Prediction and Visualization of Non-Enhancing Tumor in Glioblastoma via T1w/T2w-Ratio Map

One of the challenges in glioblastoma (GBM) imaging is to visualize non-enhancing tumor (NET) lesions. The ratio of T1- and T2-weighted images (rT1/T2) is reported as a helpful imaging surrogate of microstructures of the brain. This research study investigated the possibility of using rT1/T2 as a surrogate for the T1- and T2-relaxation time of GBM to visualize NET effectively. The data of thirty-four histologically confirmed GBM patients whose T1-, T2- and contrast-enhanced T1-weighted MRI and 11C-methionine positron emission tomography (Met-PET) were available were collected for analysis. Two of them also underwent MR relaxometry with rT1/T2 reconstructed for all cases. Met-PET was used as ground truth with T2-FLAIR hyperintense lesion, with >1.5 in tumor-to-normal tissue ratio being NET. rT1/T2 values were compared with MR relaxometry and Met-PET. rT1/T2 values significantly correlated with both T1- and T2-relaxation times in a logarithmic manner (p < 0.05 for both cases). The distributions of rT1/T2 from Met-PET high and low T2-FLAIR hyperintense lesions were different and a novel metric named Likeliness of Methionine PET high (LMPH) deriving from rT1/T2 was statistically significant for detecting Met-PET high T2-FLAIR hyperintense lesions (mean AUC = 0.556 ± 0.117; p = 0.01). In conclusion, this research study supported the hypothesis that rT1/T2 could be a promising imaging marker for NET identification.

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.

NI-13 Prediction of outcome at the time of discontinuing TMZ-adjuvant therapy in IDH-mutant lower grade glioma using 11C-methinine PET

Purpose: This study aimed to clarify whether positron emission tomography with 11C-methyl-L-methionine (11C-met PET) can predict consequential outcomes at the time of discontinuing temozolomide (TMZ)-adjuvant chemotherapy in patients with residual isocitrate dehydrogenase gene (IDH)-mutant lower-grade glioma.Methods: In 30 patients showing residual lesions of IDH-mutant lower grade glioma (16 with diffuse astrocytoma and 14 with anaplastic astrocytoma), we performed 11C-met PET, and calculated the tumor-to-normal brain tissue ratio of standardized uptake values (SUVT/N) at the time of discontinuing TMZ-adjuvant chemotherapy. We determined cutoff values to predict tumor relapse using the receiver operating characteristic curve for various prognostic factors including age, Karnofsky performance scale, number of courses of therapy, residual tumor size, and SUVT/N. The promotor methylation status of O6-methylguanine-DNA methyl-transferase gene (MGMT) was assessed using methylation-specific polymerase chain reaction. Progression-free survival (PFS) was compared between groups divided by cutoff values. Uni- and multivariate analyses were conducted using log-rank testing and Cox regression analysis, respectively.Results: Univariate analysis identified MGMT methylation status (p = 0.04) and an SUVT/N of 1.27 (p = 0.02) as predictors of PFS after TMZ discontinuation. In multivariate analysis, both unmethylated MGMT and SUVT/N ≥ 1.27 remained as strong predictors of unfavorable outcome. Conclusion: The present study suggested that 11C-met PET allows prediction of outcomes comparable to MGMT promotor methylation status at the time of discontinuing TMZ-adjuvant chemotherapy in patients with residual IDH-mutant lower-grade glioma.

COT-30 Effect of tumor resection in 11C methionine accumulation area on survival in patients with glioblastoma

Aim: The amount of tumor excised in an area enhanced by contrast medium on magnetic resonance imaging strongly affects the survival time of patients with glioblastoma. We investigated the effect of the amount of tumor removal in the 11C methionine (MET) accumulation site on overall survival(OS). Methods: Twenty-six patients (15 male; mean age, 68.9 years) with a diagnosis of glioblastoma who underwent tumor resection at Kizawa Memorial Hospital between June 1, 2015 and August 30, 2021 underwent MET-positron emission tomography (MET-PET) before and after the operation. In a comparison of MET-PET before and after tumor resection, the tumor-to-normal (T/N) ratio reduction (ΔT/N), MET accumulation area reduction (MET-extent of resection [EOR]), and the residual MET accumulation volume (MET-residual tumor volume [RTV]) were calculated. The relationship between these MET-related parameters associated with tumor resection and OS was investigated via univariable analysis. Results: Univariate analysis revealed that ΔT/N was significantly associated with OS (hazard ratio [HR]: 0.98; 95% confidence interval [CI]: 0.97–0.99; p=0.02). MET-RTV was also significantly associated with OS (HR: 1.01; 95% CI: 0.98–1.02; p=0.73) Conversely, MET-EOR (HR: 0.99; 95% CI: 0.97–1.01; p=0.06) was not significantly associated with OS. Conclusions: Aggressive surgical resection of the MET accumulation site significantly prolongs survival in patients with glioblastoma.

NI-3 Magnetic resonance relaxometry for tumor cell density imaging for glioma: An exploratory study via 11C-methionine PET and its validation via stereotactic tissue sampling

Objective: While visualization of non-enhancing tumors for glioma is crucial for planning the most appropriate surgical or non-surgical treatment of the disease, current MRI cannot achieve this goal. This study aims to test the hypothesis that quantitative and diffusion MRI can estimate tumor burden with the brain. Materials and Methods: Study 1: Ten patients who have undergone Methionine PET (Met-PET), quantitative MRI (qMRI), and diffusion MRI (DWI) were included for analysis. A cut-off of a tumor-to-normal ratio (T/Nr) 1.5 was set on Met-PET, and the values from qMRI and DWI were compared. Study 2: Seventy-nine stereo-tactically sampled tissues from 22 glioma patients were correlated with Met-PET, qMRI, and DWI measurements regarding tumor cell density. qMRI acquisition: Imaging was performed on either a 1.5 or 3 T MR scanner (Prisma or Aera; Siemens Healthcare, Erlangen, Germany). T1-relaxometry was achieved by first acquiring MP2RAGE images, then converting those images into T1-relaxation time maps. At the same time, T2-relaxometry was achieved by first acquiring multi-echo T2-weighted images and then converting those images into T2-relaxation time maps, with both relaxometries performed via Bayesian inference modeling (Olea Nova+; Canon Medical Systems, Tochigi, Japan). Results: Study 1 revealed that regions of 1850ms &lt; T1-relaxation time &lt; 3200ms and 115ms &lt; T2-relaxation time &lt; 225ms tended to be Met-PET T/Nr &gt; 1.5. DWI was not useful to separate areas between low and high Met-PET. Study 2 showed that regions of 1850ms &lt; T1-relaxation time &lt; 3200ms showed high tumor cell density than other areas (p=0.04). Conclusions: Our results supported the hypothesis that qMRI is useful for predicting the tumor load within the brain among glioma patients. T1-relaxation time was notably useful for this means. On the other hand, ADC measured from DWI was limited for tumor load prediction.

NI-8 Molecular diagnostic prediction combining T2-FLAIR mismatch sign, calcification, and methionine PET in grade II and III gliomas

Background: The 2016 WHO Classification classified grade II and III gliomas into three molecular subtypes depending on the presence of IDH mutation and 1p/19q codeletion. We combined T2-FLAIR mismatch sign, tumor calcification, and methionine PET uptake to examine whether molecular diagnosis could be predicted. Methods: 53 grade II and III glioma patients with preoperative MRI, CT, and MET-PET who underwent surgical resection or biopsy during 2000–2019 were included in this study. Out of the 53 cases, astrocytic tumors (A group: IDH-mutant, 1p19q non-codeleted) were 17, oligodendroglial tumors (O group: IDH-mutant, 1p19q codeleted) were 15, and IDH wild tumors (W group) were 21. MR and CT scans were evaluated by 3 independent reviewers to assess presence/absence of T2-FLAIR mismatch sign and calcification in the tumor, respectively. The tumor-to-normal (T/N) ratio of methionine uptake was calculated by dividing the maximum standardized uptake value (SUV) for the tumor by the mean SUV of the normal brain. Results: Out of the 53 cases, T2-FLAIR mismatch sign was present in 6 cases in group A and 9 cases in group W (p=0.008). Calcification in tumor was present in 2 cases in group A, 7 cases in group O, and 3 cases in group W (p=0.046). In the T2-FLAIR mismatch-positive cases, assuming MET-PET T/N&gt;1.401 was group W and &lt;1.401 was group A, sensitivity was 100% and specificity was 67%. In the T2-FLAIR mismatch-negative and calcification-positive cases, assuming those group O, the diagnostic predictive value was 70%. In the T2-FLAIR mismatch-negative and calcification-negative cases, assuming MET-PET T/N&gt;2.349 was group W and &lt;2.349 was group A or O, sensitivity was 60% and specificity was 94%. Conclusions: Combined diagnostic prediction of T2-FLAIR mismatch, calcification, and MET-PET T/N may be useful for preoperative molecular diagnosis of grade II and III gliomas.

NI-14 estimation of property of MRI non-contrast enhanced lesion of Glioblastoma using T1/T2 ratio

Background: Tumor mass of glioblastoma is considered to exist beyond gadolinium-enhancing lesion into T2/FLAIR-high intensity lesions (T2/FL-HIL) on MRI. However, it is challenging to differentiate non-enhancing tumor region (NET) from pure brain edema for T2/FL-HIL. The T1/T2 ratio (rT1/T2) is an MRI metric considered to semi-quantify the tissue relaxation time on MRI. This research tested the hypothesis that rT1/T2 is useful for identifying NET within T2/FL-HIL by comparing it with 11C-methionine positron emission tomography (MET-PET). Method: Forty-six glioblastoma (GBM) patients at Osaka International Cancer Institute and Osaka University Hospital where T1-, T2- and contrast-enhanced T1-weighted MRI and MET-PET were available were included in this study. rT1/T2 maps were obtained after signal corrections were performed, as reported previously. Region-of-interests (ROIs) were defined within T2/FL-HILs beyond the gadolinium-enhanced lesion. MET-PET and rT1/T2 maps were co-registered to the same coordinate system, and the relationship between methionine uptake and rT1/T2 values was examined in a voxel-wise manner.ResultApproximately three million voxels were included for analysis. Lesions with methionine uptake higher than 5.0 on T/N showed 0.7 &lt rT1/T2 &lt 0.98. For those with methionine uptake higher than 3.0, rT1/T2 was between 0.70 and 1.04.DiscussionThis report suggested that rT1/T2 represents histological characteristics of the glioblastoma within T2/FL-HIL. It also indicated that rT1/T2 could be a useful biomarker for detecting NET within T2/FL-HIL for glioblastoma.

Fractal analysis of 11C-methionine PET in patients with newly diagnosed glioma

Background The present study tested the possible utility of fractal analysis from l-[methyl-11C]-methionine (MET) uptake in patients with newly diagnosed gliomas for differentiating glioma, especially in relation to isocitrate dehydrogenase 1 (IDH1) mutation status, and as compared with the conventional standardized uptake value (SUV) parameters. Methods Investigations of MET PET/CT were performed retrospectively in 47 patients with newly diagnosed glioma. Tumors were divided into three groups: lower grade glioma (IDH1-mutant diffuse astrocytoma and IDH1-mutant anaplastic astrocytoma), higher grade glioma (IDH1-wildtype diffuse astrocytoma and IDH1-wildtype anaplastic astrocytoma), and glioblastoma. The fractal dimension for tumor, maximum SUV (SUVmax) for tumor (T) and mean SUV for normal contralateral hemisphere (N) were calculated, and the tumor-to-normal (T/N) ratio was determined. Metabolic tumor volume (MTV) and total lesion MET uptake (TLMU) were also measured. Results There were significant differences in SUVmax (p = 0.006) and T/N ratio (p = 0.02) between lower grade glioma and glioblastoma. There were no significant differences among any of the three groups in MTV or TLMU. Significant differences were obtained in the fractal dimension between lower grade glioma and higher grade glioma (p = 0.006) and glioblastoma (p < 0.001). Conclusions The results of this preliminary study in a small patient population suggest that the fractal dimension using MET PET in patients with newly diagnosed gliomas is useful for differentiating glioma, especially in relation to IDH1 mutation status, which has not been possible with SUV parameters.

Influence of 11C-MET PET acquisition time for differential diagnosis of human brain gliomas

The aim of this work was to study the effect of the reduced acquisition time of PET 11C-MET examination on the quality of primary brain tumors differential diagnosis. 57 patients with histologically verified diagnoses were recruited (glioblastoma n=20, anaplastic astrocytoma n=11, diffuse astrocytoma n=11, oligodendroglioma n=9 and anaplastic oligodendroglioma n=6). The scan time was varied in the range of 2-20 min. Our study demonstrated that in the case of intravenous administration of 11C-MET simultaneously with the start of scanning, the quality of primary gliomas differential diagnosis does not depend on the scan time. Therefor it becomes possible increasing the number of patients and reducing the acquisition time. The T/N60 ratio (T/N ratio measured in the first 60 seconds after 11C-MET intravenous injection) is equally successful parameter for glioma differential diagnosis as the traditional T/N ratio.

Dynamic 11C-Methionine PET-CT: Prognostic Factors for Disease Progression and Survival in Patients with Suspected Glioma Recurrence

Purpose: The prognostic evaluation of glioma recurrence patients is important in the therapeutic management. We investigated the prognostic value of 11C-methionine PET-CT (MET-PET) dynamic and semiquantitative parameters in patients with suspected glioma recurrence. Methods: Sixty-seven consecutive patients who underwent MET-PET for suspected glioma recurrence at MR were retrospectively included. Twenty-one patients underwent static MET-PET; 46/67 underwent dynamic MET-PET. In all patients, SUVmax, SUVmean and tumour-to-background ratio (T/B) were calculated. From dynamic acquisition, the shape and slope of time-activity curves, time-to-peak and its SUVmax (SUVmaxTTP) were extrapolated. The prognostic value of PET parameters on progression-free (PFS) and overall survival (OS) was evaluated using Kaplan–Meier survival estimates and Cox regression. Results: The overall median follow-up was 19 months from MET-PET. Recurrence patients (38/67) had higher SUVmax (p = 0.001), SUVmean (p = 0.002) and T/B (p < 0.001); deceased patients (16/67) showed higher SUVmax (p = 0.03), SUVmean (p = 0.03) and T/B (p = 0.006). All static parameters were associated with PFS (all p < 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmaxTTP (p = 0.02, p = 0.01, respectively). SUVmaxTTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmaxTTP were predictive for PFS (all p < 0.05); SUVmaxTTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmaxTTP remained significant for PFS (p = 0.03). Conclusion: Semiquantitative parameters and SUVmaxTTP were associated with clinical outcomes in patients with suspected glioma recurrence. Dynamic PET-CT acquisition, with static and kinetic parameters, can be a valuable non-invasive prognostic marker, identifying patients with worse prognosis who require personalised therapy.