Amino Acid PET Research Articles

TMET-29. THE GLUTAMINE TRANSPORTER SLC1A5 IS ASSOCIATED WITH REWIRING OF AMINO ACID, LIPID, AND IMMUNE PATHWAYS AND TUMOR PROGNOSIS IN PEDIATRIC BRAIN CANCERS

Abstract Glutamine transporters play an important role in supporting increased tumor nutritional demands, often through overexpression of the solute carrier (SLC) family of membrane transporters. We aimed to understand the relationship of SLC transporter expression with pediatric brain tumor subtypes, lipid metabolism and their potential prognostic significance using data from the Pediatric Brain Tumor Atlas (PBTA). Using the expression of amino acid transporter genes, we found that elevated expression of glutamine transporters (SLC1A5, SLC7A5, SLC7A11, SLC38A5, SLC38A3) predicted shorter progression-free survival (PFS) in low-grade gliomas (LGGs) and poorer overall survival in pediatric ependymomas, high-grade gliomas (HGGs), and medulloblastomas. We focused specifically on SLC1A5 given the availability of imaging probes (18 F-Fluoroglutamine and 18F-Fluciclovine) for the corresponding amino acid transporter (ASCT2). Kaplan-Meier analysis found that higher expression of SLC1A5 was associated with shorter OS in ependymoma and medulloblastoma (p = 0.032 and p = 9.8e-4) and shorter PFS in LGG (p = 0.022). We found a universally higher expression of ATP citrate lyase (ACLY) and Acetyl-CoA carboxylase 1 (ACC) relative to normal brain tissue across all histologies. BRAF driven low grade gliomas and SHH-driven medulloblastomas showed differential expression of ACLY compared to other histologies. In addition, Acyl-CoA synthetase short chain family member 1 and 2 (ACSS1 and 2) were universally downregulated in pediatric gliomas, indicating that pediatric CNS tumors seem to rely on ACLY over ACSS for lipid synthesis. Gene set analysis showed higher expression and network rewiring of amino acid, lipid, and immune pathways in SLC1A5-high expressing clusters. SLC1A5 correlated negatively with pathways associated with lipid metabolic breakdown/degradation and correlated positively with pathways associated with lipid biosynthesis. In conclusion, our work demonstrates that glutamine transporters, particularly SLC1A5, represent compelling targets in pediatric brain tumors and can be exploited with theranostic approaches and amino-acid PET imaging.

Differentiating high-grade glioma progression from treatment-related changes with dynamic [18F]FDOPA PET: a multicentric study.

Diagnostic accuracy of amino-acid PET for distinguishing progression from treatment-related changes (TRC) is currently based on single-center non-homogeneous glioma populations. Our study assesses the diagnostic value of static and dynamic [18F]FDOPA PET acquisitions to differentiate between high-grade glioma (HGG) recurrence and TRC in a large cohort sourced from two independent nuclear medicine centers. We retrospectively identified 106 patients with suspected glioma recurrences (WHO GIII, n = 38; GIV, n = 68; IDH-mutant, n = 35, IDH-wildtype, n = 71). Patients underwent dynamic [18F]FDOPA PET/CT (n = 83) or PET/MRI (n = 23), and static tumor-to-background ratios (TBRs), metabolic tumor volumes and dynamic parameters (time to peak and slope) were determined. The final diagnosis was either defined by histopathology or a clinical-radiological follow-up at 6 months. Optimal [18F]FDOPA PET parameter cut-offs were obtained by receiver operating characteristic analysis. Predictive factors and clinical parameters were assessed using univariate and multivariate Cox regression survival analyses. Surgery or the clinical-radiological 6-month follow-up identified 71 progressions and 35 treatment-related changes. TBRmean, with a threshold of 1.8, best-differentiated glioma recurrence/progression from post-treatment changes in the whole population (sensitivity 82%, specificity 71%, p < 0.0001) whereas curve slope was only significantly different in IDH-mutant HGGs (n = 25). In survival analyses, MTV was a clinical independent predictor of progression-free and overall survival on the multivariate analysis (p ≤ 0.01). A curve slope > -0.12/h was an independent predictor for longer PFS in IDH-mutant HGGs CONCLUSION: Our multicentric study confirms the high accuracy of [18F]FDOPA PET to differentiate recurrent malignant gliomas from TRC and emphasizes the diagnostic and prognostic value of dynamic acquisitions for IDH-mutant HGGs. • The diagnostic accuracy of dynamic amino-acid PET, for distinguishing progression from treatment-related changes, is currently based on single-center non-homogeneous glioma populations. • This multicentric study confirms the high accuracy of static [18F]FDOPA PET images for differentiating progression from treatment-related changes in a homogeneous population of high-grade gliomas and highlights the diagnostic and prognostic value of dynamic acquisitions for IDH-mutant high-grade gliomas. • Dynamic acquisitions should be performed in IDH-mutant glioma patients to provide valuable information for the differential diagnosis of recurrence and treatment-related changes.

Noninvasive Delineation of Glioma Infiltration with Combined 7T Chemical Exchange Saturation Transfer Imaging and MR Spectroscopy: A Diagnostic Accuracy Study.

For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST and MRS to predict glioma infiltration. Eighteen glioma patients of different tumor grades were enrolled in this study; 18F-fluoroethyltyrosine (FET)-PET, amide proton transfer CEST at 7 Tesla(T), MRS and conventional MR at 3T were conducted preoperatively. Multi modalities and their association were evaluated using Pearson correlation analysis patient-wise and voxel-wise. Both CEST (R = 0.736, p < 0.001) and MRS (R = 0.495, p = 0.037) correlated with FET-PET, while the correlation between CEST and MRS was weaker. In subgroup analysis, APT values were significantly higher in high grade glioma (3.923 ± 1.239) and IDH wildtype group (3.932 ± 1.264) than low grade glioma (3.317 ± 0.868, p < 0.001) or IDH mutant group (3.358 ± 0.847, p < 0.001). Using high FET uptake as the standard, the CEST/MRS combination (AUC, 95% CI: 0.910, 0.907–0.913) predicted tumor infiltration better than CEST (0.812, 0.808–0.815) or MRS (0.888, 0.885–0.891) alone, consistent with contrast-enhancing and T2-hyperintense areas. Probability maps of tumor presence constructed from the CEST/MRS combination were preliminarily verified by multi-region biopsies. The combination of 7T CEST/MRS might serve as a promising non-radioactive alternative to delineate glioma infiltration, thus reshaping the guidance for tumor resection and irradiation.

KS02.7.A Impact of FET PET on multidisciplinary neurooncological tumor board decisions in patients with brain tumors

Abstract Background Following neurooncological treatment of brain tumors, neurooncologists are often confronted with equivocal MRI findings (e.g., treatment-related changes such as pseudoprogression, non-measurable contrast-enhancing lesions, T2/FLAIR signal alterations, pseudoresponse). Especially in Europe, amino-acid PET is increasingly integrated into multidisciplinary neurooncological tumor boards (MNTB) to overcome these diagnostic uncertainties. We evaluated the correctness of MNTB decisions, in which amino acid PET findings were taken into account. Material and Methods In a single-university center study, we retrospectively evaluated 182 MNTB decisions of 154 patients with histomolecularly defined WHO grade 3 or 4 gliomas (n=123), including glioblastoma (n=80), anaplastic glioma (n=42), and gliosarcoma (n=1), or brain metastases (n=31) secondary to lung cancer, melanoma, breast cancer, or colorectal cancer presenting equivocal MRI findings following anticancer treatment. All patients underwent O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET imaging as an adjunct for decision-making. Additionally, the patients’ clinical status, pretreatment, and conventional MRI findings were considered for decision-making. The presence of neoplastic tissue was considered if the mean FET uptake as assessed by tumor-to-brain ratios was &amp;gt; 2.0. MNTB decisions were validated using the neuropathological result in 42% (n=77) or clinicoradiologically in 58% (n=105). The diagnostic performance of MTNB decisions was evaluated using 2x2 contingency tables. Results The validation of all 182 MNTB recommendations, which integrated FET PET in the decision-making process, were correct in 95% (sensitivity, 97%; specificity, 75%; positive predictive value, 96%). Due to tumor progression, MNTB recommendations prompted a treatment change in 88% (n=160 of 182 decisions). When FET PET findings suggested progressive disease (n=157), MNTB decisions were correct in 96% (positive predictive value, 97%). In 22 MNTB decisions with the recommendation to continue the current treatment regimen, 82% were correctly identified as treatment-related changes. Conclusion FET PET seems to have a significant impact on MNTB decisions. A prospective evaluation of MNTB decisions with and without the integration of FET PET is warranted to define the added value of FET PET.

P15.10.B A multicenter phase 3 trial in progress: diagnostic performance of18F-fluciclovine PET for the detection of recurrent brain metastases after radiation therapy (REVELATE)

Abstract Background Following treatment of brain metastases, which can affect up to 40% of patients with cancer, patients will typically be closely monitored with serial brain magnetic resonance imaging (MRI) owing to the high likelihood of recurrence. The recommended follow-up modalities (CE-T1-weighted and FLAIR/T2-weighted MRI) have poor specificity, meaning that differentiation of true disease from treatment-related changes such as radiation necrosis can be difficult. Recent pilot studies have reported amino acid PET radiopharmaceutical, 18F-fluciclovine, to be potentially useful in discriminating brain tumor recurrence from treatment-related changes. This may potentially help physicians to make confident diagnoses and inform subsequent treatment plans. Material and Methods REVELATE (NCT04410133) will evaluate the diagnostic performance of 18F-fluciclovine PET (read with conventional MRI for anatomical reference) for the detection of recurrent brain metastases in patients for whom MRI is equivocal. This multicenter, phase 3, prospective, open-label trial aims to enroll approximately 150 subjects from across 19 US sites with solid tumor brain metastases who have undergone radiation therapy, if they have a lesion considered equivocal on MRI that requires further confirmatory diagnostic procedures (either biopsy/neurosurgical intervention or clinical follow-up). Patients will undergo 18F-fluciclovine PET &amp;lt;42 days after the equivocal MRI and 1-21 days pre-biopsy/neurosurgical intervention. Clinical follow-up will occur for 6m post-18F-fluciclovine PET. Results The primary endpoint of REVELATE is the subject-level 18F-fluciclovine negative and positive percent agreement (equivalent to specificity and sensitivity, respectively) for detection of recurrent brain metastases. Further objectives include evaluation of the lesion-level diagnostic performance, inter-reader and intra-reader agreement, and safety evaluations. Conclusion This ongoing phase 3 study will provide efficacy and safety data for the use of 18F-fluciclovine for the detection of recurrent brain metastases. Enrolment began in October 2020 and the trial is active but not recruiting at the time of submission.

JS07.4.A Correspondence of glutamine and glycine imaging based on 7T MRSI to amino acid PET

Abstract Background New approaches for 7 Tesla magnetic resonance spectroscopic imaging (MRSI) allow the simultaneous imaging of multiple neuro-oncological biomarkers with 3-4 mm resolution in clinically feasible measurement times. Specifically, the amino acids glutamine (Gln) and Glycine (Gly), were previously limited to single voxel detection at lower fields. Both could add to our capabilities to resolve heterogeneous tumour metabolism. Purpose To progress the validation of Gln and Gly as neuro-oncological markers by conducting the first comparison to amino acid PET in a cohort of glioma patients. Material and Methods In 24 glioma patients (WHO 2021 classification), we quantitatively compared 7T MRSI (3D, 3.4 mm isotropic resolution, 15 min scan time) and routine PET (FET or MET). Within manual tumour segmentations, we defined hotspot volumes of interest (VOI) for the ratios of total choline (tCho, clinical standard reference), Gln, Gly to total N-acetylaspartate (tNAA) and PET tumour-to-brain ratios (TBR), all with a cut-off threshold of 1.6. For these VOIs, we calculated VOI volumes and median ratios as well as Dice similarity coefficients (DSC) and centre of intensity distance (CoI), between MRSI and PET ratios. Results We found that Gln and Gly ratios to tNAA had a higher correspondence to PET-based amino acid metabolism than tCho. Our resulting median VOI volumes were 19.08±23.10 cm³ for tCho/tNAA, 33.68±24.60 cm³ for Gln/tNAA, and 22.38±18.49 cm³ for Gly/tNAA compared to 24.33±30.46 cm³ for PET, with correlation coefficients &amp;gt;0.5 for all MRSI hotspot values in relation to PET volumes. Median ratios were 0.52±0.13 for tCho/tNAA, 0.61±0.25 for Gln/tNAA, 0.33±0.15 for Gly/tNAA and 2.11±0.42 for PET. The median DSCs to PET amounted to 0.53±0.36 for tCho/tNAA, 0.66±0.40 for Gln/tNAA, and 0.57±0.36 for Gly/tNAA, while the median CoI distances were 0.56±0.43 cm for tCho/tNAA, 0.39±0.22 cm for Gln/tNAA, and 0.45±0.48 cm for Gly/tNAA. Conclusion With this first study that compared high-resolution 3D-MRSI at 7 Tesla to amino acid PET and a quantitative evaluation, we demonstrated that Gln and Gly corresponded better to PET than tCho, which is the main marker used in clinical MR, both within the study and compared to previous literature. Future research is needed to clearly define the benefits of 7T MRSI for neuro-oncology such as the identification of tumour microenvironments or non-invasive determination of molecular-pathologic markers. Gln could be further explored by the application of Gln-based PET tracers to MR-PET. We still see further developments of MRSI methods, such as motion correction or absolute quantification of concentrations instead of ratios, as necessary to obtain such goals.

JS07.5.A 18F-fluciclovine PET and multi-parametric MRI to distinguish pseudoprogression from tumor progression in post-treatment glioblastoma

Abstract Background Differentiation of tumor progression (TP) from pseudoprogression (PsP) is a major unmet need in glioblastoma (GBM). 18F-Fluciclovine is a synthetic amino acid PET radiotracer with higher uptake in tumor tissue vs. areas of treatment-related change. We aimed to assess the combined value of 18F-Fluciclovine PET and multi-parametric MRI for differentiating PsP from TP. Material and Methods We enrolled 30 patients with GBM with a new or enlarging contrast-enhancing lesion on MRI after chemoradiotherapy who were planned for surgical resection of the lesion. Patients underwent pre-operative 18F-Fluciclovine PET and multi-parametric MRI. Following surgery, the relative percentages of viable tumor and therapy-related changes observed on histopathology were quantified. Patients were categorized as TP if viable tumor represented ≥ 50% of the specimen, mixed TP if &amp;lt; 50% and &amp;gt; 10%, and PsP if ≤ 10%. SUVmax, SUVpeak, and 50% threshold SUVmean were calculated and normalized to contralateral brain, pituitary gland, and superior sagittal sinus (SSS). The least absolute shrinkage and selection operator (LASSO) was used to determine the variables most predictive of tumor percentage. The strength of association between the primary outcome and selected variables was assessed by Pearson’s or Point-biserial correlation. Results 18 patients with TP, 4 with mixed TP-PsP, and 8 with PsP were included. There was a positive correlation between 50% threshold SUV mean measured from PET images acquired 50-60 minutes post-injection and rCBVmax by MRI and tumor percentage by histology (r= 0.56; p= 0.004 and r=0.50; p=0.012 respectively). 40-50 minutes SUVmax (OR=1.78 rpb=0.51) and rCBVmax (OR=1.64, rpb=0.48) were positively correlated with tumor TP/mixed TP group. Patients who demonstrated TP/mixed TP-PsP had significantly higher 40-50 minutes SUVmax compared to patients with histological PsP (6.71±2.03 vs 3.93±1.63; p=0.012). 40-50 minutes SUVmax cut-off of 4.46 provided 90% sensitivity and 80% specificity for differentiation of TP/mixed TP-PsP from PsP (AUC=0.88). Combining a 40-50 minutes SUVmax cut-off of 4.46 and an rCBVmax cut-off of 3.67 provided 100% sensitivity and 100% specificity for differentiating TP/mixed TP-PsP from PsP (AUC=1). Patients who demonstrated TP had a significantly higher 40-50 minutes SUVmax compared to patients with histological PsP (6.99±2.06 vs 3.93±1.63; p=0.008). A 40-50 minutes SUVmax cut-off of 4.66 provided 94% sensitivity and 80% specificity for differentiation of TP from PsP (AUC=0.89). Conclusion 18F-Fluciclovine PET uptake is positively correlated with viable tumor quantification on histology and can accurately differentiate PsP from TP in patients with GBM. Further independent studies are required to cross-validate these promising early results.

NEIM-03 A MULTICENTER PHASE 3 TRIAL IN PROGRESS: DIAGNOSTIC PERFORMANCE OF18F-FLUCICLOVINE PET FOR THE DETECTION OF RECURRENT BRAIN METASTASES AFTER RADIATION THERAPY (REVELATE)

INTRODUCTIONFollowing treatment of brain metastases, which can affect up to 40% of patients with cancer, patients will typically be closely monitored with serial brain magnetic resonance imaging (MRI) owing to the high likelihood of recurrence. The recommended follow-up modalities (CE-T1-weighted and FLAIR/T2-weighted MRI) have poor specificity, meaning that differentiation of true disease from treatment-related changes such as radiation necrosis can be difficult. Recent pilot studies have reported amino acid PET radiopharmaceutical, 18F-fluciclovine, to be potentially useful in discriminating tumor recurrence from treatment-related changes. This may potentially aid physicians in making confident diagnoses and inform subsequent treatment plans. METHODSREVELATE (NCT04410133) will evaluate the diagnostic performance of 18F-fluciclovine PET (read with conventional MRI for anatomical reference) for the detection of recurrent brain metastases in patients for whom MRI is equivocal. This multicenter, phase 3, prospective, open-label trial aims to enroll approximately 150 subjects from across 19 US sites with solid tumor brain metastases who have undergone radiation therapy, if they have a lesion considered equivocal on MRI that requires further confirmatory diagnostic procedures (either biopsy/neurosurgical intervention or clinical follow-up). Patients will undergo 18F-fluciclovine PET <42 days after the equivocal MRI and 1–21 days pre-biopsy/neurosurgical intervention. Clinical follow-up will occur for 6m post-18F-fluciclovine PET. Secondary objectives include evaluation of subject- and lesion-level 18F-fluciclovine negative and positive percent agreement (equivalent to specificity and sensitivity, respectively) for recurrent brain metastases, inter-reader and intra-reader agreement, and safety evaluations. Enrolment began in October 2020 and the trial is active but not recruiting at the time of submission.

Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression

PurposeTo investigate the potential of radiomics applied to static clinical PET data using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (FET) to differentiate treatment-related changes (TRC) from tumor progression (TP) in patients with gliomas.Patients and MethodsOne hundred fifty-one (151) patients with histologically confirmed gliomas and post-therapeutic progressive MRI findings according to the response assessment in neuro-oncology criteria underwent a dynamic amino acid PET scan using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (FET). Thereof, 124 patients were investigated on a stand-alone PET scanner (data used for model development and validation), and 27 patients on a hybrid PET/MRI scanner (data used for model testing). Mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated using the PET data from 20 to 40 min after tracer injection. Logistic regression models were evaluated for the FET PET parameters TBRmean, TBRmax, and for radiomics features of the tumor areas as well as combinations thereof to differentiate between TP and TRC. The best performing models in the validation dataset were finally applied to the test dataset. The diagnostic performance was assessed by receiver operating characteristic analysis.ResultsThirty-seven patients (25%) were diagnosed with TRC, and 114 (75%) with TP. The logistic regression model comprising the conventional FET PET parameters TBRmean and TBRmax resulted in an AUC of 0.78 in both the validation (sensitivity, 64%; specificity, 80%) and the test dataset (sensitivity, 64%; specificity, 80%). The model combining the conventional FET PET parameters and two radiomics features yielded the best diagnostic performance in the validation dataset (AUC, 0.92; sensitivity, 91%; specificity, 80%) and demonstrated its generalizability in the independent test dataset (AUC, 0.85; sensitivity, 81%; specificity, 70%).ConclusionThe developed radiomics classifier allows the differentiation between TRC and TP in pretreated gliomas based on routinely acquired static FET PET scans with a high diagnostic accuracy.

TBIO-11. The glutamine transporter and candidate diagnostic and therapeutic target SLC1A5 is associated with subtype-specific metabolic phenotypes and tumor prognosis in pediatric brain cancers

Abstract Glutamine transporters play an important role in supporting increased tumor nutritional demands relative to non-cancerous cells, often through overexpression of the solute carrier (SLC) family of membrane transporters. Preclinical studies in adult cancers demonstrate that targeting glutamine addiction via SLC1A5 inhibition results in growth-inhibitory and tumoricidal effects. Given their relatively higher expression in cancer versus normal brain tissue, SLC transporters represent compelling targets for molecularly-targeted radiation and application of available prognostic amino-acid PET imaging probes. However, the role of SLC transporters in pediatric brain cancers has yet to be investigated. We aimed to understand the relationship of SLC transporter expression with pediatric brain tumor subtypes and their potential prognostic significance using data from the Pediatric Brain Tumor Atlas (PBTA). Using the expression of amino acid transporter genes in ensemble survival models (Reactome: R-HSA-352230), we found that elevated expression of glutamine transporters (SLC1A5, SLC7A5, SLC7A11, SLC38A5, SLC38A3) predicted shorter progression-free survival (PFS) in low-grade gliomas (LGGs) and poorer overall survival in pediatric ependymomas, high-grade gliomas (HGGs), and medulloblastomas. We focused specifically on SLC1A5 given the availability of imaging probes (18 F-Fluoroglutamine and 18F-Fluciclovine) for the corresponding amino acid transporter (ASCT2). Through transcriptome-based consensus clustering, we found that supratentorial, RELA fusion-positive ependymomas and sonic hedgehog-activated medulloblastomas were over-represented among clusters expressing higher levels of SLC1A5 (p = 3.38e-7 and p = 2.18-26, respectively). Kaplan-Meier analysis found that higher expression of SLC1A5 was associated with shorter OS in ependymoma and medulloblastoma (p = 9.8e-4 and p = 0.032) and shorter PFS in LGG (p = 0.022). Gene set analysis showed higher expression and network rewiring of amino acid, lipid, and immune pathways in SLC1A5-high expressing clusters. Our work demonstrates that glutamine transporters, particularly SLC1A5, represent compelling targets in pediatric brain cancers that warrant further investigation for molecularly-targeted treatment and amino-acid PET imaging.

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors.

Simple SummaryMagnetic resonance spectroscopic imaging is an imaging method that can map the distribution of multiple biochemicals in the human brain in one scan. Using stronger magnetic fields, such as 7 Tesla, allows for higher resolution images and more biochemical maps. To test these results, we compared it to positron emission tomography, the established clinical standard for metabolic imaging. This comparison mainly looked at the overlap between regions with increased signal between both methods. We found that the molecules glutamine and glycine, only mappable at 7 Tesla, corresponded better to positron emission tomography than the commonly used choline.(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

Amino Acid PET Imaging with 18F-DOPA in the evaluation of Pediatric Brain Tumors.

Although MRI is the workhorse of brain tumor initial evaluation and follow-up, there is a growing amount of data recommending the incorporation of amino-acid PET imaging at different stages of the management of these patients. Recent nuclear medicine and neuro-oncology clinical practice recommendations support the use of amino-acid imaging in brain tumor imaging. Considering 18F-DOPA is FDA approved for the evaluation of parkinsonian syndromes, it could be used clinically for other valuable clinical indications such as brain tumor evaluations. This value seems to be well established in adults and has growing evidence for its use in pediatrics as well. We offer to present four pediatric brain tumor cases imaged with 18F-DOPA and review the literature.

The Utility of Conventional Amino Acid PET Radiotracers in the Evaluation of Glioma Recurrence also in Comparison with MRI.

Aim: In this comprehensive review we present an update on the most relevant studies evaluating the utility of amino acid PET radiotracers for the evaluation of glioma recurrence as compared to magnetic resonance imaging (MRI). Methods: A literature search extended until June 2020 on the PubMed/MEDLINE literature database was conducted using the terms “high-grade glioma”, “glioblastoma”, “brain tumors”, “positron emission tomography”, “PET”, “amino acid PET”, “[11C]methyl-l-methionine”, “[18F]fluoroethyl-tyrosine”, “[18F]fluoro-l-dihydroxy-phenylalanine”, “MET”, “FET”, “DOPA”, “magnetic resonance imaging”, “MRI”, “advanced MRI”, “magnetic resonance spectroscopy”, “perfusion-weighted imaging”, “diffusion-weighted imaging”, “MRS”, “PWI”, “DWI”, “hybrid PET/MR”, “glioma recurrence”, “pseudoprogression”, “PSP”, “treatment-related change”, and “radiation necrosis” alone and in combination. Only original articles edited in English and about humans with at least 10 patients were included. Results: Forty-four articles were finally selected. Conventional amino acid PET tracers were demonstrated to be reliable diagnostic techniques in differentiating tumor recurrence thanks to their high uptake from tumor tissue and low background in normal grey matter, giving additional and early information to standard modalities. Among them, MET–PET seems to present the highest diagnostic value but its use is limited to on-site cyclotron facilities. [18F]labelled amino acids, such as FDOPA and FET, were developed to provide a more suitable PET tracer for routine clinical applications, and demonstrated similar diagnostic performance. When compared to the gold standard MRI, amino acid PET provides complementary and comparable information to standard modalities and seems to represent an essential tool in the differentiation between tumor recurrence and other entities such as pseudoprogression, radiation necrosis, and pseudoresponse. Conclusions: Despite the introduction of new advanced imaging techniques, the diagnosis of glioma recurrence remains challenging. In this scenario, the growing knowledge about imaging techniques and analysis, such as the combined PET/MRI and the application of artificial intelligence (AI) and machine learning (ML), could represent promising tools to face this difficult and debated clinical issue.

What Does PET Imaging Bring to Neuro-Oncology in 2022? A Review.

Simple SummaryPositron emission tomography (PET) imaging is increasingly used to supplement MRI in the management of patient with brain tumors. In this article, we provide a review of the current place and perspectives of PET imaging for the diagnosis and follow-up of from primary brain tumors such as gliomas, meningiomas and central nervous system lymphomas, as well as brain metastases. Different PET radiotracers targeting different biological processes are used to accurately depict these brain tumors and provide unique metabolic and biologic information. Radiolabeled amino acids such as [18F]FDOPA or [18F]FET are used for imaging of gliomas while both [18F]FDG and amino acids can be used for brain metastases. Meningiomas can be seen with a high contrast using radiolabeled ligands of somatostatin receptors, which they usually carry. Unconventional tracers that allow the study of other biological processes such as cell proliferation, hypoxia, or neo-angiogenesis are currently being studied for brain tumors imaging.PET imaging is being increasingly used to supplement MRI in the clinical management of brain tumors. The main radiotracers implemented in clinical practice include [18F]FDG, radiolabeled amino acids ([11C]MET, [18F]FDOPA, [18F]FET) and [68Ga]Ga-DOTA-SSTR, targeting glucose metabolism, L-amino-acid transport and somatostatin receptors expression, respectively. This review aims at addressing the current place and perspectives of brain PET imaging for patients who suffer from primary or secondary brain tumors, at diagnosis and during follow-up. A special focus is given to the following: radiolabeled amino acids PET imaging for tumor characterization and follow-up in gliomas; the role of amino acid PET and [18F]FDG PET for detecting brain metastases recurrence; [68Ga]Ga-DOTA-SSTR PET for guiding treatment in meningioma and particularly before targeted radiotherapy.

Amino Acid and Proliferation PET/CT for the Diagnosis of Multiple Myeloma.

Multiple myeloma (MM) is a hematologic malignancy characterized by infiltration of monoclonal plasma cells in the bone marrow (BM). The standard examination performed for the assessment of bone lesions has progressed from radiographic skeletal survey to the more advanced imaging modalities of computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography/computed tomography (PET/CT). The Durie-Salmon PLUS staging system (upgraded from the Durie-Salmon staging system) applies 2-[18F]-fluoro-2-deoxy-glucose (18F-FDG) PET/CT, and MRI findings to the staging of MM, and 18F-FDG PET/CT has been incorporated into the International Myeloma Working Group (IMWG) guidelines for the diagnosis and staging of MM. However, 18F-FDG PET/CT has significant limitations in the assessment of diffuse BM infiltration and in the differentiation of MM lesions from inflammatory or infectious lesions. The potential of several new PET tracers that exploit the underlying disease mechanism of MM has been evaluated in terms of improving the diagnosis. L-type amino acid transporter 1 (LAT1), a membrane protein that transports neutral amino acids, is associated with cell proliferation and has strong ability to represent the status of MM. This review evaluates the potential of amino acid and proliferation PET tracers for diagnosis and compares the characteristics and accuracy of non-FDG tracers in the management of patients with MM.

A systematic review of amino acid PET in assessing treatment response to temozolomide in glioma.

The response assessment in neuro-oncology (RANO) criteria have been the gold standard for monitoring treatment response in glioblastoma (GBM) and differentiating tumor progression from pseudoprogression. While the RANO criteria have played a key role in detecting early tumor progression, their ability to identify pseudoprogression is limited by post-treatment damage to the blood-brain barrier (BBB), which often leads to contrast enhancement on MRI and correlates poorly to tumor status. Amino acid positron emission tomography (AA PET) is a rapidly growing imaging modality in neuro-oncology. While contrast-enhanced MRI relies on leaky vascularity or a compromised BBB for delivery of contrast agents, amino acid tracers can cross the BBB, making AA PET particularly well-suited for monitoring treatment response and diagnosing pseudoprogression. The authors performed a systematic review of PubMed, MEDLINE, and Embase through December 2021 with the search terms “temozolomide” OR “Temodar,” “glioma” OR “glioblastoma,” “PET,” and “amino acid.” There were 19 studies meeting inclusion criteria. Thirteen studies utilized [18F]FET, five utilized [11C]MET, and one utilized both. All studies used static AA PET parameters to evaluate TMZ treatment in glioma patients, with nine using dynamic tracer parameters in addition. Throughout these studies, AA PET demonstrated utility in TMZ treatment monitoring and predicting patient survival.

Feasibility on the Use of Radiomics Features of 11[C]-MET PET/CT in Central Nervous System Tumours: Preliminary Results on Potential Grading Discrimination Using a Machine Learning Model.

Background/Aim: Nowadays, Machine Learning (ML) algorithms have demonstrated remarkable progress in image-recognition tasks and could be useful for the new concept of precision medicine in order to help physicians in the choice of therapeutic strategies for brain tumours. Previous data suggest that, in the central nervous system (CNS) tumours, amino acid PET may more accurately demarcate the active disease than paramagnetic enhanced MRI, which is currently the standard method of evaluation in brain tumours and helps in the assessment of disease grading, as a fundamental basis for proper clinical patient management. The aim of this study is to evaluate the feasibility of ML on 11[C]-MET PET/CT scan images and to propose a radiomics workflow using a machine-learning method to create a predictive model capable of discriminating between low-grade and high-grade CNS tumours. Materials and Methods: In this retrospective study, fifty-six patients affected by a primary brain tumour who underwent 11[C]-MET PET/CT were selected from January 2016 to December 2019. Pathological examination was available in all patients to confirm the diagnosis and grading of disease. PET/CT acquisition was performed after 10 min from the administration of 11C-Methionine (401–610 MBq) for a time acquisition of 15 min. 11[C]-MET PET/CT images were acquired using two scanners (24 patients on a Siemens scan and 32 patients on a GE scan). Then, LIFEx software was used to delineate brain tumours using two different semi-automatic and user-independent segmentation approaches and to extract 44 radiomics features for each segmentation. A novel mixed descriptive-inferential sequential approach was used to identify a subset of relevant features that correlate with the grading of disease confirmed by pathological examination and clinical outcome. Finally, a machine learning model based on discriminant analysis was used in the evaluation of grading prediction (low grade CNS vs. high-grade CNS) of 11[C]-MET PET/CT. Results: The proposed machine learning model based on (i) two semi-automatic and user-independent segmentation processes, (ii) an innovative feature selection and reduction process, and (iii) the discriminant analysis, showed good performance in the prediction of tumour grade when the volumetric segmentation was used for feature extraction. In this case, the proposed model obtained an accuracy of ~85% (AUC ~79%) in the subgroup of patients who underwent Siemens tomography scans, of 80.51% (AUC 65.73%) in patients who underwent GE tomography scans, and of 70.31% (AUC 64.13%) in the whole patients’ dataset (Siemens and GE scans). Conclusions: This preliminary study on the use of an ML model demonstrated to be feasible and able to select radiomics features of 11[C]-MET PET with potential value in prediction of grading of disease. Further studies are needed to improve radiomics algorithms to personalize predictive and prognostic models and potentially support the medical decision process.

OL92 - Radiomics features of 11[C]-MET PET/CT in primary brain tumors: preliminary results on grading discrimination using a machine learning model

1096 Background: Nowadays Artificial Intelligence (AI) algorithms have demonstrated remarkable progress in image-recognition tasks and could be useful for the new concept of precision medicine in order to help physicians in the choice of therapeutic strategies for brain tumors. Previous data suggest that, in primary brain tumor, amino acid PET may demarcate more accurately the active disease than paramagnetic enhanced MRI that is the standard method of the evaluation in brain tumors and help in the evaluation of disease grading, as a fundamental basis for the correct clinical management of these patients. The aim of this study is to propose a radiomics workflow in order to create a predictive model on 11[C]-MET PET/CT scan images capable to discriminate between low-grade and high-grade primary brain tumors. Materials and Methods: in this retrospective study we selected fifty-six patients affected by primary brain tumor who underwent 11[C]-MET PET/CT from January 2016 to December 2019 at the Nuclear Medicine department of the Cannizzaro Hospital of Catania. Histological specimen the analysis was available in all patients in order to confirm the diagnosis and grading disease. PET/CT acquisition was performed after 10 minutes from the administration of 11C-Methionine (401-610 MBq) for a time acquisition of 15 minutes. 11[C]-MET PET/CT images were acquired using two scanners (24 patients on a Siemens scan and 32 patients on a GE scan). Then, LIFEx software was used to perform the segmentation and the extraction of features in order to identify the volume of interest (VOI) and to extract features of first, second, and third-order. LIFEx calculates 44 RF reflecting the VOI shape, the VOI voxel values, the histogram of VOI values, or the VOI textural content. A novel mixed descriptive-inferential sequential approach was used to identify a subset of relevant features that correlate with the outcome. A machine learning model based on discriminant analysis was tested in the evaluation of grading prediction (low vs high-grade) of 11[C]-MET PET/CT. Results: The machine learning model applicated in this study to stratify brain tumors as “low” and “high” grade showed discriminant texture features as follow: two features in fixed ROI respectively NGLDM Busyness (p-value: 0.1615) and GLZLM LZLGE (p-value 0.3207); three features in total volume respectively SHAPE Sphericity (p-value 0.0314), SHAPE Compacity (p-value 0.0215) and HISTO Kurtosis (p-value 0.0232). The results of performances, using a semi-automatic and user-independent segmentation process and an innovative feature extraction process on fixed ROI, showed a good performance in prediction of disease grade with an accuracy of 70.31% (AUC 64.13%) in all patients, of 80.51% (AUC 65.73%) in GE tomograph, of 84.98%(AUC 78.91%) in Siemens Tomograph. Using our model of machine learning with discriminant analysis the results of the performances were suboptimal in all patients group( 24 Siemens plus 32 GE) with an accuracy of 57.25 % and AUC of 58.51%. However in subgroup analysis, despite the low number of patients and different scanner, our model demonstrated good performances in the prediction of disease grade as follow: GE Scanner Accuracy 71.64 and AUC 62.8%; Siemens Scanner Accuracy 72,88% and AUC 78.91%. Conclusions: This preliminary study on radiomics features analysis of 11[C]-MET PET/CT suggests a possible value of Artificial Intelligence to assess primary brain tumors and to predict disease outcome in terms of grading discrimination at diagnosis. Further studies are needed to improve radiomics algorithms to personalize predictive and prognostic models and potentially support the medical decision process.

RADT-12. USE OF FDOPA PET FOR RADIATION THERAPY TARGETING IN GRADE 2 IDH MUTANT GLIOMA

Abstract BACKGROUND Low-grade, IDH mutant (IDHmt) gliomas typically do not enhance on MRI complicating radiotherapy (RT) target delineation. Amino acid PET using 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (FDOPA) has demonstrated avidity in IDHmt gliomas and may assist in RT planning for non-enhancing tumors. This study aims to compare conventional and FDOPA-defined target volumes in grade 2 IDHmt gliomas. METHODS In a prospective pilot study, patients underwent MRI and FDOPA PET using a 3T MRI/PET system followed by standard therapy. Gross tumor volumes (GTV) included the T2/FLAIR abnormality and surgical cavity; clinical target volumes (CTV) included a 1 cm expansion constrained anatomically. Metabolic target volumes (MTVs) were generated using the FDOPA SUV &amp;gt; 1.5-fold normal brain isocurve. Union of GTV and MTV generated a fusion GTV (fGTV); expanding fGTV by 1 cm yielded the fusion CTV (fCTV). Target volumes were compared volumetrically with overlap (Dice coefficient) and surface metrics (Hausdorff distance). Medians are reported with ranges. RESULTS Four patients with grade 2 IDHmt glioma (3 1p/19q codeleted oligodendrogliomas, 1 non-codeleted astrocytoma) received MRI/PET before treatment. All oligodendrogliomas exhibited FDOPA avidity; the astrocytoma showed no avidity. GTV and CTV measured 16.1 cc (4.9 - 82.2 cc) and 76.7 cc (29.5 - 256.1 cc), respectively. The MTV volume outside of GTV was 0.8 cc (0.2 – 6.1 cc), but was covered in each case by the CTV. Addition of FDOPA increased fGTV and fCTV volumes by 5.4% and 17.5%, respectively. Dice coefficient and Hausdorff distances for GTV vs fGTV were 0.96 (0.95 - 0.99) and 11.2 mm (10.0 – 11.9 mm), respectively, and for CTV vs fCTV were 0.87 (0.81 – 0.95) and 10.2 mm (10.0 - 11.0), respectively. CONCLUSIONS FDOPA PET identified tracer-avid regions outside of MRI-defined GTVs in a group of IDHmt gliomas. FDOPA PET provides useful metabolic information for RT planning and warrants further investigation.

NIMG-27. REGORAFENIB RESPONSE ASSESSMENT USING FET PET IN PATIENTS WITH PROGRESSIVE GLIOMA

Abstract BACKGROUND The REGOMA phase 2 trial showed an encouraging overall survival benefit of the multikinase inhibitor regorafenib in glioblastoma patients at first progression. We used O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET for the early assessment of response to regorafenib in patients with progressive glioma in an advanced disease stage. METHODS Thirty patients with progressive glioma were treated according to the REGOMA trial and prospectively followed. FET PET and MRI were performed at baseline and after the second cycle of regorafenib. Static PET parameters such as maximum and mean tumor-to-brain ratios (TBRmax, TBRmean) and metabolic tumor volumes (MTV) were calculated. Threshold values of FET PET parameters to predict a response were established by ROC analyses using an overall survival of ≥ 6 months as reference. The predictive value of FET PET parameters and their changes concerning overall survival was subsequently evaluated using the Kaplan-Meier test. MRI changes were evaluated according to the RANO criteria. RESULTS Up to now, 18 of 30 patients (glioblastoma, 83%; age range, 24-71 years) were eligible for data evaluation. The median number of tumor relapses before regorafenib was 2 (range, 1-4). During regorafenib (median cycles, 4; range, 2-9 cycles), CTCAE grade 3 or 4 side effects occurred in 56% and 11%, respectively. The median overall survival was 6 months (range, 3-18 months). After two cycles of regorafenib, a TBRmean reduction of 13% predicted a significantly longer overall survival (12 vs. 6 months; P=0.034). In contrast, MRI changes evaluated according to RANO criteria (i.e., Stable Disease or Partial Response vs. Progressive Disease) were not predictive (11 vs. 8 months; P=0.644). CONCLUSION Data suggest that amino acid PET using the tracer FET may be clinically valuable for identifying responders to regorafenib early after treatment initiation.