From 2013-2019, we retrospectively identified patients who (i) were diagnosed with newly diagnosed and histomolecularly characterized IDH-wildtype astrocytic glioma not eligible for complete resection, showed (ii) minimal (i.e., ≤ 5 mL) or absent MRI contrast enhancement, and (iii) had undergone MR and FET PET imaging before initiation of radiotherapy.
According to these search criteria, we identified 18 adult patients (mean age, 51 ± 14 years; age range, 24-66 years; 6 females). Due to tumor localization in deep or eloquent brain areas, ten patients underwent stereotactic biopsy. In the remaining eight patients, only partial resection could be achieved. The patients either had no contrast enhancement (n=8) or minimal contrast enhancement on MRI (n=10).
Seventeen of 18 patients were treated according to the EORTC/NCIC 22981/26981 trial with radiotherapy and concomitant temozolomide chemotherapy followed by maintenance temozolomide chemotherapy over six cycles . Fourteen patients completed radiotherapy with concomitant and maintenance temozolomide chemotherapy over six cycles. One patient was treated with radiotherapy only.
During follow-up, contrast-enhanced conventional MRI was performed every 8-12 weeks. Furthermore, patients were assessed by neurological examination, and the Karnofsky Performance Score was determined every 8-12 weeks during the treatment and after treatment completion. The patients’ outcome was evaluated by calculating the PFS and OS. The PFS was defined as the time interval between histomolecularly confirmed glioma diagnosis and tumor progression according to the RANO criteria . The OS was defined as the time interval between histomolecularly confirmed glioma diagnosis and death. The median follow-up time was 13.7 months (range, 6.5-31.4 months). Table 1 provides a summary of the patients’ characteristics.
Following the International Standardized Brain Tumor Imaging Protocol (BTIP) , MR imaging was performed using a 1.5 T or 3.0 T MRI scanner with a standard head coil before and after administration of a gadolinium-based contrast agent (0.1 mmol/kg body weight). The sequence protocol comprised 3D isovoxel T1-weighted, 2D T2-weighted, and 2D fluid-attenuated inversion recovery-weighted (FLAIR) sequences. Volumes of contrast enhancement and non-enhancing FLAIR-signal abnormality were automatically segmented using the HD-GLIO brain tumor segmentation tool [21, 22]. The automatic segmentation results were visually validated and manually revised, if necessary, using the software PMOD (Version 3.9, PMOD Technologies Ltd., Zurich, Switzerland).
FET PET Imaging
As described previously, the amino acid FET was produced via nucleophilic 18F-fluorination with a radiochemical purity of greater than 98%, specific radioactivity greater than 200 GBq/µmol, and a radiochemical yield of about 60% . According to national and international guidelines for brain tumor imaging using labeled amino acid analogs , all patients fasted for at least four hours before the PET measurements. All patients underwent a dynamic PET scan from 0 to 50 minutes post-injection of 3 MBq of FET per kg of body weight. PET imaging was performed either on an ECAT Exact HR+ PET scanner (n=7 patients) in 3-dimensional mode (Siemens, Erlangen, Germany) (axial field-of-view, 15.5 cm) or simultaneously with 3T MR imaging using a BrainPET insert (n=11 patients) (Siemens, Erlangen, Germany). The BrainPET is a compact cylinder that fits into the bore of the Magnetom Trio MR scanner (axial field of view, 19.2 cm) .
Iterative reconstruction parameters were 16 subsets, six iterations using the OSEM algorithm for ECAT HR+ PET scanner and two subsets, 32 iterations using the OP-OSEM algorithm for the BrainPET. Data were corrected for random, scattered coincidences, dead time, and motion for both systems. Attenuation correction for the ECAT HR+ PET scan was based on a transmission scan, and for the BrainPET scan on a template-based approach . The reconstructed dynamic data set consisted of 16 time frames (5 x 1 minute; 5 x 3 minutes; 6 x 5 minutes) for both scanners.
To optimize comparability of the results related to the influence of the two different PET scanners, reconstruction parameters, and post-processing steps, a 2.5 mm 3D Gaussian filter was applied to the BrainPET data before further processing, resulting in an image resolution of approximately 4 mm (image resolution of the ECAT HR+ PET scanner, approximately 6 mm). In phantom experiments using spheres of different sizes to simulate lesions, this filter kernel demonstrated the best comparability between PET data obtained from the ECAT HR+ PET and the BrainPET scanner .
FET PET Data Analysis
FET PET data analysis was performed as described previously . In brief, for the evaluation of FET data, summed PET images over 20-40 minutes post-injection were used. Mean amino acid uptake in the tumor was determined by a 2-dimensional auto-contouring process using a tumor-to-brain ratio (TBR) of 1.6 as described previously [9, 28]. For calculating the maximal amino acid uptake, a circular ROI with a diameter of 1.6 cm was centered on the maximal tumor uptake . Maximum and mean TBRs (TBRmax, TBRmean) were calculated by dividing the mean standardized uptake value (SUV) of the tumor ROIs by the mean SUV of healthy brain tissue. The FET metabolic tumor volume (MTV) was determined by a 3-dimensional auto-contouring process using a TBR of 1.6 or more using the software PMOD (Version 3.9, PMOD Technologies Ltd., Zurich, Switzerland).
As described previously , time-activity curves (TAC) of FET uptake in the tumor were generated by applying a spherical volume-of-interest (VOI) with a volume of 2 mL centered on the maximal tumor uptake to the entire dynamic dataset. A reference TAC was generated by placing a reference ROI in the unaffected brain tissue (as described above). For TAC evaluation, the time-to-peak (TTP; defined as the time in minutes from the beginning of the dynamic acquisition up to the lesion’s maximum SUV) was calculated. In cases with constantly increasing FET uptake without identifiable peak uptake, we defined the end of the dynamic PET acquisition as TTP. Furthermore, the TAC slope in the late phase of FET uptake was assessed by fitting a linear regression line to the late phase of the curve (20-50 minutes post-injection). The slope was expressed as the change of the SUV per hour. This procedure enables a more objective evaluation of kinetic data than a TAC assignment to FET uptake patterns .
Neuropathological Tumor Classification and Analysis of Molecular Markers
All tumors were histomolecularly classified according to the World Health Organization (WHO) Classification of Tumors of the Central Nervous System of 2016 For molecular biomarker analysis, tumor DNA was extracted from formalin-fixed and paraffin-embedded tissue samples with a histologically estimated tumor cell content of 80% or more. For assessing the isocitrate dehydrogenase (IDH) mutation status, the presence of an IDH1-R132H mutation was evaluated by immunohistochemistry using a mutation-specific antibody in a standard immunohistochemical staining procedure as reported [29, 30]If immunostaining for IDH1-R132H remained negative, the mutational hot-spots at codon 132 of IDH1 and codon 172 of IDH2 were directly sequenced as reported [31, 32]. The MGMT promoter methylation status was assessed by methylation-specific PCR, as described elsewhere .
Descriptive statistics are provided as mean and standard deviation or median and range. The prognostic value of the FET PET parameters (TBRmax, TBRmean, and MTV), as well as dynamic FET PET parameters (TTP, slope), was assessed by receiver operating characteristic (ROC) curve analyses using a favorable PFS and OS as reference. A favorable outcome was defined as a PFS ≥ 7.0 months and an OS ≥ 15.0 months. Decision cut-off was considered optimal when the product of paired values for sensitivity and specificity reached its maximum. When this product was identical for different thresholds, the threshold resulting in the best survival estimate was selected. As a measure of the test’s diagnostic quality, the area under the ROC curve (AUC), its standard error, and significance level were determined. Only patients with uncensored survival data were included in ROC analyses for the evaluation of the diagnostic performance.
Univariate survival analyses were performed using Kaplan-Meier estimates. The log-rank test was used for comparison of the median PFS and OS between the subgroups. Multivariate Cox proportional hazards models were constructed to test the relationship between MTV and other decisive prognostic factors (i.e., age and MGMT promoter methylation) and the contrast-enhancing volume for survival prediction. Hazard ratios (HR) and their 95%-confidence intervals (CI) were calculated. P-values of 0.05 or less were considered statistically significant. For statistical analyses and creation of figures R software was used .