT) mutation had higher TBR and lower ADC values. Tumor protein P53 mutation correlated with lower TBR and higher ADC values. α-thalassemia/mental-retardation-syndrome-X-linked gene (ATRX) correlated with higher ADC values. 1p/19q codeletion and epidermal growth factor receptor (EGFR) mutations correlated with lower ADC values. Isocitrate dehydrogenase 1 (IDH1) mutations correlated with higher TBRmean values. No correlation existed between TBRmax/TBRmean/ADC/eADC values and phosphatase and tensin homolog mutations (PTEN) or O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. Furthermore, TBR/ADC combination had a higher diagnostic accuracy than each single imaging method for high-grade and IDH1-, hTERT-, and EGFR-mutated gliomas. This is the first study establishing the accurate diagnostic criteria for glioma based on FET-PET and DWI.

Machine Learning-Based Radiomics in Neuro-Oncology

In the last decades, modern medicine has evolved into a data-centered discipline, generating massive amounts of granular high-dimensional data exceeding human comprehension. With improved computational methods, machine learning and artificial intelligence (AI) as tools for data processing and analysis are becoming more and more important. At the forefront of neuro-oncology and AI-research, the field of radiomics has emerged. Non-invasive assessments of quantitative radiological biomarkers mined from complex imaging characteristics across various applications are used to predict survival, discriminate between primary and secondary tumors, as well as between progression and pseudo-progression. In particular, the application of molecular phenotyping, envisioned in the field of radiogenomics, has gained popularity for both primary and secondary brain tumors. Although promising results have been obtained thus far, the lack of workflow standardization and availability of multicenter data remains challenging. The objective of this review is to provide an overview of novel applications of machine learning- and deep learning-based radiomics in primary and secondary brain tumors and their implications for future research in the field.

Effects of Carbidopa Premedication on 18F-FDOPA PET Imaging of Glioma: A Multiparametric Analysis

Simple Summary

¹⁸F-FDOPA PET imaging is routinely used and recommended to assess gliomas. Carbidopa is a peripheral enzyme inhibitor. Carbidopa premedication increases the radiotracer uptake on static images. None of the evidence-based data available to date recommends carbidopa premedication. Our study therefore determined the impact of carbidopa premedication on static, radiomics and dynamic parameters for ¹⁸F-FDOPA PET brain tumor imaging. We show that carbidopa premedication leads to higher SUV and TTP dynamic parameters and impacts SUV-dependent radiomics by the same magnitude in healthy brains and tumors. The carbidopa effect is therefore compensated for by correcting for the tumor-to-healthy-brain ratio, a significant advantage for harmonizing data for multicentric studies. Results were obtained from simulations of time-activity curves using compartmental modeling.

Abstract

Purpose: This study aimed to determine the impact of carbidopa premedication on static, dynamic and radiomics parameters of ¹⁸F-FDOPA PET in brain tumors. Methods: The study included 54 patients, 18 of whom received carbidopa, who underwent ¹⁸F-FDOPA PET for newly diagnosed gliomas. SUV-derived, 105 radiomics features and TTP dynamic parameters were extracted from volumes of interest in healthy brains and tumors. Simulation of the effects of carbidopa on time-activity curves were generated. Results: All static and TTP dynamic parameters were significantly higher in healthy brain regions of premedicated patients (ΔSUV_mean = +53%, ΔTTP = +48%, p < 0.001). Furthermore, carbidopa impacted 81% of radiomics features, of which 92% correlated with SUV_mean (absolute correlation coefficient ≥ 0.4). In tumors, premedication with carbidopa was an independent predictor of SUV_mean (ΔSUV_mean = +52%, p < 0.001) and TTP (ΔTTP = +24%, p = 0.025). All parameters were no longer significantly modified by carbidopa premedication when using ratios to healthy brain. Simulated data confirmed that carbidopa leads to higher tumor TTP values, corrected by the ratios. Conclusion: In ¹⁸F-FDOPA PET, carbidopa induces similarly higher SUV and TTP dynamic parameters and similarly impacts SUV-dependent radiomics in healthy brain and tumor regions, which is compensated for by correcting for the tumor-to-healthy-brain ratio. This is a significant advantage for multicentric study harmonization.

Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?

Purpose

Dynamic amino acid positron emission tomography (PET) has become essential in neuro-oncology, most notably for its prognostic value in the noninvasive prediction of isocitrate dehydrogenase (IDH) mutations in newly diagnosed gliomas. The 6-[¹⁸F]fluoro-l-DOPA (¹⁸F-FDOPA) kinetic model has an underlying complexity, while previous studies have predominantly used a semiquantitative dynamic analysis. Our study addresses whether a semiquantitative analysis can capture all the relevant information contained in time–activity curves for predicting the presence of IDH mutations compared to the more sophisticated graphical and compartmental models.

Methods

Thirty-seven tumour time–activity curves from ¹⁸F-FDOPA PET dynamic acquisitions of newly diagnosed gliomas (median age = 58.3 years, range = 20.3–79.9 years, 16 women, 16 IDH-wild type) were analyzed with a semiquantitative model based on classical parameters, with (SQ) or without (Ref SQ) a reference region, or on parameters of a fit function (SQ Fit), a graphical Logan model with input function (Logan) or reference region (Ref Logan), and a two-tissue compartmental model previously reported for ¹⁸F-FDOPA PET imaging of gliomas (2TCM). The overall predictive performance of each model was assessed with an area under the curve (AUC) comparison using multivariate analysis of all the parameters included in the model. Moreover, each extracted parameter was assessed in a univariate analysis by a receiver operating characteristic curve analysis.

Results

The SQ model with an AUC of 0.733 for predicting IDH mutations showed comparable performance to the other models with AUCs of 0.752, 0.814, 0.693, 0.786, and 0.863, respectively corresponding to SQ Fit, Ref SQ, Logan, Ref Logan, and 2TCM (p ≥ 0.10 for the pairwise comparisons with other models). In the univariate analysis, the SQ time-to-peak parameter had the best diagnostic performance (75.7% accuracy) compared to all other individual parameters considered.

Conclusions

The SQ model circumvents the complexities of the ¹⁸F-FDOPA kinetic model and yields similar performance in predicting IDH mutations when compared to the other models, most notably the compartmental model. Our study provides supportive evidence for the routine clinical application of the SQ model for the dynamic analysis of ¹⁸F-FDOPA PET images in newly diagnosed gliomas.

Repeatability of image features extracted from FET PET in application to post-surgical glioblastoma assessment

Positron emission tomography (PET) imaging using the amino acid tracer O-[2-(¹⁸F)fluoroethyl]-L-tyrosine (FET) has gained increased popularity within the past decade in the management of glioblastoma (GBM). Radiomics features extracted from FET PET images may be sensitive to variations when imaging at multiple time points. It is therefore necessary to assess feature robustness to test-retest imaging. Eight patients with histologically confirmed GBM that had undergone post-surgical test-retest FET PET imaging were recruited. In total, 1578 radiomic features were extracted from biological tumour volumes (BTVs) delineated using a semi-automatic contouring method. Feature repeatability was assessed using the intraclass correlation coefficient (ICC). The effect of both bin width and filter choice on feature repeatability was also investigated. 59/106 (55.7%) features from the original image and 843/1472 (57.3%) features from filtered images had an ICC ≥ 0.85. Shape and first order features were most stable. Choice of bin width showed minimal impact on features defined as stable. The Laplacian of Gaussian (LoG, σ = 5 mm) and Wavelet filters (HLL and LHL) significantly improved feature repeatability (p ≪ 0.0001, p = 0.003, p = 0.002, respectively). Correlation of textural features with tumour volume was reported for transparency. FET PET radiomic features extracted from post-surgical images of GBM patients that are robust to test-retest imaging were identified. An investigation with a larger dataset is warranted to validate the findings in this study.

Pre- and Post-Treatment Imaging of Primary Central Nervous System Tumors in the Molecular and Genetic Era

Recent advances in the molecular and genetic characterization of central nervous system (CNS) tumors have ushered in a new era of tumor classification, diagnosis, and prognostic assessment. In this emerging and rapidly evolving molecular genetic era, imaging plays a critical role in the preoperative diagnosis and surgical planning, molecular marker prediction, targeted treatment planning, and post-therapy assessment of CNS tumors. This review provides an overview of the current imaging methods relevant to the molecular genetic classification of CNS tumors. Specifically, we focused on 1) the correlates between imaging features and specific molecular genetic markers and 2) the post-therapy imaging used for therapeutic assessment.

Additive Value of Dynamic FDOPA PET/CT for Glioma Grading

Purpose: The aim of this study was to assess the value of the FDOPA PET kinetic parameters extracted using full kinetic analysis for tumor grading with neuronavigation-guided biopsies as reference in patients with newly-diagnosed gliomas.

Methods: Fourteen patients with untreated gliomas were investigated. Twenty minutes of dynamic positron-emission tomography (PET) imaging and a 20-min static image 10 min after injection were reconstructed from a 40-min list-mode acquisition immediately after FDOPA injection. Tumors volume-of-interest (VOI) were generated based on the MRI-guided brain biopsies. Static parameters (TBRmax and TBRmean) and kinetic parameters [K1 and k2 using full kinetic analysis with the reversible single-tissue compartment model with blood volume parameter and the time-to-peak (TTP)] were extracted. Performances of each parameter for differentiating low-grade gliomas (LGG) from high-grade gliomas (HGG) were evaluated by receiver-operating characteristic analyses (area under the curve; AUC).

Results: Thirty-two tumoral VOI were analyzed. K1, k2, and TTP were significantly higher for HGG than for LGG (median K1-value = 0.124 vs. 0.074 ml/ccm/min, p = 0.025, median k2-value = 0.093 vs. 0.063 min⁻¹, p = 0.025, and median TTP-value = 10.0 vs. 15.0 min, p = 0.025). No significant difference was observed for the static parameters. The AUC for the kinetic parameters was higher than the AUC for the static parameters (respectively, AUC_K1 = 0.787, AUC_k2 = 0.785, AUC_TTP = 0.775, AUC_TBRmax = 0.551, AUC_TBRmean = 0.575), significantly compared to TBRmax (respectively, p = 0.001 for K1, p = 0.031 for k2, and p = 0.029 for TTP).

Conclusion: The present study suggests an additive value of FDOPA PET/CT kinetic parameters for newly-diagnosed gliomas grading.

A Linearized Fit Model for Robust Shape Parameterization of FET-PET TACs

The kinetic analysis of [Formula: see text]-FET time-activity curves (TAC) can provide valuable diagnostic information in glioma patients. The analysis is most often limited to the average TAC over a large tissue volume and is normally assessed by visual inspection or by evaluating the time-to-peak and linear slope during the late uptake phase. Here, we derived and validated a linearized model for TACs of [Formula: see text]-FET in dynamic PET scans. Emphasis was put on the robustness of the numerical parameters and how reliably automatic voxel-wise analysis of TAC kinetics was possible. The diagnostic performance of the extracted shape parameters for the discrimination between isocitrate dehydrogenase (IDH) wildtype (wt) and IDH-mutant (mut) glioma was assessed by receiver-operating characteristic in a group of 33 adult glioma patients. A high agreement between the adjusted model and measured TACs could be obtained and relative, estimated parameter uncertainties were small. The best differentiation between IDH-wt and IDH-mut gliomas was achieved with the linearized model fitted to the averaged TAC values from dynamic FET PET data in the time interval 4-50 min p.i.. When limiting the acquisition time to 20-40 min p.i., classification accuracy was only slightly lower (-3%) and was comparable to classification based on linear fits in this time interval. Voxel-wise fitting was possible within a computation time ≈ 1 min per image slice. Parameter uncertainties smaller than 80% for all fits with the linearized model were achieved. The agreement of best-fit parameters when comparing voxel-wise fits and fits of averaged TACs was very high (p < 0.001).

TERT-Promoter Mutational Status in Glioblastoma - Is There an Association With Amino Acid Uptake on Dynamic 18F-FET PET?

Objective

The mutation of the ‘telomerase reverse transcriptase gene promoter’ (TERTp) has been identified as an important factor for individual prognostication and tumorigenesis and will be implemented in upcoming glioma classifications. Uptake characteristics on dynamic ¹⁸F-FET PET have been shown to serve as additional imaging biomarker for prognosis. However, data on the correlation of TERTp-mutational status and amino acid uptake on dynamic ¹⁸F-FET PET are missing. Therefore, we aimed to analyze whether static and dynamic ¹⁸F-FET PET parameters are associated with the TERTp-mutational status in de-novo IDH-wildtype glioblastoma and whether a TERTp-mutation can be predicted by dynamic ¹⁸F-FET PET.

Methods

Patients with de-novo IDH-wildtype glioblastoma, WHO grade IV, available TERTp-mutational status and dynamic ¹⁸F-FET PET scan prior to any therapy were included. Here, established clinical parameters maximal and mean tumor-to-background-ratios (TBR_max/TBR_mean), the biological-tumor-volume (BTV) and minimal-time-to-peak (TTP_min) on dynamic PET were analyzed and correlated with the TERTp-mutational status.

Results

One hundred IDH-wildtype glioblastoma patients were evaluated; 85/100 of the analyzed tumors showed a TERTp-mutation (C228T or C250T), 15/100 were classified as TERTp-wildtype. None of the static PET parameters was associated with the TERTp-mutational status (median TBR_max 3.41 vs. 3.32 (p=0.362), TBR_mean 2.09 vs. 2.02 (p=0.349) and BTV 26.1 vs. 22.4 ml (p=0.377)). Also, the dynamic PET parameter TTP_min did not differ in both groups (12.5 vs. 12.5 min, p=0.411). Within the TERTp-mutant subgroups (i.e., C228T (n=23) & C250T (n=62)), the median TBR_max (3.33 vs. 3.69, p=0.095), TBR_mean (2.08 vs. 2.09, p=0.352), BTV (25.4 vs. 30.0 ml, p=0.130) and TTP_min (12.5 vs. 12.5 min, p=0.190) were comparable, too.

Conclusion

Uptake characteristics on dynamic ¹⁸F-FET PET are not associated with the TERTp-mutational status in glioblastoma However, as both, dynamic ¹⁸F-FET PET parameters as well as the TERTp-mutation status are well-known prognostic biomarkers, future studies should investigate the complementary and independent prognostic value of both factors in order to further stratify patients into risk groups.

Dynamic 18F-Fluoro-Ethyl-Tyrosine Positron Emission Tomography/ Computed Tomography: A Better Predictor of Isocitrate Dehydrogenase Mutation in Presurgical Evaluations of Glioma

The recent WHO classification of gliomas has incorporated molecular markers such as isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion into the ambit of morphological diagnosis, and 18F-fluoro-ethyl-tyrosine (¹⁸F-FET) positron emission tomography (PET) has shown its utility in noninvasive glioma grading and prognosis. Both dynamic and static FET PET parameters may assist in predicting the IDH mutational status, but time to peak derived from dynamic data may be a better predictor for IDH status. We present a case of left frontal lobe lesion suggestive of high-grade glioma on magnetic resonance imaging and static ¹⁸F-FET PET images, however, dynamic FET image was suggestive of low-grade IDH1-mutated glioma which was later confirmed on histology and immunohistochemistry.

Comparison of [18F]Fluoroethyltyrosine PET and Sodium MRI in Cerebral Gliomas: a Pilot Study

PURPOSE

Positron emission tomography (PET) using O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) improves the diagnostics of cerebral gliomas compared with conventional magnetic resonance imaging (MRI). Sodium MRI is an evolving method to assess tumor metabolism. In this pilot study, we explored the relationship of [¹⁸F]FET-PET and sodium MRI in patients with cerebral gliomas in relation to the mutational status of the enzyme isocitrate dehydrogenase (IDH).

PROCEDURES

Ten patients with untreated cerebral gliomas and one patient with a recurrent glioblastoma (GBM) were investigated by dynamic [¹⁸F]FET-PET and sodium MRI using an enhanced simultaneous single-quantum- and triple-quantum-filtered imaging of ²³Na (SISTINA) sequence to estimate total (NaT), weighted non-restricted (NaNR, mainly extracellular), and restricted (NaR, mainly intracellular) sodium in tumors and normal brain tissue. [¹⁸F]FET uptake and sodium parameters in tumors with a different IDH mutational status were compared. After biopsy or resection, histology and the IDH mutational status were determined neuropathologically.

RESULTS

NaT (p = 0.05), tumor-to-brain ratios (TBR) of NaT (p = 0.02), NaNR (p = 0.003), and the ratio of NaT/NaR (p < 0.001) were significantly higher in IDH-mutated than in IDH-wild-type gliomas (n = 5 patients each) while NaR was significantly lower in IDH-mutated gliomas (p = 0.01). [¹⁸F]FET parameters (TBR, time-to-peak) were not predictive of IDH status in this small cohort of patients. There was no obvious relationship between sodium distribution and [¹⁸F]FET uptake. The patient with a recurrent GBM exhibited an additional radiation injury with strong abnormalities in sodium MRI.

CONCLUSIONS

Sodium MRI appears to be more strongly related to the IDH mutational status than are [¹⁸F]FET-PET parameters. A further evaluation of the combination of the two methods in a larger group of high- and low-grade gliomas seems promising.

The diagnostic value of lower glucose consumption for IDH1 mutated gliomas on FDG-PET

Background

Non-invasive diagnosis of IDH1 mutation for gliomas has great clinical significance, and PET has natural advantage to detect metabolism, as IDH mutated gliomas share lower glucose consumption.

Methods

Clinical data of patients with gliomas and ¹⁸F-FDG PET were retrospectively reviewed. Receiver operating characteristic curve (ROC) analysis was conducted, and standard uptake value (SUV) was estimated in combination with grades or IDH1 mutation. The glucose consumption was investigated with U251 cells expressing wild-type or mutated IDH1 by glucose assay. Quantification of glucose was determined by HPLC in clinical tissues. Meanwhile, bioinformatics and western blot were applied to analyze the expression level of metabolic enzymes (e.g. HK1, PKM2, PC) in gliomas.

Results

Seventy-one glioma cases were enrolled, including 30 carrying IDH1 mutation. The sensitivity and specificity dependent on SUV_max (3.85) predicting IDH1 mutation reached 73.2 and 86.7%, respectively. The sensitivity and specificity of differentiating grades by SUVmax (3.1) were 92.3 and 64.4%, respectively. Glucose consumption of U251 IDH1 mutant cells (0.209 ± 0.0472 mg/ml) was obviously lower than IDH1wild-type cells (0.978 ± 0.0773 mg/ml, P = 0.0001) and astrocyte controls (0.335 ± 0.0592 mg/ml, P = 0.0451). Meanwhile, the glucose quantity in IDH1mutant glioma samples were significantly lower than those in IDH1 wild-type tissues (1.033 ± 1.19608 vs 6.361 ± 4.3909 mg/g, P = 0.0051). Silico analysis and western blot confirmed that HK1 and PKM2 in IDH1 wild-type gliomas were significantly higher than in IDH1 mutant group, while PC was significantly higher in IDH1 mutant gliomas.

Conclusion

SUV_max on PET can predict IDH1 mutation with adequate sensitivity and specificity, as is supported by reduced glucose consumption in IDH1 mutant gliomas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07797-6.

Diagnostic Performance of [11C]Methionine Positron Emission Tomography in Newly Diagnosed and Untreated Glioma Based on the Revised World Health Organization 2016 Classification

BACKGROUND

The relationship between uptake of amino acid tracer with positron emission tomography (PET) and glioma subtypes/gene status is still unclear.

OBJECTIVE

To assess the relationship between uptake of [¹¹C]methionine using PET and pathology, IDH (isocitrate dehydrogenase) mutation, 1p/19q codeletion, and TERT (telomerase reverse transcriptase) promoter status in gliomas.

METHODS

The participants were 68 patients with newly diagnosed and untreated glioma who underwent surgical excision and preoperative [¹¹C]methionine PET examination at Osaka City University Hospital between July 2011 and March 2018. Clinical and imaging studies were reviewed retrospectively based on the medical records at our institution.

RESULTS

The mean lesion/contralateral normal brain tissue (L/N) ratio of diffuse astrocytomas was significantly lower than that of anaplastic astrocytomas (P = 0.00155), glioblastoma (P < 0.001), and oligodendrogliomas (P = 0.0157). The mean L/N ratio of IDH mutant gliomas was significantly lower than that of IDH wild-type gliomas (median 1.75 vs. 2.61; P = 0.00162). A mean L/N ratio of 2.05 provided the best sensitivity and specificity for distinguishing between IDH mutant and IDH wild-type gliomas (69.2% and 76.2%, respectively). The mean L/N ratio of TERT promoter mutant gliomas was significantly higher than that of TERT promoter wild-type gliomas (P = 0.0147). Multiple regression analysis showed that pathologic diagnosis was the only influential factor on L/N ratio.

CONCLUSIONS

Distinguishing glioma subtypes based on the revised 2016 World Health Organization classification of the central nervous system tumors on the basis of [¹¹C]methionine PET alone seems to be difficult. However, [¹¹C]methionine PET might be useful for predicting the IDH mutation status in newly diagnosed and untreated gliomas noninvasively before tumor resection.

Conventional and advanced imaging throughout the cycle of care of gliomas

Although imaging of gliomas has evolved tremendously over the last decades, published techniques and protocols are not always implemented into clinical practice. Furthermore, most of the published literature focuses on specific timepoints in glioma management. This article reviews the current literature on conventional and advanced imaging techniques and chronologically outlines their practical relevance for the clinical management of gliomas throughout the cycle of care. Relevant articles were located through the Pubmed/Medline database and included in this review. Interpretation of conventional and advanced imaging techniques is crucial along the entire process of glioma care, from diagnosis to follow-up. In addition to the described currently existing techniques, we expect deep learning or machine learning approaches to assist each step of glioma management through tumor segmentation, radiogenomics, prognostication, and characterization of pseudoprogression. Thorough knowledge of the specific performance, possibilities, and limitations of each imaging modality is key for their adequate use in glioma management.

Heterogeneous parameters based on 18F-FET PET imaging can non-invasively predict tumor grade and isocitrate dehydrogenase gene 1 mutation in untreated gliomas

Background

The present study aimed to explore the efficacy of easily obtained intratumoral heterogeneous parameters, other than regular semi-quantitative parameters, based on static O-(2-[18F]fluoroethyl)-l-tyrosine (¹⁸F-FET) positron emission tomography (PET) imaging in glioma grade and isocitrate dehydrogenase (IDH) gene 1 mutation prediction.

Methods

Fifty-eight adult patients with untreated glioma (grades II-IV) who underwent preoperative ¹⁸F-FET PET/computed tomography (CT) imaging were enrolled in the present study. Eight semi-automatically obtained static PET imaging parameters after lesion delineation were chosen for analysis. These were: maximal tumor-to-background ratio (TBRmax), peak tumor-to-background ratio (TBRpeak), mean tumor-to-background ratio (TBRmean), coefficient of variation (COV), heterogeneity index (HI), the standard deviation of lesion standardized uptake value (SUVsd), metabolic tumor volume (MTV), and total lesion tracer standardized uptake (TLU). Pathological and immunohistochemical results were used as a reference. The receiver-operating characteristic analysis was used to investigate the predictive efficacy of these parameters in glioma grade and IDH1 mutation status.

Results

TLU [area under the curve (AUC): 0.841, P<0.0001], TBRpeak (AUC: 0.832, P<0.0001), and HI (AUC: 0.826, P<0.0001) had the top 3 single-parameter predictive performance between grade II or III and grade IV glioma patients. Combinations of TBRmax, SUVsd, and TBRmean (AUC: 0.850, P<0.0001); HI, SUVsd, and MTV (AUC: 0.848, P<0.0001); and HI, SUVsd, and TLU (AUC: 0.848, P<0.0001) had the top 3 multiple-parameter predictive performance. SUVsd (AUC: 0.710, P=0.0028), TLU (AUC: 0.698, P=0.0074), and HI (AUC: 0.676, P=0.0159) had the top 3 single-parameter predictive performance in the IDH1 genotype. Combinations of TBRmax, SUVsd, and TBRmean (AUC: 0.821, P<0.0001); SUVsd and TBRmean (AUC: 0.804, P<0.0001); and SUVsd, HI, and TBRmean (AUC: 0.799, P<0.0001) had the top 3 multiple-parameter predictive performance.

Conclusions

These easily obtained and highly repetitive heterogeneous parameters based on static ¹⁸F-FET PET/CT imaging can non-invasively predict glioma grade and IDH1 mutation, crucial in treatment planning, and prognostic evaluation.

Current trends in the use of O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) in neurooncology

The diagnostic potential of PET using the amino acid analogue O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) in brain tumor diagnostics has been proven in many studies during the last two decades and is still the subject of multiple studies every year. In addition to standard magnetic resonance imaging (MRI), positron emission tomography (PET) using [18F]FET provides important diagnostic data concerning brain tumor delineation, therapy planning, treatment monitoring, and improved differentiation between treatment-related changes and tumor recurrence. The pharmacokinetics, uptake mechanisms and metabolism have been well described in various preclinical studies. The accumulation of [18F]FET in most benign lesions and healthy brain tissue has been shown to be low, thus providing a high contrast between tumor tissue and benign tissue alterations. Based on logistic advantages of F-18 labelling and convincing clinical results, [18F]FET has widely replaced short lived amino acid tracers such as L-[11C]methyl-methionine ([11C]MET) in many centers across Western Europe. This review summarizes the basic knowledge on [18F]FET and its contribution to the care of patients with brain tumors. In particular, recent studies about specificity, possible pitfalls, and the utility of [18F]FET PET in tumor grading and prognostication regarding the revised WHO classification of brain tumors are addressed.

Advancing Imaging to Enhance Surgery: From Image to Information Guidance

Conventional magnetic resonance imaging (cMRI) has an established role as a crucial disease parameter in the multidisciplinary management of glioblastoma, guiding diagnosis, treatment planning, assessment, and follow-up. Yet, cMRI cannot provide adequate information regarding tissue heterogeneity and the infiltrative extent beyond the contrast enhancement. Advanced magnetic resonance imaging and PET and newer analytical methods are transforming images into data (radiomics) and providing noninvasive biomarkers of molecular features (radiogenomics), conveying enhanced information for improving decision making in surgery. This review analyzes the shift from image guidance to information guidance that is relevant for the surgical treatment of glioblastoma.

Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status

OBJECTIVES

To investigate the predictive value of static O-(2-¹⁸F-fluoroethyl)-L-tyrosine positron emission tomography (¹⁸F-FET PET) and cerebral blood volume (CBV) for glioma grading and determining isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status.

METHODS

Fifty-two patients with newly diagnosed gliomas who underwent simultaneous ¹⁸F-FET PET and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) examinations on hybrid PET/MR were retrospectively enrolled. The mean and max tumor-to-brain ratio (TBR) and normalized CBV (nCBV) were calculated based on whole tumor volume segmentations with reference to PET/MR images. The predictive efficacy of FET PET and CBV in glioma according to the 2016 World Health Organization (WHO) classification was evaluated by receiver operating characteristic curve analyses with the area under the curve (AUC).

RESULTS

TBRmean, TBRmax, nCBVmean, and nCBVmax differed between low- and high-grade gliomas, with the highest AUC of nCBVmean (0.920). TBRmax and nCBVmean showed significant differences between gliomas with and without IDH mutation (p = 0.032 and 0.010, respectively). Furthermore, TBRmean, TBRmax, and nCBVmean discriminated between IDH-wildtype glioblastomas and IDH-mutated astrocytomas (p = 0.049, 0.034 and 0.029, respectively). The combination of TBRmax and nCBVmean showed the best predictive performance (AUC, 0.903). Only nCBVmean differentiated IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas (p < 0.001) (AUC, 0.829), but none of the parameters discriminated between oligodendrogliomas and astrocytomas.

CONCLUSIONS

Both FET PET and DSC-PWI might be non-invasive predictors for glioma grades and IDH mutation status. FET PET combined with CBV could improve the differentiation of IDH-mutated astrocytomas and IDH-wildtype glioblastomas. However, FET PET and CBV might be limited for identifying oligodendrogliomas.

KEY POINTS

• Static ¹⁸F-FET PET and DSC-PWI parameters differed between low- and high-grade gliomas, with the highest AUC of the mean value of normalized CBV. • Static ¹⁸F-FET PET and DSC-PWI parameters based on hybrid PET/MR showed predictive value in identifying glioma IDH mutation subtypes, which have gained importance for both determining the diagnosis and prognosis of gliomas according to the 2016 WHO classification. • Static ¹⁸F-FET PET and DSC-PWI parameters have limited potential in differentiating IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas or IDH-mutated astrocytomas.

Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Simple Summary

Approximately 75–80% of according to the classification of world health organization (WHO) grade II and III gliomas are characterized by a mutation of the isocitrate dehydrogenase (IDH) enzymes, which are very important in glioma cell metabolism. Patients with IDH mutated glioma have a significantly better prognosis than patients with IDH wildtype status, typically seen in glioblastoma WHO grade IV. Here we used a prospective O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) positron emission tomography guided single-voxel ¹H-magnetic resonance spectroscopy approach to predict the IDH status before surgery. Finally, 34 patients were included in this neuroimaging study, of whom eight had additionally tissue analysis. Using a machine learning technique, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% and a specificity of 75.0%. It was newly recognized, that two metabolites (myo-inositol and glycine) have a particularly important role in the determination of the IDH status.

Abstract

Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard ¹H-magnetic resonance spectroscopy (¹H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) for optimized voxel placement in ¹H-MRS. Routine ¹H-magnetic resonance (¹H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the ¹H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%) and a specificity of 75.0% (95% CI, 42.9–94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo ¹H-nuclear magnetic resonance (¹H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

MGMT Promoter Methylation and IDH1 Mutations Do Not Affect [18F]FDOPA Uptake in Primary Brain Tumors

The aim of our study was to investigate the effects of methylation of O⁶-methylguanine-DNA methyltransferase promoter (MGMTp) and isocitrate dehydrogenase 1 (IDH 1) mutations on amino acid metabolism evaluated with 3,4-dihydroxy-6-[¹⁸F]-fluoro-l-phenylalanine ([¹⁸F] FDOPA) positron emission tomography/computed tomography (PET/CT). Seventy-two patients with primary brain tumors were enrolled in the study (33 women and 39 men; mean age 44 ± 12 years old). All of them were subjected to PET/CT examination after surgical treatment. Of them, 29 (40.3%) were affected by grade II glioma and 43 (59.7%) by grade III. PET/CT was scored as positive or negative and standardized uptake value ratio (SUVr) was calculated as the ratio between SUVmax of the lesion vs. that of the background. Statistical analysis was performed with the Mann–Whitney U test. Methylation of MGMTp was detectable in 61 out of the 72 patients examinated. Mean SUVr in patients without methylation of MGMTp was 1.44 ± 0.38 vs. 1.35 ± 0.48 of patients with methylation (p = 0.15). Data on IDH1 mutations were available for 43 subjects; of them, 31 are IDH-mutant. Mean SUVr was 1.38 ± 0.51 in patients IDH mutant and 1.46 ± 0.56 in patients IDH wild type. MGMTp methylation and IDH1 mutations do not affect [¹⁸F] FDOPA uptake in primary brain tumors and therefore cannot be assessed or predicted by radiopharmaceutical uptake parameters.

A Nomogram Modeling 11C-MET PET/CT and Clinical Features in Glioma Helps Predict IDH Mutation

Purpose: We developed a ¹¹C-Methionine positron emission tomography/computed tomography (¹¹C-MET PET/CT)-based nomogram model that uses easy-accessible imaging and clinical features to achieve reliable non-invasive isocitrate dehydrogenase (IDH)-mutant prediction with strong clinical translational capability.

Methods: One hundred and ten patients with pathologically proven glioma who underwent pretreatment ¹¹C-MET PET/CT were retrospectively reviewed. IDH genotype was determined by IDH1 R132H immunohistochemistry staining. Maximum, mean and peak tumor-to-normal brain tissue (TNRmax, TNRmean, TNRpeak), metabolic tumor volume (MTV), total lesion methionine uptake (TLMU), and standard deviation of SUV (SUV_SD) of the lesions on MET PET images were obtained via a dedicated workstation (Siemens. syngo.via). Univariate and multivariate logistic regression models were used to identify the predictive factors for IDH mutation. Nomogram and calibration plots were further performed.

Results: In the entire population, TNRmean, TNRmax, TNRpeak, and SUV_SD of IDH-mutant glioma patients were significantly lower than these values of IDH wildtype. Receiver operating characteristic (ROC) analysis suggested SUV_SD had the best performance for IDH-mutant discrimination (AUC = 0.731, cut-off ≤ 0.29, p < 0.001). All pairs of the ¹¹C-MET PET metrics showed linear associations by Pearson correlation coefficients between 0.228 and 0.986. Multivariate analyses demonstrated that SUV_SD (>0.29 vs. ≤ 0.29 OR: 0.053, p = 0.010), dichotomized brain midline structure involvement (no vs. yes OR: 26.52, p = 0.000) and age (≤ 45 vs. >45 years OR: 3.23, p = 0.023), were associated with a higher incidence of IDH mutation. The nomogram modeling showed good discrimination, with a C-statistics of 0.866 (95% CI: 0.796–0.937) and was well-calibrated.

Conclusions:¹¹C-Methionine PET/CT imaging features (SUV_SD and the involvement of brain midline structure) can be conveniently used to facilitate the pre-operative prediction of IDH genotype. The nomogram model based on ¹¹C-Methionine PET/CT and clinical age features might be clinically useful in non-invasive IDH mutation status prediction for untreated glioma patients.

Use of static and dynamic [18F]-F-DOPA PET parameters for detecting patients with glioma recurrence or progression

BACKGROUND

Static [¹⁸F]-F-DOPA PET images are currently used for identifying patients with glioma recurrence/progression after treatment, although the additional diagnostic value of dynamic parameters remains unknown in this setting. The aim of this study was to evaluate the performances of static and dynamic [¹⁸F]-F-DOPA PET parameters for detecting patients with glioma recurrence/progression as well as assess further relationships with patient outcome.

METHODS

Fifty-one consecutive patients who underwent an [¹⁸F]-F-DOPA PET for a suspected glioma recurrence/progression at post-resection MRI, were retrospectively included. Static parameters, including mean and maximum tumor-to-normal-brain (TBR) ratios, tumor-to-striatum (TSR) ratios, and metabolic tumor volume (MTV), as well as dynamic parameters with time-to-peak (TTP) values and curve slope, were tested for predicting the following: (1) glioma recurrence/progression at 6 months after the PET exam and (2) survival on longer follow-up.

RESULTS

All static parameters were significant predictors of glioma recurrence/progression (accuracy ≥ 94%) with all parameters also associated with mean progression-free survival (PFS) in the overall population (all p < 0.001, 29.7 vs. 0.4 months for TBR_max, TSR_max, and MTV). The curve slope was the sole dynamic PET predictor of glioma recurrence/progression (accuracy = 76.5%) and was also associated with mean PFS (p < 0.001, 18.0 vs. 0.4 months). However, no additional information was provided relative to static parameters in multivariate analysis.

CONCLUSION

Although patients with glioma recurrence/progression can be detected by both static and dynamic [¹⁸F]-F-DOPA PET parameters, most of this diagnostic information can be achieved by conventional static parameters.