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Vikhrova NB, Kalaeva DB, Tyurina AN, Belyaev AY, Danilov GV, Pronin IN. [PET/CT with 11C-methionine in assessment of brain glioma metabolism]. ZHURNAL VOPROSY NEIROKHIRURGII IMENI N. N. BURDENKO 2024; 88:63-69. [PMID: 38334732 DOI: 10.17116/neiro20248801163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
OBJECTIVE To study 11C-methionine (MET) metabolism in gliomas using CNS tumor biobank imaging data. MATERIAL AND METHODS MRI and 11C-MET PET/CT were performed in 225 patients (49±14 years, M/F=84/101) according to standard protocols with analysis of 11C-MET accumulation index and volumetric parameters (V_FLAIR, V_PET and V_PET/FLAIR). These results were compared with molecular genetic testing and 2-year overall survival. RESULTS We examined 225 patients with gliomas (97 glioblastomas, 70 astrocytomas, 58 oligodendrogliomas). Accumulation index and volume of 11C-MET in glioblastomas were significantly higher in the general group (AI=2.90, Se 69%, Sp 76%, AUC 0.76; V_PET=24.3 cm3, Se 67%, Sp 60%, AUC 0.65; V_PET/FLAIR 0.46, Se 60%, Sp 69%, AUC 0.67) and within the group of astrocytomas (AI=2.93, Se 68%, Sp 89%, AUC 0.84; V_PET=8.06 cm3, Se 91%, Sp 35%, AUC 0.66; V_PET/FLAIR 0.27, Se 77%, Sp 60%, AUC 0.71). The median 2-year overall survival in patients with glioblastomas was 13 months that was significantly lower compared to IDH «+» gliomas (p<0.0001). There was a relationship between high accumulation index of 11C-MET and shorter overall survival in patients with glioblastomas. Significantly higher AI >3.59 (Se 89%, Sp 67%, AUC 0.79) was additionally obtained in subgroup of patients with glioblastomas >50 years (n=34) for EGFR «+» tumors. CONCLUSION We found variable 11C-MET metabolism in WHO 2021 gliomas and confirmed significant difference in metabolic activity and volume of 11C-MET accumulation in glioblastomas compared to IDH «+» gliomas. Moreover, we revealed the relationship between high accumulation index and shorter survival. Analysis of 11C-MET metabolism in patients over 50 years old revealed higher accumulation index in the EGFR «+» group. Further comparison of these imaging methods and assessment of other significant mutations are necessary to identify the anatomical and metabolic patterns of IDH «+» gliomas.
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Affiliation(s)
| | - D B Kalaeva
- Burdenko Neurosurgical Center, Moscow, Russia
- National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russia
| | - A N Tyurina
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - G V Danilov
- Burdenko Neurosurgical Center, Moscow, Russia
| | - I N Pronin
- Burdenko Neurosurgical Center, Moscow, Russia
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Castello A, Castellani M, Florimonte L, Ciccariello G, Mansi L, Lopci E. PET radiotracers in glioma: a review of clinical indications and evidence. Clin Transl Imaging 2022. [DOI: 10.1007/s40336-022-00523-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Morland D, Triumbari EKA, Boldrini L, Gatta R, Pizzuto D, Annunziata S. Radiomics in Oncological PET Imaging: A Systematic Review—Part 1, Supradiaphragmatic Cancers. Diagnostics (Basel) 2022; 12:diagnostics12061329. [PMID: 35741138 PMCID: PMC9221970 DOI: 10.3390/diagnostics12061329] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 12/10/2022] Open
Abstract
Radiomics is an upcoming field in nuclear oncology, both promising and technically challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia and assess its quality, we performed a literature search in the PubMed database up to 18 February 2022. Inclusion criteria were: studies based on human data; at least one specified tumor type; supradiaphragmatic malignancy; performing radiomics on PET imaging. Exclusion criteria were: studies only based on phantom or animal data; technical articles without a clinically oriented question; fewer than 30 patients in the training cohort. A review database containing PMID, year of publication, cancer type, and quality criteria (number of patients, retrospective or prospective nature, independent validation cohort) was constructed. A total of 220 studies met the inclusion criteria. Among them, 119 (54.1%) studies included more than 100 patients, 21 studies (9.5%) were based on prospectively acquired data, and 91 (41.4%) used an independent validation set. Most studies focused on prognostic and treatment response objectives. Because the textural parameters and methods employed are very different from one article to another, it is complicated to aggregate and compare articles. New contributions and radiomics guidelines tend to help improving quality of the reported studies over the years.
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Affiliation(s)
- David Morland
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
- Service de Médecine Nucléaire, Institut Godinot, 51100 Reims, France
- Laboratoire de Biophysique, UFR de Médecine, Université de Reims Champagne-Ardenne, 51100 Reims, France
- CReSTIC (Centre de Recherche en Sciences et Technologies de l’Information et de la Communication), EA 3804, Université de Reims Champagne-Ardenne, 51100 Reims, France
- Correspondence:
| | - Elizabeth Katherine Anna Triumbari
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
| | - Luca Boldrini
- Radiotherapy Unit, Radiomics, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (L.B.); (R.G.)
| | - Roberto Gatta
- Radiotherapy Unit, Radiomics, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (L.B.); (R.G.)
- Department of Clinical and Experimental Sciences, University of Brescia, 25121 Brescia, Italy
- Department of Oncology, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Daniele Pizzuto
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
| | - Salvatore Annunziata
- Nuclear Medicine Unit, TracerGLab, Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168 Rome, Italy; (E.K.A.T.); (D.P.); (S.A.)
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Zhou W, Huang Q, Wen J, Li M, Zhu Y, Liu Y, Dai Y, Guan Y, Zhou Z, Hua T. Integrated CT Radiomics Features Could Enhance the Efficacy of 18F-FET PET for Non-Invasive Isocitrate Dehydrogenase Genotype Prediction in Adult Untreated Gliomas: A Retrospective Cohort Study. Front Oncol 2021; 11:772703. [PMID: 34869011 PMCID: PMC8640504 DOI: 10.3389/fonc.2021.772703] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/01/2021] [Indexed: 01/03/2023] Open
Abstract
Purpose We aimed to investigate the predictive models based on O-[2-(18F)fluoroethyl]-l-tyrosine positron emission tomography/computed tomography (18F-FET PET/CT) radiomics features for the isocitrate dehydrogenase (IDH) genotype identification in adult gliomas. Methods Fifty-eight consecutive pathologically confirmed adult glioma patients with pretreatment 18F-FET PET/CT were retrospectively enrolled. One hundred and five radiomics features were extracted for analysis in each modality. Three independent radiomics models (PET-Rad Model, CT-Rad Model and PET/CT-Rad Model) predicting IDH mutation status were generated using the least absolute shrinkage and selection operator (LASSO) regression analysis based on machine learning algorithms. All-subsets regression and cross validation were applied for the filter and calibration of the predictive radiomics models. Besides, semi-quantitative parameters including maximum, peak and mean tumor to background ratio (TBRmax, TBRpeak, TBRmean), standard deviation of glioma lesion standardized uptake value (SUVSD), metabolic tumor volume (MTV) and total lesion tracer uptake (TLU) were obtained and filtered for the simple model construction with clinical feature of brain midline involvement status. The area under the receiver operating characteristic curve (AUC) was applied for the evaluation of the predictive models. Results The AUC of the simple predictive model consists of semi-quantitative parameter SUVSD and dichotomized brain midline involvement status was 0.786 (95% CI 0.659-0.883). The AUC of PET-Rad Model building with three 18F-FET PET radiomics parameters was 0.812 (95% CI 0.688-0.902). The AUC of CT-Rad Model building with three co-registered CT radiomics parameters was 0.883 (95% CI 0.771-0.952). While the AUC of the combined 18F-FET PET/CT-Rad Model building with three CT and one PET radiomics features was 0.912 (95% CI 0.808-0.970). DeLong test results indicated the PET/CT-Rad Model outperformed the PET-Rad Model (p = 0.048) and simple predictive model (p = 0.034). Further combination of the PET/CT-Rad Model with the clinical feature of dichotomized tumor location status could slightly enhance the AUC to 0.917 (95% CI 0.814-0.973). Conclusion The predictive model combining 18F-FET PET and integrated CT radiomics features could significantly enhance and well balance the non-invasive IDH genotype prediction in untreated gliomas, which is important in clinical decision making for personalized treatment.
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Affiliation(s)
- Weiyan Zhou
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Qi Huang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianbo Wen
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming Li
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuhua Zhu
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Yan Liu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.,Jinan Guoke Medical Engineering Technology Development Co., LTD, Jinan, China
| | - Yakang Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.,Jinan Guoke Medical Engineering Technology Development Co., LTD, Jinan, China
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhirui Zhou
- Radiation Oncology Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Tao Hua
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
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Taha B, Boley D, Sun J, Chen CC. State of Radiomics in Glioblastoma. Neurosurgery 2021; 89:177-184. [PMID: 33913492 DOI: 10.1093/neuros/nyab124] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Accepted: 02/13/2021] [Indexed: 12/30/2022] Open
Abstract
Radiomics is an emerging discipline that aims to make intelligent predictions and derive medical insights based on quantitative features extracted from medical images as a means to improve clinical diagnosis or outcome. Pertaining to glioblastoma, radiomics has provided powerful, noninvasive tools for gaining insights into pathogenesis and therapeutic responses. Radiomic studies have yielded meaningful biological understandings of imaging features that are often taken for granted in clinical medicine, including contrast enhancement on glioblastoma magnetic resonance imaging, the distance of a tumor from the subventricular zone, and the extent of mass effect. They have also laid the groundwork for noninvasive detection of mutations and epigenetic events that influence clinical outcomes such as isocitrate dehydrogenase (IDH) and O6-methylguanine-DNA methyltransferase (MGMT). In this article, we review advances in the field of glioblastoma radiomics as they pertain to prediction of IDH mutation status and MGMT promoter methylation status, as well as the development of novel, higher order radiomic parameters.
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Affiliation(s)
- Birra Taha
- Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota, USA
| | - Daniel Boley
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA
| | - Ju Sun
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA
| | - Clark C Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota, USA
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Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma. Diagnostics (Basel) 2021; 11:diagnostics11020189. [PMID: 33525709 PMCID: PMC7911154 DOI: 10.3390/diagnostics11020189] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 01/26/2021] [Accepted: 01/26/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Positron emission tomography with 11C-methionine (MET) is well established in the diagnostic work-up of malignant brain tumors. Texture analysis is a novel technique for extracting information regarding relationships among surrounding voxels, in order to quantify their inhomogeneity. This study evaluated whether the texture analysis of MET uptake has prognostic value for patients with glioma. METHODS We retrospectively analyzed adults with glioma who had undergone preoperative metabolic imaging at a single center. Tumors were delineated using a threshold of 1.3-fold of the mean standardized uptake value for the contralateral cortex, and then processed to calculate the texture features in glioma. RESULTS The study included 42 patients (median age: 56 years). The World Health Organization classifications were grade II (7 patients), grade III (17 patients), and grade IV (18 patients). Sixteen (16.1%) all-cause deaths were recorded during the median follow-up of 18.8 months. The univariate analyses revealed that overall survival (OS) was associated with age (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.01-1.08, p = 0.0093), tumor grade (HR 3.64, 95% CI 1.63-9.63, p = 0.0010), genetic status (p < 0.0001), low gray-level run emphasis (LGRE, calculated from the gray-level run-length matrix) (HR 2.30 × 1011, 95% CI 737.11-4.23 × 1019, p = 0.0096), and correlation (calculated from the gray-level co-occurrence matrix) (HR 5.17, 95% CI 1.07-20.93, p = 0.041). The multivariate analyses revealed OS was independently associated with LGRE and correlation. The survival curves were also significantly different (both log-rank p < 0.05). CONCLUSION Textural features obtained using preoperative MET positron emission tomography may compliment the semi-quantitative assessment for prognostication in glioma cases.
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