Objectives: This study sought to assess 18 F-fludarabine ( 18 F-FLUDA) PET/ CT's ability in differentiating primary central nervous system lymphomas (PCNSLs) from glioblastoma multiformes (GBMs). Patients and Methods: Patients harboring either PCNSL (n = 8) before any treatment, PCNSL treated using corticosteroids (PCNSLh; n = 10), or GBM (n = 13) were investigated with conventional MRI and PET/CT, using 11 C-MET and 18 F-FLUDA. The main parameters measured with each tracer were SUV T and T/N ratios for the first 30 minutes of 11 C-MET acquisition, as well as at 3 different times after 18 F-FLUDA injection. The early 18 F-FLUDA uptake within the first minute of injection was equally considered, whereas this parameter was combined with the later uptakes to obtain R FLUDA 2 and R FLUDA 3 ratios. Results: No significant differences in 11 C-MET uptakes were observed among PCNSL, PCNSLh, and GBM. With 18 F-FLUDA, a clear difference in dynamic GBM uptake was observed, which decreased over time after an early maximum, as compared with that of PCNSL, which steadily increased over time, PCNSLh exhibiting intermediate values. The most discriminative parameters consisting of R FLUDA 2 and R FLUDA 3 integrated the early tracer uptake (first 60 seconds), thereby provided 100% specificity and sensitivity. Conclusions: 18 F-FLUDA was shown to likely be a promising radiopharmaceutical for differentiating PCNSL from other malignancies, although a pretreatment with corticosteroids might compromise this differential diagnostic ability. The diagnostic role of 18 F-FLUDA should be further investigating, along with its potential of defining therapeutic strategies in patients with PCNSL, while assessing the treatments' effectiveness.
The study of plastic and energy metabolism and their correlation with various histologic types of brain gliomas. Assessment of heterogeneity tumor structure and adjacent brain tissues by comparing MRI and 11C-methionine and 18F-fluorodeoxyglucose PET/CT data. Materials and methods. 52 patients (M/F 27/25, average age 48±12 years) with gliomas were enrolled in this study: glioblastoma (n = 19), anaplastic astrocytoma (n=9), diffuse astrocytoma (n=9), anaplastic oligodendroglioma (n=6), oligodendroglioma (n=6). Research protocol consisted from MRI before (T2, T2-FLAIR, 3DT1 (FSPGR) and after contrast enhancement (2DT1 (SE)) and dynamic MET and FDG PET/CT.Quantification parameters were: tumor to normal index (T/N) at last 10 min of time-activity curve (reflects the activity of metabolic processes), T/N in first peak of maximum uptake (Pmax) during first 60sec of study (reflects delivery level of radiopharmaceutical agent). Measurements were made in three areas: 1 -tumor core, 2 -edema/infiltration, 3 -intact brain tissue in close vicinity to the tumor borders (outside the T2-FLAIR hyperintensity zone). Сomparison was made between areas 1 and 2, 2and 3, and with intact brain tissue reference; MET and FDG accumulation correlations were studied.Results. Significant differences in T/N MET between areas 1 and 2 were obtained in all gliomas (p <0.05). Pmax MET differed only in glioblastomas (p <0.0001) and oligodendrogliomas (p <0.05), which correlated with the high level of vascularization of these tumor types. T/N FDG significantly differed between area 2 and 3 (p <0.05), which might allow to evaluate the boundaries of infiltrative growth of glioma, with mandatory comparison with MRI. Strong stable correlations of plastic and energy metabolism (as well as high level of radiopharmaceutical agent delivery) in the core of astrocytomas (Grade II-III) (Rs 0.8, p <0.05) and edema/infiltration area around of glioblastomas (Rs 0.5, p = 0, 02) were found and proved the evolutionary theory of glioma growth. Conclusion.The patterns of MET/FDG distribution as well as plastic and energy metabolism correlations in different tumor areas (core and edema/infiltration) and intact brain tissue in close vicinity to the tumor borders bring us closer to understanding the fundamental metabolic processes of brain gliomas.
Oxygen metabolism is a key factor in the life of a living organism. The article is the first part of a review of methods for measuring oxygen metabolism.Purpose. The aim of this review is to present an insight into the evolution of methods for measuring oxygen metabolism in a way from global to local measurement of brain perfusion. The role of the 15O isotope as the “gold standard” for measuring oxygen metabolism using positron emission tomography (PET) is described. We also provide a case report of brain tumor perfusion measurements from our clinic.Materials and methods. More than 200 Pubmed publications were studied with the keywords “positron emission tomography + O-15”. Relevant publications that do not contain these keywords or contain them in a different wording were also analyzed. A clinical case of a brain tumor perfusion using CT perfusion, MR-ASL and PET with H215O is provided.Results. The evolution of methods for measuring perfusion, oxygen extraction, and oxygen metabolism, is described. More than 50 papers are cited depicting key advances in measurement technologies. Examples of the use of PET with H215O in fundamental research and clinical practice are given.Conclusion. The obvious value of oxygen-isotope PET data is combined with the invasiveness (in some cases), technical complexity and high cost of the procedure. The second part of the review will be devoted to alternative methods for measuring oxygen metabolism, which are developing in the 21st century and which are intended for wide clinical use.
Nowadays, the quantitative analysis of PET/CT data in patients with glioblastoma is not strictly standardized in the clinic and does not exclude the human factor. This study aimed to evaluate the relationship between the radiomic features of glioblastoma 11C-methionine PET images and the tumor-to-normal brain (T/N) ratio determined by radiologists in clinical routine. PET/CT data were obtained for 40 patients (mean age 55 ± 12 years; 77.5% men) with a histologically confirmed diagnosis of glioblastoma. Radiomic features were calculated for the whole brain and tumor-containing regions of interest using the RIA package for R. We redesigned the original RIA functions for GLCM and GLRLM calculation to reduce computation time significantly. Machine learning over radiomic features was applied to predict T/N with the best median correlation between the true and predicted values of 0.73 (p = 0.01). The present study showed a reproducible linear relationship between 11C-methionine PET radiomic features and a T/N indicator routinely assessed in brain tumors. Radiomics enabled utilizing texture properties of PET/CT neuroimaging that may reflect the biological activity of glioblastoma and can potentially augment the radiological assessment.
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