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Śledzińska-Bebyn P, Furtak J, Bebyn M, Serafin Z. Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling. Magn Reson Imaging 2024; 112:63-81. [PMID: 38914147 DOI: 10.1016/j.mri.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/20/2024] [Accepted: 06/20/2024] [Indexed: 06/26/2024]
Abstract
This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Affiliation(s)
- Paulina Śledzińska-Bebyn
- Department of Radiology, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland.
| | - Jacek Furtak
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, Bydgoszcz, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Marek Bebyn
- Department of Internal Diseases, 10th Military Clinical Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
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Lu Y, Du N, Fang X, Shu W, Liu W, Xu X, Ye Y, Xiao L, Mao R, Li K, Lin G, Li S. Identification of T2W hypointense ring as a novel noninvasive indicator for glioma grade and IDH genotype. Cancer Imaging 2024; 24:80. [PMID: 38943156 PMCID: PMC11212435 DOI: 10.1186/s40644-024-00726-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 06/20/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND This study aimed to evaluate the T2W hypointense ring and T2-FLAIR mismatch signs in gliomas and use these signs to construct prediction models for glioma grading and isocitrate dehydrogenase (IDH) mutation status. METHODS Two independent radiologists retrospectively evaluated 207 glioma patients to assess the presence of T2W hypointense ring and T2-FLAIR mismatch signs. The inter-rater reliability was calculated using the Cohen's kappa statistic. Two logistic regression models were constructed to differentiate glioma grade and predict IDH genotype noninvasively, respectively. Receiver operating characteristic (ROC) analysis was used to evaluate the developed models. RESULTS Of the 207 patients enrolled (119 males and 88 females, mean age 51.6 ± 14.8 years), 45 cases were low-grade gliomas (LGGs), 162 were high-grade gliomas (HGGs), 55 patients had IDH mutations, and 116 were IDH wild-type. The number of T2W hypointense ring signs was higher in HGGs compared to LGGs (p < 0.001) and higher in the IDH wild-type group than in the IDH mutant group (p < 0.001). There were also significant differences in T2-FLAIR mismatch signs between HGGs and LGGs, as well as between IDH mutant and wild-type groups (p < 0.001). Two predictive models incorporating T2W hypointense ring, absence of T2-FLAIR mismatch, and age were constructed. The area under the ROC curve (AUROC) was 0.940 for predicting HGGs (95% CI = 0.907-0.972) and 0.830 for differentiating IDH wild-type (95% CI = 0.757-0.904). CONCLUSIONS The combination of T2W hypointense ring, absence of T2-FLAIR mismatch, and age demonstrate good predictive capability for HGGs and IDH wild-type. These findings suggest that MRI can be used noninvasively to predict glioma grading and IDH mutation status, which may have important implications for patient management and treatment planning.
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Affiliation(s)
- Yawen Lu
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China
| | - Ningfang Du
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Xuhao Fang
- Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Weiquan Shu
- Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Wei Liu
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China
| | - Xinxin Xu
- Clinical Research Center for Gerontology, Huadong Hospital, Fudan University, Shanghai, China
| | - Yao Ye
- Department of Pathology, Huadong Hospital, Fudan University, Shanghai, China
| | - Li Xiao
- Department of Pathology, Huadong Hospital, Fudan University, Shanghai, China
| | - Renling Mao
- Department of Neurosurgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Kefeng Li
- Center for AI-driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao, SAR, China.
| | - Guangwu Lin
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China.
| | - Shihong Li
- Department of Radiology, Huadong Hospital, Fudan University, No.220 West YanAn Road, Shanghai, 200040, China.
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Martín-Noguerol T, Santos-Armentia E, Ramos A, Luna A. An update on susceptibility-weighted imaging in brain gliomas. Eur Radiol 2024:10.1007/s00330-024-10703-w. [PMID: 38581609 DOI: 10.1007/s00330-024-10703-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 02/17/2024] [Accepted: 02/23/2024] [Indexed: 04/08/2024]
Abstract
Susceptibility-weighted imaging (SWI) has become a standard component of most brain MRI protocols. While traditionally used for detecting and characterising brain hemorrhages typically associated with stroke or trauma, SWI has also shown promising results in glioma assessment. Numerous studies have highlighted SWI's role in differentiating gliomas from other brain lesions, such as primary central nervous system lymphomas or metastases. Additionally, SWI aids radiologists in non-invasively grading gliomas and predicting their phenotypic profiles. Various researchers have suggested incorporating SWI as an adjunct sequence for predicting treatment response and for post-treatment monitoring. A significant focus of these studies is on the detection of intratumoural susceptibility signals (ITSSs) in gliomas, which are indicative of microhemorrhages and vessels within the tumour. The quantity, distribution, and characteristics of these ITSSs can provide radiologists with more precise information for evaluating and characterising gliomas. Furthermore, the potential benefits and added value of performing SWI after the administration of gadolinium-based contrast agents (GBCAs) have been explored. This review offers a comprehensive, educational, and practical overview of the potential applications and future directions of SWI in the context of glioma assessment. CLINICAL RELEVANCE STATEMENT: SWI has proven effective in evaluating gliomas, especially through assessing intratumoural susceptibility signal changes, and is becoming a promising, easily integrated tool in MRI protocols for both pre- and post-treatment assessments. KEY POINTS: • Susceptibility-weighted imaging is the most sensitive sequence for detecting blood and calcium inside brain lesions. • This sequence, acquired with and without gadolinium, helps with glioma diagnosis, characterisation, and grading through the detection of intratumoural susceptibility signals. • There are ongoing challenges that must be faced to clarify the role of susceptibility-weighted imaging for glioma assessment.
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Affiliation(s)
| | | | - Ana Ramos
- Department of Neuroradiology, University Hospital, 12 de Octubre, Madrid, Spain
| | - Antonio Luna
- MRI Unit, Radiology Department, HT Medica, Carmelo Torres 2, 23007, Jaén, Spain
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Zeng S, Ma H, Xie D, Huang Y, Wang M, Zeng W, Zhu N, Ma Z, Yang Z, Chu J, Zhao J. Quantitative susceptibility mapping evaluation of glioma. Eur Radiol 2023; 33:6636-6647. [PMID: 37095360 DOI: 10.1007/s00330-023-09647-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 12/28/2022] [Accepted: 02/24/2023] [Indexed: 04/26/2023]
Abstract
OBJECTIVES To comprehensively evaluate the glioma using quantitative susceptibility mapping (QSM). MATERIALS AND METHODS Forty-two patients (18 women; mean age, 45 years) with pathologically confirmed gliomas were retrospectively included. All the patients underwent conventional and advanced MRI examinations (QSM, DWI, MRS, etc.). Five patients underwent paired QSM (pre- and post-enhancement). Four Visually Accessible Rembrandt Image (VASARI) features and intratumoural susceptibility signal (ITSS) were observed. Three ROIs each were manually drawn separately in the tumour parenchyma with relatively high and low magnetic susceptibility. The association between the tumour's magnetic susceptibility and other MRI parameters was also analysed. RESULTS Morphologically, gliomas with heterogeneous ITSS were more similar to high-grade gliomas (p = 0.006, AUC: 0.72, sensitivity: 70%, and specificity: 73%). Heterogeneous ITSS was significantly associated with tumour haemorrhage, necrosis, diffusion restriction, and avid enhancement but did not change between pre- and post-enhanced QSM. Quantitatively, tumour parenchyma magnetic susceptibility had limited value in grading gliomas and identifying IDH mutation status, whereas the relatively low magnetic susceptibility of the tumour parenchyma helped identify oligodendrogliomas in IDH mutated gliomas (AUC = 0.78) with high specificity (100%). The relatively high tumour magnetic susceptibility significantly increased after enhancement (p = 0.039). Additionally, we found that the magnetic susceptibility of the tumour parenchyma was significantly correlated with ADC (r = 0.61) and Cho/NAA (r = 0.40). CONCLUSIONS QSM is a promising candidate for the comprehensive evaluation of gliomas, except for IDH mutation status. The magnetic susceptibility of tumour parenchyma may be affected by tumour cell proliferation. KEY POINTS • Morphologically, gliomas with a heterogeneous intratumoural susceptibility signal (ITSS) are more similar to high-grade gliomas (p = 0.006; AUC, 0.72; sensitivity, 70%; and specificity, 73%). Heterogeneous ITSS was significantly associated with tumour haemorrhage, necrosis, diffusion restriction, and avid enhancement but did not change between pre- and post-enhanced QSM. • Tumour parenchyma's relatively low magnetic susceptibility helped identify oligodendroglioma with high specificity. • Tumour parenchyma magnetic susceptibility was significantly correlated with ADC (r = 0.61) and Cho/NAA (r = 0.40).
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Affiliation(s)
- Shanmei Zeng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Hui Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Dingxiang Xie
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Yingqian Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Mengzhu Wang
- Department of MR Scientific Marketing, Siemens Healthineers, Guangzhou, Guangdong, People's Republic of China
| | - Wenting Zeng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Nengjin Zhu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Zuliwei Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Zhiyun Yang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Jianping Chu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China.
| | - Jing Zhao
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China.
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Hangel G, Schmitz‐Abecassis B, Sollmann N, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda KM, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Hirschler L, Smits M, Petr J, Emblem KE. Advanced MR Techniques for Preoperative Glioma Characterization: Part 2. J Magn Reson Imaging 2023; 57:1676-1695. [PMID: 36912262 PMCID: PMC10947037 DOI: 10.1002/jmri.28663] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/14/2023] Open
Abstract
Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Medical Delta FoundationDelftthe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - N. Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Cancer Center AmsterdamAmsterdamNetherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
- Department of NeurologyHaaglanden Medical CenterNetherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and Psychotherapy, International Institute for the Advanced Studies of Psychotherapy and Applied Mental HealthBabes‐Bolyai UniversityRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | | | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftthe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University HospitalBrnoCzechia
- Faculty of MedicineMasaryk UniversityBrnoCzechia
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Marion Smits
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamthe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
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La Rosa C, Donato PD, Specchi S, Bernardini M. Susceptibility artifact morphology is more conspicuous on susceptibility-weighted imaging compared to T2* gradient echo sequences in the brains of dogs and cats with suspected intracranial disease. Vet Radiol Ultrasound 2023; 64:464-472. [PMID: 36633010 DOI: 10.1111/vru.13210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 11/29/2022] [Accepted: 12/12/2022] [Indexed: 01/13/2023] Open
Abstract
Susceptibility-weighted imaging (SWI) has been found to be more reliable in the detection of vessels and blood products than T2*-weighted gradient echo (GE) in several human brain diseases. In veterinary medicine, published information on the diagnostic usefulness of SWI is lacking. The aim of this retrospective observational study was to investigate the value of SWI compared to T2*-weighted GE images in a population of dogs and cats with presumed, MRI-based diagnoses grouped as neoplastic (27), cerebrovascular (14), inflammatory (14), head trauma (5), other pathologies (4), or that were normal (36). Areas of signal void (ASV) were assessed based on shape, distribution, number, and conspicuity. Presence of ASV was found in 31 T2*-weighted GE and 40 SWI sequences; the conspicuity of lesions increased in 92.5% of cases with SWI. A 44.7% increase in the number of cerebral microbleeds (CMBs) was identified within the population using SWI (110) compared to T2*-weighted GE (76). Linear ASV presumed to be abnormal vascular structures, as are reported in humans, were identified in 12 T2*-weighted GE and 19 SWI sequences. In presumed brain tumors, abnormal vascular structures were detected in 11 of 27 (40.7%) cases on T2*-weighted GE and in 16 of 27 (59.3%) cases on SWI, likely representing tumor neovascularization; amorphous ASV interpreted as presumed hemorrhages on T2*-weighted GE were diagnosed as vessels on SWI in five of 27 (18.5%) cases. Since SWI shows ASV more conspicuously than T2*-weighted GE, the authors advocate the use of SWI in veterinary patients.
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Affiliation(s)
- Claudia La Rosa
- Anicura Ospedale Veterinario I Portoni Rossi, Zola Predosa, Italy
| | - Pamela Di Donato
- Anicura Ospedale Veterinario I Portoni Rossi, Zola Predosa, Italy
- Antech Imaging Service, Fountain Valley, California, USA
| | - Swan Specchi
- Anicura Ospedale Veterinario I Portoni Rossi, Zola Predosa, Italy
- Antech Imaging Service, Fountain Valley, California, USA
| | - Marco Bernardini
- Anicura Ospedale Veterinario I Portoni Rossi, Zola Predosa, Italy
- Department of Animal Medicine, Production and Health, University of Padua, Legnaro, Italy
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7
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Chen Z, Zhai X, Chen Z. Computed cancer magnetic susceptibility imaging (canχ): Computational inverse mappings of cancer MRI. Magn Reson Imaging 2023; 102:86-95. [PMID: 37075866 DOI: 10.1016/j.mri.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/31/2023] [Accepted: 04/16/2023] [Indexed: 04/21/2023]
Abstract
PURPOSE We report a new cancer imaging modality in the contrast of tissue intrinsic susceptibility property by computed inverse magnetic resonance imaging (CIMRI). METHODS In MRI physics, an MRI signal is formed from tissue magnetism source (primarily magnetic susceptibility χ) through a cascade of MRI-introduced transformations (e.g. dipole-convolved magnetization) involving MRI setting parameters (e.g. echo time). In two-step computational inverse mappings (from phase image to internal fieldmap to susceptibility source), we could remove the MRI transformations and imaging parameters, thereby obtaining χ-depicted cancer images (canχ) from MRI phase images. Canχ is computationally implemented from clinical cancer MRI phase image by CIMRI. RESULTS As a result of MRI effect removal through computational inverse mappings, the reconstructed χ map (canχ) could provide a new cancerous tissue depiction in contrast of tissue intrinsic magnetism property (i.e. diamagnetism vs paramagnetism) as in an off-scanner state (e.g. in absence of main field B0). CONCLUSION Through retrospective clinical cancer MRI data analysis, we reported on the canχ method in technical details and demonstrated its feasibility of innovating cancer imaging in the contrast of tissue intrinsic paramagnetism/diamagnetism property (in a cancer tissue state free from MRI effect).
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Affiliation(s)
- Zikuan Chen
- Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA 91010, United States of America; Zinv LLC, Albuquerque, NM 87108, United States of America.
| | - Xiulan Zhai
- Zinv LLC, Albuquerque, NM 87108, United States of America
| | - Zeyuan Chen
- Department of Computer Sciences, University of California-Davis, Davis, CA 95616, United States of America; Microsoft Corporation, Seattle, WA 98052, United States of America.
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Tavakoli MB, Khorasani A, Jalilian M. Improvement grading brain glioma using T2 relaxation times and susceptibility-weighted images in MRI. INFORMATICS IN MEDICINE UNLOCKED 2023. [DOI: 10.1016/j.imu.2023.101201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
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9
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Borja AJ, Saini J, Raynor WY, Ayubcha C, Werner TJ, Alavi A, Revheim ME, Nagaraj C. Role of Molecular Imaging with PET/MR Imaging in the Diagnosis and Management of Brain Tumors. PET Clin 2022; 17:431-451. [PMID: 35662494 DOI: 10.1016/j.cpet.2022.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Gliomas are the most common primary brain tumors. Hybrid PET/MR imaging has revolutionized brain tumor imaging, allowing for noninvasive, simultaneous assessment of morphologic, functional, metabolic, and molecular parameters within the brain. Molecular information obtained from PET imaging may aid in the detection, classification, prognostication, and therapeutic decision making for gliomas. 18F-fluorodeoxyglucose (FDG) has been widely used in the setting of brain tumor imaging, and multiple techniques may be employed to optimize this methodology. More recently, a number of non-18F-FDG-PET radiotracers have been applied toward brain tumor imaging and are used in clinical practice.
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Affiliation(s)
- Austin J Borja
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Jitender Saini
- Department of Neuro Imaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Hosur Road, Bengaluru, Karnataka 560-029, India
| | - William Y Raynor
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Cyrus Ayubcha
- Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Thomas J Werner
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Mona-Elisabeth Revheim
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Sognsvannsveien 20, Oslo 0372, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Problemveien 7, Oslo 0315, Norway
| | - Chandana Nagaraj
- Department of Neuro Imaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Hosur Road, Bengaluru, Karnataka 560-029, India.
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10
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Carrete LR, Young JS, Cha S. Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas. Front Neurosci 2022; 16:787755. [PMID: 35281485 PMCID: PMC8904563 DOI: 10.3389/fnins.2022.787755] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 01/19/2022] [Indexed: 12/12/2022] Open
Abstract
Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.
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Affiliation(s)
- Luis R. Carrete
- University of California San Francisco School of Medicine, San Francisco, CA, United States
| | - Jacob S. Young
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
- *Correspondence: Jacob S. Young,
| | - Soonmee Cha
- Department of Radiology, University of California, San Francisco, San Francisco, CA, United States
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11
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Grading Trigone Meningiomas Using Conventional Magnetic Resonance Imaging With Susceptibility-Weighted Imaging and Perfusion-Weighted Imaging. J Comput Assist Tomogr 2022; 46:103-109. [PMID: 35027521 DOI: 10.1097/rct.0000000000001256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To compare conventional magnetic resonance imaging (MRI), susceptibility-weighted imaging (SWI), and perfusion-weighted imaging (PWI) characteristics in different grades of trigone meningiomas. METHODS Thirty patients with trigone meningiomas were enrolled in this retrospective study. Conventional MRI was performed in all patients; SWI (17 cases), dynamic contrast-enhanced PWI (10 cases), and dynamic susceptibility contrast PWI (6 cases) were performed. Demographics, conventional MRI features, SWI- and PWI-derived parameters were compared between different grades of trigone meningiomas. RESULTS On conventional MRI, the irregularity of tumor shape (ρ = 0.497, P = 0.005) and the extent of peritumoral edema (ρ = 0.187, P = 0.022) might help distinguish low-grade and high-grade trigone meningiomas. On multiparametric functional MRI, rTTPmax (1.17 ± 0.06 vs 1.30 ± 0.05, P = 0.048), Kep, Ve, and iAUC demonstrated their potentiality to predict World Health Organization grades I, II, and III trigone meningiomas. CONCLUSIONS Conventional MRI combined with dynamic susceptibility contrast and dynamic contrast-enhanced can help predict the World Health Organization grade of trigone meningiomas.
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12
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Using of Laplacian Re-decomposition image fusion algorithm for glioma grading with SWI, ADC, and FLAIR images. POLISH JOURNAL OF MEDICAL PHYSICS AND ENGINEERING 2021. [DOI: 10.2478/pjmpe-2021-0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Abstract
Introduction: Based on the tumor’s growth potential and aggressiveness, glioma is most often classified into low or high-grade groups. Traditionally, tissue sampling is used to determine the glioma grade. The aim of this study is to evaluate the efficiency of the Laplacian Re-decomposition (LRD) medical image fusion algorithm for glioma grading by advanced magnetic resonance imaging (MRI) images and introduce the best image combination for glioma grading.
Material and methods: Sixty-one patients (17 low-grade and 44 high-grade) underwent Susceptibility-weighted image (SWI), apparent diffusion coefficient (ADC) map, and Fluid attenuated inversion recovery (FLAIR) MRI imaging. To fuse different MRI image, LRD medical image fusion algorithm was used. To evaluate the effectiveness of LRD in the classification of glioma grade, we compared the parameters of the receiver operating characteristic curve (ROC).
Results: The average Relative Signal Contrast (RSC) of SWI and ADC maps in high-grade glioma are significantly lower than RSCs in low-grade glioma. No significant difference was detected between low and high-grade glioma on FLAIR images. In our study, the area under the curve (AUC) for low and high-grade glioma differentiation on SWI and ADC maps were calculated at 0.871 and 0.833, respectively.
Conclusions: By fusing SWI and ADC map with LRD medical image fusion algorithm, we can increase AUC for low and high-grade glioma separation to 0.978. Our work has led us to conclude that, by fusing SWI and ADC map with LRD medical image fusion algorithm, we reach the highest diagnostic accuracy for low and high-grade glioma differentiation and we can use LRD medical fusion algorithm for glioma grading.
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Abstract
PURPOSE OF REVIEW This review aims to cover current MRI techniques for assessing treatment response in brain tumors, with a focus on radio-induced lesions. RECENT FINDINGS Pseudoprogression and radionecrosis are common radiological entities after brain tumor irradiation and are difficult to distinguish from real progression, with major consequences on daily patient care. To date, shortcomings of conventional MRI have been largely recognized but morphological sequences are still used in official response assessment criteria. Several complementary advanced techniques have been proposed but none of them have been validated, hampering their clinical use. Among advanced MRI, brain perfusion measures increase diagnostic accuracy, especially when added with spectroscopy and susceptibility-weighted imaging. However, lack of reproducibility, because of several hard-to-control variables, is still a major limitation for their standardization in routine protocols. Amide Proton Transfer is an emerging molecular imaging technique that promises to offer new metrics by indirectly quantifying intracellular mobile proteins and peptide concentration. Preliminary studies suggest that this noncontrast sequence may add key biomarkers in tumor evaluation, especially in posttherapeutic settings. SUMMARY Benefits and pitfalls of conventional and advanced imaging on posttreatment assessment are discussed and the potential added value of APT in this clinicoradiological evolving scenario is introduced.
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Affiliation(s)
- Lucia Nichelli
- Department of Neuroradiology, Sorbonne Université, Assistance Publique-Hôpitaux de Paris, Groupe Hospitalier Pitié-Salpêtrière-Charles Foix
- Sorbonne Université, INSERM, CNRS, Assistance Publique-Hôpitaux de Paris, Institut du Cerveau et de la Moelle épinière, boulevard de l’Hôpital, Paris
| | - Stefano Casagranda
- Department of Research & Innovation, Olea Medical, avenue des Sorbiers, La Ciotat, France
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14
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Morrison MA, Lupo JM. 7-T Magnetic Resonance Imaging in the Management of Brain Tumors. Magn Reson Imaging Clin N Am 2021; 29:83-102. [PMID: 33237018 DOI: 10.1016/j.mric.2020.09.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This article provides an overview of the current status of ultrahigh-field 7-T magnetic resonance (MR) imaging in neuro-oncology, specifically for the management of patients with brain tumors. It includes a discussion of areas across the pretherapeutic, peritherapeutic, and posttherapeutic stages of patient care where 7-T MR imaging is currently being exploited and holds promise. This discussion includes existing technical challenges, barriers to clinical integration, as well as our impression of the future role of 7-T MR imaging as a clinical tool in neuro-oncology.
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Affiliation(s)
- Melanie A Morrison
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA.
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15
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Varrassi M, Bellisari FC, De Donato MC, Tommasino E, Di Sibio A, Bruno F, Di Vitantonio H, Splendiani A, Di Cesare E, Masciocchi C. Intracranial ependymomas: The role of advanced neuroimaging in diagnosis and management. Neuroradiol J 2021; 34:80-92. [PMID: 33525963 DOI: 10.1177/1971400921990770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Intracranial ependymomas represent a rare subgroup of glial tumours, showing a wide variety of imaging characteristics, often representing a challenging diagnosis for neuroradiologists. Here, we review the most recent scientific Literature on intracranial ependymomas, highlighting the most characteristic computed tomography and magnetic resonance imaging features of these neoplasms, along with epidemiologic data, recent classification aspects, clinical presentation and conventional therapeutic strategies. In addition, we report an illustrative case of an 18-year-old girl presenting with an intracranial supratentorial, anaplastic ependymoma, with the aim of contributing to the existing knowledge and comprehension of this rare tumour.
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Affiliation(s)
| | | | | | - Emanuele Tommasino
- Department of Biotechnological and Applied Clinical Science, University of L'Aquila, Italy
| | | | - Federico Bruno
- Department of Biotechnological and Applied Clinical Science, University of L'Aquila, Italy
| | | | - Alessandra Splendiani
- Department of Biotechnological and Applied Clinical Science, University of L'Aquila, Italy
| | - Ernesto Di Cesare
- Department of Biotechnological and Applied Clinical Science, University of L'Aquila, Italy
| | - Carlo Masciocchi
- Department of Biotechnological and Applied Clinical Science, University of L'Aquila, Italy
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Convection Enhanced Delivery of Topotecan for Gliomas: A Single-Center Experience. Pharmaceutics 2020; 13:pharmaceutics13010039. [PMID: 33396668 PMCID: PMC7823846 DOI: 10.3390/pharmaceutics13010039] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 12/24/2020] [Accepted: 12/24/2020] [Indexed: 12/24/2022] Open
Abstract
A key limitation to glioma treatment involves the blood brain barrier (BBB). Convection enhanced delivery (CED) is a technique that uses a catheter placed directly into the brain parenchyma to infuse treatments using a pressure gradient. In this manuscript, we describe the physical principles behind CED along with the common pitfalls and methods for optimizing convection. Finally, we highlight our institutional experience using topotecan CED for the treatment of malignant glioma.
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17
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Simultaneous feedback control for joint field and motion correction in brain MRI. Neuroimage 2020; 226:117286. [PMID: 32992003 DOI: 10.1016/j.neuroimage.2020.117286] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 07/21/2020] [Accepted: 08/14/2020] [Indexed: 11/23/2022] Open
Abstract
T2*-weighted gradient-echo sequences count among the most widely used techniques in neuroimaging and offer rich magnitude and phase contrast. The susceptibility effects underlying this contrast scale with B0, making T2*-weighted imaging particularly interesting at high field. High field also benefits baseline sensitivity and thus facilitates high-resolution studies. However, enhanced susceptibility effects and high target resolution come with inherent challenges. Relying on long echo times, T2*-weighted imaging not only benefits from enhanced local susceptibility effects but also suffers from increased field fluctuations due to moving body parts and breathing. High resolution, in turn, renders neuroimaging particularly vulnerable to motion of the head. This work reports the implementation and characterization of a system that aims to jointly address these issues. It is based on the simultaneous operation of two control loops, one for field stabilization and one for motion correction. The key challenge with this approach is that the two loops both operate on the magnetic field in the imaging volume and are thus prone to mutual interference and potential instability. This issue is addressed at the levels of sensing, timing, and control parameters. Performance assessment shows the resulting system to be stable and exhibit adequate loop decoupling, precision, and bandwidth. Simultaneous field and motion control is then demonstrated in examples of T2*-weighted in vivo imaging at 7T.
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18
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Hu J, Zhao Y, Li M, Liu J, Wang F, Weng Q, Wang X, Cao D. Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI. Eur J Radiol 2020; 131:109251. [PMID: 32916409 DOI: 10.1016/j.ejrad.2020.109251] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 07/25/2020] [Accepted: 08/10/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade. METHOD In all, 229 low-grade [Grade I] and 87 high-grade [Grade II/III] patients with pathologically diagnosed meningiomas were enrolled. Radiomic features from conventional MRI (cMRI), ADC maps and SWI were extracted based on the volume of entire tumor. Classification performance of different radiomic models (cMRI, ADC, SWI, cMRI + ADC, cMRI + SWI, ADC + SWI, and cMRI + ADC + SWI models) was evaluated by a nested LOOCV approach, combining the LASSO feature selection and RF classifier that was trained (1) without subsampling, and (2) with the synthetic minority over-sampling technique (SMOTE). The prediction performance of radiomic models was assessed using ROC curve and AUC of them was compared using Delong's test. RESULTS The cMRI + ADC + SWI model demonstrated the best performance without or with subsampling, which AUCs were 0.84 and 0.81, respectively. Following the cMRI + ADC + SWI model, the AUC range of the other models was 0.75-0.80 without subsampling, and was 0.71-0.79 with subsampling. Although the cMRI + ADC model and cMRI + SWI model showed higher AUCs than the cMRI model without subsampling (0.77 vs 0.80, P = 0.037 and 0.77 vs 0.80, P = 0.009, respectively), there was no significant difference among these models with subsampling (0.78 vs 0.77, P = 0.552 and 0.78 vs 0.79, P = 0.246, respectively). CONCLUSIONS Multiparametric radiomic model based on cMRI, ADC map and SWI yielded the best prediction performance in predicting the meningioma grade, which might offer potential guidance in clinical decision-making.
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Affiliation(s)
- Jianping Hu
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Yijing Zhao
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Mengcheng Li
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Jianyi Liu
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Feng Wang
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Qiang Weng
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Xingfu Wang
- Department of Pathology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Dairong Cao
- Department of Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
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19
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Weston P, Morales C, Dunning M, Parry A, Carrera I. Susceptibility weighted imaging at 1.5 Tesla magnetic resonance imaging in dogs: Comparison with T2*-weighted gradient echo sequence and its clinical indications. Vet Radiol Ultrasound 2020; 61:566-576. [PMID: 32663373 DOI: 10.1111/vru.12894] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 04/16/2020] [Accepted: 04/19/2020] [Indexed: 12/30/2022] Open
Abstract
Susceptibility weighted imaging (SWI) is a high resolution, fully velocity-compensated, three-dimensional gradient echo (GE) MRI technique. In humans, SWI has been reported to be more sensitive than T2*-weighted GE sequences in the identification of both intracranial hemorrhage and intra-vascular deoxyhemoglobin. However, published clinical studies comparing SWI to T2*-weighted GE sequences in dogs are currently lacking. The aim of this retrospective, observational study was to compare SWI and T2*-weighted GE sequences in a group of dogs with intracranial disease. Medical records were searched for dogs that underwent a brain MRI examination that included T2*-weighted GE and SWI sequences. The presence and appearance of non-vascular and vascular signal voids observed on T2*-weighted GE and SWI were compared. Thirty-two dogs were included with the following diagnoses: presumed and confirmed intracranial neoplasia (27), cerebrovascular accidents (3), and trauma (2). Hemorrhagic lesions were significantly more conspicuous on SWI than T2*-weighted GE sequences (P < .0001). Venous structures were well defined in all SWI sequences, and poorly defined in all dogs on T2*-weighted GE. Susceptibility weighted imaging enabled identification of vascular abnormalities in 30 of 32 (93.8%) dogs, including: neovascularization in 19 of 32 (59.4%) dogs, displacement of perilesional veins in five of 32 (15.6%) dogs, and apparent dilation of perilesional veins in 10 of 32 (31.3%) dogs. Presence of neovascularization was significantly associated with T1-weighted post-contrast enhancement (P = .0184). Hemorrhagic lesions and venous structures were more conspicuous on SWI compared to T2*-weighted GE sequences. Authors recommend adding SWI to standard brain protocols in dogs for detecting hemorrhage and identifying venous abnormalities for lesion characterization.
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Affiliation(s)
| | | | - Mark Dunning
- Willows Referral Centre, Solihull, UK.,School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
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20
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Schwarz D, Bendszus M, Breckwoldt MO. Clinical Value of Susceptibility Weighted Imaging of Brain Metastases. Front Neurol 2020; 11:55. [PMID: 32117017 PMCID: PMC7010951 DOI: 10.3389/fneur.2020.00055] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 01/15/2020] [Indexed: 12/25/2022] Open
Abstract
MRI is used for screening, initial diagnosis and follow-up of brain metastases. Multiparametric MRI protocols encompass an array of image sequences to depict key aspects of metastases morphology and biology. Given the recent safety concerns of Gd-administration and the retention of linear Gd-agents in the brain, non-contrast sequences are currently evaluated regarding their diagnostic value for brain imaging studies. Susceptibility weighted imaging has been established as a valuable clinical and research tool that is heavily used in clinical practice and utilized in diverse pathologies ranging from neuroinflammation, neurovascular disease to neurooncology. We review the value of SWI in the field of brain metastases with an emphasis on its role in early diagnosis, determination of the primary tumor entity, treatment monitoring and discuss therapy-associated changes that can affect SWI. We also review recent insights on the role of “isolated SWI signals” and the controversy on the specificity of SWI for the early detection of brain metastases.
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Affiliation(s)
- Daniel Schwarz
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Michael O Breckwoldt
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany.,Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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21
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Su CQ, Lu SS, Han QY, Zhou MD, Hong XN. Intergrating conventional MRI, texture analysis of dynamic contrast-enhanced MRI, and susceptibility weighted imaging for glioma grading. Acta Radiol 2019; 60:777-787. [PMID: 30244590 DOI: 10.1177/0284185118801127] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND The application of conventional magnetic resonance imaging (MRI) in glioma grading is limited and non-specific. PURPOSE To investigate the application values of MRI, texture analysis (TA) of dynamic contrast-enhanced MRI (DCE-MRI) and intratumoral susceptibility signal (ITSS) on susceptibility weighted imaging (SWI), alone and in combination, for glioma grading. MATERIAL AND METHODS Fifty-two patients with pathologically confirmed gliomas who underwent DCE-MRI and SWI were enrolled in this retrospective study. Conventional MRIs were evaluated by the VASARI scoring system. TA of DCE-MRI-derived parameters and the degree of ITSS were compared between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). The diagnostic ability of each parameter and their combination for glioma grading were analyzed. RESULTS Significant statistical differences in VASARI features were observed between LGGs and HGGs ( P < 0.05), of which the enhancement quality had the highest area under the curve (AUC) (0.873) with 93.3% sensitivity and 80% specificity. The TA of DCE-MRI derived parameters were significantly different between LGGs and HGGs ( P < 0.05), of which the uniformity of Ktrans had the highest AUC (0.917) with 93.3% sensitivity and 90% specificity. The degree of ITSS was significantly different between LGGs and HGGs ( P < 0.001). The AUC of the ITSS was 0.925 with 93.3% sensitivity and 90% specificity. The best discriminative power was obtained from a combination of enhancement quality, Ktrans- uniformity, and ITSS, resulting in 96.7% sensitivity, 100.0% specificity, and AUC of 0.993. CONCLUSION Combining conventional MRI, TA of DCE-MRI, and ITSS on SWI may help to improve the differentiation between LGGs and HGGs.
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Affiliation(s)
- Chun-Qiu Su
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Shan-Shan Lu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Qiu-Yue Han
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Mao-Dong Zhou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Xun-Ning Hong
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
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22
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Bhattacharjee R, Gupta RK, Patir R, Vaishya S, Ahlawat S, Singh A. Quantitative vs. semiquantitative assessment of intratumoral susceptibility signals in patients with different grades of glioma. J Magn Reson Imaging 2019; 51:225-233. [PMID: 31087724 DOI: 10.1002/jmri.26786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 04/30/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Susceptibility weighted imaging (SWI) provides vascular information and plays an important role in improving the diagnostic accuracy of preoperative glioma grading. Intratumoral susceptibility signal intensities (ITSS) obtained from SWI has been used in glioma grading. However, the current method for estimation of ITSS is semiquantitative, manual count-dependent, and includes hemorrhage as well as vasculature. PURPOSE To develop a quantitative approach that calculates the vasculature volume within tumors by filtering out the hemorrhage from ITSS using R2 * values and connected component analysis-based segmentation algorithm; to evaluate the accuracy of the proposed ITSS vasculature volume (IVV) for differentiating various grades of glioma; and compare it with reported semiquantitative ITSS approach. STUDY TYPE Retrospective. SUBJECTS Histopathologically confirmed 41 grade IV, 19 grade III, and 15 grade II glioma patients.Field Strength/Sequence: SWI (four echoes: 5.6, 11.8, 18, 24.2 msec) along with conventional MRI sequences (T2 -weighted, T1 -weighted, 3D-fluid-attenuated inversion recovery [FLAIR], and diffusion-weighted imaging [DWI]) at 3.0T. ASSESSMENT R2 * relaxation maps were calculated from multiecho SWI. The R2 * cutoff value for hemorrhage ITSS was determined. A segmentation algorithm was designed, based on this R2 * hemorrhage combined with connected component shape analysis, to quantify the IVV from all slices containing tumor by filtering out hemorrhages. Semiquantitative ITSS scoring as well as total ITSS volume (TIV) including hemorrhages were also calculated. STATISTICAL TESTS One-way analysis of variance (ANOVA) and Tukey-Kramer post-hoc tests were performed to see the difference among the three grades of the tumor (II, III, and IV) in terms of semiquantitative ITSS scoring, TIV, and IVV. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the three methods individually in discriminating between grades of glioma. RESULTS One-way ANOVA showed that only the proposed IVV significantly differentiated different grades of gliomas having visible ITSS. ROC analysis showed that IVV provided the highest AUC for the discrimination of grade II vs. III (0.93), grade III vs. IV (0.98), and grade II vs. IV glioma (0.94). IVV also provided the highest sensitivity and specificity for differentiating grade II vs. III (87.44, 98.41), grade III vs. IV (97.15, 94.12), and grade II vs. IV (98.72, 92.31). DATA CONCLUSION The proposed quantitative method segregates hemorrhage from tumor vasculature. It scores above the existing semiquantitative method in terms of ITSS estimation and grading accuracy. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:225-233.
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Affiliation(s)
- Rupsa Bhattacharjee
- Center for Biomedical Engineering, Indian Institute of Technology Delhi, Delhi, India.,Philips Health System, Philips India Limited, Gurugram, India
| | - Rakesh Kumar Gupta
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurugram, India
| | - Rana Patir
- Department of Neurosurgery, Fortis Memorial Research Institute, Gurugram, India
| | - Sandeep Vaishya
- Department of Neurosurgery, Fortis Memorial Research Institute, Gurugram, India
| | - Suneeta Ahlawat
- SRL Diagnostics, Fortis Memorial Research Institute, Gurugram, India
| | - Anup Singh
- Center for Biomedical Engineering, Indian Institute of Technology Delhi, Delhi, India.,Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, India
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The Role of Susceptibility-Weighted Imaging and Dedicated MRI Protocols in the Diagnostic Evaluation of Patients with Drug-Resistant Epilepsy. ARCHIVES OF NEUROSCIENCE 2018. [DOI: 10.5812/ans.68741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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24
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Mahammedi A, Bachir S, Purdy J, Larvie M, Buehler M. Pyogenic brain abscess, ventriculitis and diffuse meningitis with fatal outcome in an adult: Radiologic-pathologic correlation ☆,. Radiol Case Rep 2018; 13:1063-1068. [PMID: 30228844 PMCID: PMC6137902 DOI: 10.1016/j.radcr.2018.04.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 04/13/2018] [Accepted: 04/13/2018] [Indexed: 10/25/2022] Open
Abstract
Rupture of brain abscesses with evolution into ventriculitis with meningitis may result in sudden and dramatic worsening of the clinical situation. We present a 57-year-old man with such an event and fatal outcome. Multiple imaging modalities including computed tomography and advanced magnetic resonance imaging were correlated with gross specimen and histologic images. The differential diagnosis of multiple lesions with ring enhancement and prominent perifocal edema includes mainly infectious and neoplastic processes, such as brain abscess, metastasis, and multicentric glioblastoma. Pyogenic ventriculitis is an uncommon manifestation of severe intracranial infection that might be clinically obscure. We discuss the characteristic magnetic resonance findings of brain abscess and its complications, including meningitis and ventriculitis with emphasis on the role of diffusion-weighted and fluid-attenuated inversion recovery imaging.
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Affiliation(s)
- Abdelkader Mahammedi
- Cleveland Clinic, Department of Neuroradiology, Neuroradiology Room L10-407, 9500 Euclid Ave., Cleveland, OH 44195, USA
| | - Suha Bachir
- Cleveland Clinic, Department of Neuroradiology, Neuroradiology Room L10-407, 9500 Euclid Ave., Cleveland, OH 44195, USA
| | - Jenna Purdy
- University of Toledo, Department of Pathology and Neuroradiology, Toledo, OH, USA
| | - Mykol Larvie
- Cleveland Clinic, Department of Neuroradiology, Neuroradiology Room L10-407, 9500 Euclid Ave., Cleveland, OH 44195, USA
| | - Mark Buehler
- University of Toledo, Department of Pathology and Neuroradiology, Toledo, OH, USA
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Walsh AJ, Sun H, Emery DJ, Wilman AH. Hematocrit Measurement with R2* and Quantitative Susceptibility Mapping in Postmortem Brain. AJNR Am J Neuroradiol 2018; 39:1260-1266. [PMID: 29794234 DOI: 10.3174/ajnr.a5677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Accepted: 04/01/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND AND PURPOSE Noninvasive venous oxygenation quantification with MR imaging will improve the neurophysiologic investigation and the understanding of the pathophysiology in neurologic diseases. Available MR imaging methods are limited by sensitivity to flow and often require assumptions of the hematocrit level. In situ postmortem imaging enables evaluation of methods in a fully deoxygenated environment without flow artifacts, allowing direct calculation of hematocrit. This study compares 2 venous oxygenation quantification methods in in situ postmortem subjects. MATERIALS AND METHODS Transverse relaxation (R2*) mapping and quantitative susceptibility mapping were performed on a whole-body 4.7T MR imaging system. Intravenous measurements in major draining intracranial veins were compared between the 2 methods in 3 postmortem subjects. The quantitative susceptibility mapping technique was also applied in 10 healthy control subjects and compared with reference venous oxygenation values. RESULTS In 2 early postmortem subjects, R2* mapping and quantitative susceptibility mapping measurements within intracranial veins had a significant and strong correlation (R2 = 0.805, P = .004 and R2 = 0.836, P = .02). Higher R2* and susceptibility values were consistently demonstrated within gravitationally dependent venous segments during the early postmortem period. Hematocrit ranged from 0.102 to 0.580 in postmortem subjects, with R2* and susceptibility as large as 291 seconds-1 and 1.75 ppm, respectively. CONCLUSIONS Measurements of R2* and quantitative susceptibility mapping within large intracranial draining veins have a high correlation in early postmortem subjects. This study supports the use of quantitative susceptibility mapping for evaluation of in vivo venous oxygenation and postmortem hematocrit concentrations.
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Affiliation(s)
- A J Walsh
- From the Departments of Biomedical Engineering (A.J.W., H.S., A.H.W.)
- Radiology and Diagnostic Imaging (A.J.W., D.J.E.), Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - H Sun
- From the Departments of Biomedical Engineering (A.J.W., H.S., A.H.W.)
| | - D J Emery
- Radiology and Diagnostic Imaging (A.J.W., D.J.E.), Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - A H Wilman
- From the Departments of Biomedical Engineering (A.J.W., H.S., A.H.W.)
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Di Ieva A, Le Reste PJ, Carsin-Nicol B, Ferre JC, Cusimano MD. Diagnostic Value of Fractal Analysis for the Differentiation of Brain Tumors Using 3-Tesla Magnetic Resonance Susceptibility-Weighted Imaging. Neurosurgery 2017; 79:839-846. [PMID: 27332779 DOI: 10.1227/neu.0000000000001308] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Susceptibility-weighted imaging (SWI) of brain tumors provides information about neoplastic vasculature and intratumoral micro- and macrobleedings. Low- and high-grade gliomas can be distinguished by SWI due to their different vascular characteristics. Fractal analysis allows for quantification of these radiological differences by a computer-based morphological assessment of SWI patterns. OBJECTIVE To show the feasibility of SWI analysis on 3-T magnetic resonance imaging to distinguish different kinds of brain tumors. METHODS Seventy-eight patients affected by brain tumors of different histopathology (low- and high-grade gliomas, metastases, meningiomas, lymphomas) were included. All patients underwent preoperative 3-T magnetic resonance imaging including SWI, on which the lesions were contoured. The images underwent automated computation, extracting 2 quantitative parameters: the volume fraction of SWI signals within the tumors (signal ratio) and the morphological self-similar features (fractal dimension [FD]). The results were then correlated with each histopathological type of tumor. RESULTS Signal ratio and FD were able to differentiate low-grade gliomas from grade III and IV gliomas, metastases, and meningiomas (P < .05). FD was statistically different between lymphomas and high-grade gliomas (P < .05). A receiver-operating characteristic analysis showed that the optimal cutoff value for differentiating low- from high-grade gliomas was 1.75 for FD (sensitivity, 81%; specificity, 89%) and 0.03 for signal ratio (sensitivity, 80%; specificity, 86%). CONCLUSION FD of SWI on 3-T magnetic resonance imaging is a novel image biomarker for glioma grading and brain tumor characterization. Computational models offer promising results that may improve diagnosis and open perspectives in the radiological assessment of brain tumors. ABBREVIATIONS FD, fractal dimensionSR, signal ratioSWI, susceptibility-weighted imaging.
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Affiliation(s)
- Antonio Di Ieva
- ‡Australian School of Advanced Medicine, Department of Neurosurgery, Macquarie University Hospital, Sydney, New South Wales, Australia; §Garvan Institute of Medical Research, Sydney, New South Wales, Australia; ¶Department of Neurosurgery, University Hospital Pontchaillou, Rennes, France; ‖Department of Neuroradiology, University Hospital Pontchaillou, Rennes, France; #Division of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
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MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives. J Immunol Res 2017; 2017:5813951. [PMID: 28512646 PMCID: PMC5415864 DOI: 10.1155/2017/5813951] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 02/06/2017] [Accepted: 03/02/2017] [Indexed: 01/14/2023] Open
Abstract
Pseudophenomena, that is, imaging alterations due to therapy rather than tumor evolution, have an important impact on the management of glioma patients and the results of clinical trials. RANO (response assessment in neurooncology) criteria, including conventional MRI (cMRI), addressed the issues of pseudoprogression after radiotherapy and concomitant chemotherapy and pseudoresponse during antiangiogenic therapy of glioblastomas (GBM) and other gliomas. The development of cancer immunotherapy forced the identification of further relevant response criteria, summarized by the iRANO working group in 2015. In spite of this, the unequivocal definition of glioma progression by cMRI remains difficult particularly in the setting of immunotherapy approaches provided by checkpoint inhibitors and dendritic cells. Advanced MRI (aMRI) may in principle address this unmet clinical need. Here, we discuss the potential contribution of different aMRI techniques and their indications and pitfalls in relation to biological and imaging features of glioma and immune system interactions.
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Duyn JH, Schenck J. Contributions to magnetic susceptibility of brain tissue. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3546. [PMID: 27240118 PMCID: PMC5131875 DOI: 10.1002/nbm.3546 10.1002/nbm.3546] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 02/19/2016] [Accepted: 03/31/2016] [Indexed: 11/17/2023]
Abstract
This review discusses the major contributors to the subtle magnetic properties of brain tissue and how they affect MRI contrast. With the increased availability of high-field scanners, the use of magnetic susceptibility contrast for the study of human brain anatomy and function has increased dramatically. This has not only led to novel applications, but has also improved our understanding of the complex relationship between MRI contrast and magnetic susceptibility. Chief contributors to the magnetic susceptibility of brain tissue have been found to include myelin as well as iron. In the brain, iron exists in various forms with diverse biological roles, many of which are now only starting to be uncovered. An interesting aspect of magnetic susceptibility contrast is its sensitivity to the microscopic distribution of iron and myelin, which provides opportunities to extract information at spatial scales well below MRI resolution. For example, in white matter, the myelin sheath that surrounds the axons can provide tissue contrast that is dependent on the axonal orientation and reflects the relative size of intra- and extra-axonal water compartments. The extraction of such ultrastructural information, together with quantitative information about iron and myelin concentrations, is an active area of research geared towards the characterization of brain structure and function, and their alteration in disease. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jeff H. Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular
Imaging, National Institutes of Neurological Disorders and Stroke, National
Institutes of Health, Bethesda, Maryland 20892, USA
| | - John Schenck
- MRI Technologies and Systems, General Electric
Global Research Center, 1 Research Circle, Schenectady, New York 12309, USA
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Duyn JH, Schenck J. Contributions to magnetic susceptibility of brain tissue. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3546. [PMID: 27240118 PMCID: PMC5131875 DOI: 10.1002/nbm.3546] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 02/19/2016] [Accepted: 03/31/2016] [Indexed: 05/08/2023]
Abstract
This review discusses the major contributors to the subtle magnetic properties of brain tissue and how they affect MRI contrast. With the increased availability of high-field scanners, the use of magnetic susceptibility contrast for the study of human brain anatomy and function has increased dramatically. This has not only led to novel applications, but has also improved our understanding of the complex relationship between MRI contrast and magnetic susceptibility. Chief contributors to the magnetic susceptibility of brain tissue have been found to include myelin as well as iron. In the brain, iron exists in various forms with diverse biological roles, many of which are now only starting to be uncovered. An interesting aspect of magnetic susceptibility contrast is its sensitivity to the microscopic distribution of iron and myelin, which provides opportunities to extract information at spatial scales well below MRI resolution. For example, in white matter, the myelin sheath that surrounds the axons can provide tissue contrast that is dependent on the axonal orientation and reflects the relative size of intra- and extra-axonal water compartments. The extraction of such ultrastructural information, together with quantitative information about iron and myelin concentrations, is an active area of research geared towards the characterization of brain structure and function, and their alteration in disease. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jeff H. Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular
Imaging, National Institutes of Neurological Disorders and Stroke, National
Institutes of Health, Bethesda, Maryland 20892, USA
| | - John Schenck
- MRI Technologies and Systems, General Electric
Global Research Center, 1 Research Circle, Schenectady, New York 12309, USA
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Soman S, Bregni JA, Bilgic B, Nemec U, Fan A, Liu Z, Barry RL, Du J, Main K, Yesavage J, Adamson MM, Moseley M, Wang Y. Susceptibility-Based Neuroimaging: Standard Methods, Clinical Applications, and Future Directions. CURRENT RADIOLOGY REPORTS 2017; 5. [PMID: 28695062 DOI: 10.1007/s40134-017-0204-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The evaluation of neuropathologies using MRI methods that leverage tissue susceptibility have become standard practice, especially to detect blood products or mineralization. Additionally, emerging MRI techniques have the ability to provide new information based on tissue susceptibility properties in a robust and quantitative manner. This paper discusses these advanced susceptibility imaging techniques and their clinical applications.
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Affiliation(s)
- Salil Soman
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Rosenberg 90A, 1 Deaconess Road, Boston, MA 02215, Tel: 617-754-2009
| | | | - Berkin Bilgic
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, A.A. Martinos Center for Biomedical Imaging 149 13th Street, Room 2.102, Charlestown, MA 02129, Tel: 617-866-8740
| | - Ursula Nemec
- Department of Radiology, Medical University of Vienna, Austria
| | - Audrey Fan
- Department of Radiology, Stanford School of Medicine 300 Pasteur Dr, MC 5105, Stanford, CA94305
| | - Zhe Liu
- Cornell MRI Research Lab, Cornell University, 515 East 71st St, Suite 104, New York, NY 10021, ,
| | - Robert L Barry
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, A.A. Martinos Center for Biomedical Imaging 149 13th Street, Suite 2.301, Charlestown, MA 02129 USA, Tel: 615-801-0795
| | - Jiang Du
- Department of Radiology, UCSD, 200 West Arbor Drive, San Diego, CA 92103-8226, Tel: 619-471-0519
| | - Keith Main
- Principal Scientist (SME), Research Division, Defense and Veterans Brain Injury Center, General Dynamics Health Solutions, 1335 East-West Hwy, Suite 4-100, Silver Spring, MD 20910
| | - Jerome Yesavage
- Department of Psychiatry & Behavioral Sciences, Stanford School of Medicine, Mail Code 151-Y, 3801 Miranda Avenue, Palo Alto, California 94304, Phone (650) 852-3287
| | - Maheen M Adamson
- Department of Neurosurgery, Department of Psychiatry & Behavioral Sciences, Stanford School of Medicine, Defense and Veterans Brain Injury Center, VA Palo Alto Health Care System (PSC/117), 3801 Miranda Avenue (151Y), Palo Alto, CA 94304
| | - Michael Moseley
- Department of Radiology, Stanford School of Medicine, Mail Code 5488, Route 8, Rm PS059, Stanford, CA, 94305-5488, Tel: 650-725-6077
| | - Yi Wang
- Department of Radiology, Cornell Medical School, Department of Biomedical Engineering, Cornell University, 301 Weill Hall, 237 Tower Road, Ithaca, NY 14853, Tel: 646 962-2631
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Pyogenic brain abscess with atypical features resembling glioblastoma in advanced MRI imaging. Radiol Case Rep 2017; 12:365-370. [PMID: 28491190 PMCID: PMC5417631 DOI: 10.1016/j.radcr.2016.12.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 11/28/2016] [Accepted: 12/19/2016] [Indexed: 12/28/2022] Open
Abstract
Differentiation between infectious and neoplastic brain processes is crucial for treatment planning. Advanced magnetic resonance imaging techniques, such as diffusion, perfusion, susceptibility weighted imaging, and magnetic resonance spectroscopy, enhance the imaging differences between these two pathologies. However, despite the utilization of these advanced techniques, the pathologic process may be confound by atypical findings. Here, we report a case of an autistic patient with multiple brain lesions with diffusion weighted imaging, susceptibility weighted imaging, and perfusion patterns resembling features of a multicentric glioblastoma, which were confirmed surgically, neuropathologically, and bacteriologically as brain abscesses. We discuss the differentiation of these different entities in the light of advanced magnetic resonance imaging techniques.
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Belliveau JG, Bauman G, Macdonald DR. Detecting tumor progression in glioma: current standards and new techniques. Expert Rev Anticancer Ther 2016; 16:1177-1188. [PMID: 27661768 DOI: 10.1080/14737140.2016.1240621] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
INTRODUCTION The post-treatment monitoring of glioma patients remains an area of active research and development. Conventional imaging with MRI is a highly sensitive modality for detecting and monitoring primary and secondary brain tumors and includes multi-parametric sequences to better characterize the disease. Standardized schemes for measuring response to treatment are in wide clinical use; however, the introduction of new therapeutics have introduced new patterns of response that can confound interpretation of conventional MRI and can cause uncertainty in the proper management following therapy. Areas covered: A summary of current and evolving techniques for assessing glioma response in this era of new therapies that address these challenges are presented in this review. While this review focuses more on clinical and early clinical methodologies for MRI and nuclear medicine techniques some promising pre-clinical techniques are also presented. Expert commentary: While successful single institution results have been widely reported in the literature, any new methodologies must be undertaken in multi-center settings. Additionally, the need for standardization of protocols in quantitative measured are an important area that must be addressed for new and promising techniques to be implemented to a wide array of patients.
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Affiliation(s)
- Jean-Guy Belliveau
- a Department of Medical Biophysics , University of Western Ontario , London , ON , Canada
| | - Glenn Bauman
- b Department of Medical Biophysics and Oncology , University of Western Ontario , London , ON , Canada
| | - David R Macdonald
- c Department of Oncology , University of Western Ontario , London , ON , Canada
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Visualization of Anatomic Variation of the Anterior Septal Vein on Susceptibility-Weighted Imaging. PLoS One 2016; 11:e0164221. [PMID: 27716782 PMCID: PMC5055311 DOI: 10.1371/journal.pone.0164221] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 09/21/2016] [Indexed: 11/19/2022] Open
Abstract
Background and Purpose Understanding the anatomy of the anterior septal vein (ASV) is critical for minimally invasive procedures to the third ventricle and for assessing lesion size and venous drainage in the anterior cranial fossa. Accordingly, this study evaluated topographic anatomy and anatomic variation of the ASV using susceptibility-weighted imaging (SWI). Methods Sixty volunteers were examined using a 3.0T MR system. The diameter of the ASV and distance between bilateral septal points were measured. ASVs were divided into types 1 (only drains frontal lobe) and 2 (drains both frontal lobe and head of the caudate nucleus). We evaluated the ASV-internal cerebral vein (ICV) junction based on its positional relationship with the appearance of a venous angle or a false venous angle and the foramen of Monro. Fused SW and T1-weighted images were used to observe positional relationships between the course of the ASV and the surrounding brain structures. Results The ASV and its small tributaries were clearly visualized in 120 hemispheres (100%). The average diameter of ASVs was 1.05±0.17 mm (range 0.9–1.6 mm). The average distance between bilateral septal points was 2.23±1.03 mm (range 1.3–6.6 mm). The ASV types 1 and 2 were in 77 (64.2%) and 43 (35.8%) hemispheres, respectively. In 83 (69.2%) hemispheres, the ASV-ICV junction was situated at the venous angle and the posterior margin of the foramen of Monro. In 37 (30.8%) hemispheres, the ASV-ICV junction was situated beyond the posterior margin of the foramen of Monro. The average distance between the posteriorly located ASV-ICV junction and the posterior margin of the foramen of Monro was 6.41±3.95 mm (range 2.4–15.9 mm). Conclusion Using SWI, the topographic anatomy and anatomic variation of the ASV were clearly demonstrated. Preoperative assessment of anatomic variation of the ASV may be advantageous for minimally invasive neurosurgical procedures.
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Wang X, Li L, Luo P, Li L, Cui Q, Wang J, Jing Z, Wang Y. Neuronavigation-assisted trajectory planning for deep brain biopsy with susceptibility-weighted imaging. Acta Neurochir (Wien) 2016; 158:1355-62. [PMID: 27165299 DOI: 10.1007/s00701-016-2823-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2015] [Accepted: 04/25/2016] [Indexed: 01/14/2023]
Abstract
BACKGROUND Susceptibility-weighted imaging (SWI) exploits susceptibility differences between tissues to enhance contrast in magnetic resonance imaging to enable the visualization of small blood vessels that are difficult to detect by other contrast agents. This study explored the value of SWI-based planning for neuronavigation-guided deep brain biopsies to reduce the incidence of post-surgical complications. METHODS The cohort of 84 patients was divided into 41 biopsies performed aided by SWI (SWI group) and 43 biopsies based on conventional T1w-Gd-based imaging (T1w-Gd group). Biopsy targets were determined using magnetic resonance spectroscopy (MRS) before the operation, and the safest trajectory was selected based on preoperative images of blood vessels. RESULTS Within 24 h of surgery, there was no radiographically identified bleeding, no blood extravasation and no clinical intracranial hypertension in the SWI group. Only one patient (2.5 %) with basal ganglia lymphoma developed transient hemiparesis after biopsy, who later recovered after undergoing symptomatic treatment. Complication rates in the SWI group were lower than in the T1w-Gd group, where a 7 % morbidity rate was encountered with one patient developing a permanent neurological deficit and two showing biopsy-associated hemorrhages. SWI imaging yielded a better visualization of subcortical vessels and deep-seated brain structures. CONCLUSIONS SWI-based imaging revealed significantly better visualization of small-caliber vasculature that was not detectable on conventional T1w-Gd imaging, minimizing damage to the brain and reducing postoperative complications. Furthermore, MRS can contribute significantly to target selection to improve the yield of image-guided biopsies.
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Affiliation(s)
- Xin Wang
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Long Li
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Peng Luo
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Lianxiang Li
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Qitao Cui
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Jun Wang
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Zhitao Jing
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
| | - Yunjie Wang
- Department of Neurosurgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
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Grabner G, Kiesel B, Wöhrer A, Millesi M, Wurzer A, Göd S, Mallouhi A, Knosp E, Marosi C, Trattnig S, Wolfsberger S, Preusser M, Widhalm G. Local image variance of 7 Tesla SWI is a new technique for preoperative characterization of diffusely infiltrating gliomas: correlation with tumour grade and IDH1 mutational status. Eur Radiol 2016; 27:1556-1567. [PMID: 27300198 PMCID: PMC5334387 DOI: 10.1007/s00330-016-4451-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Revised: 04/29/2016] [Accepted: 05/25/2016] [Indexed: 12/12/2022]
Abstract
OBJECTIVES To investigate the value of local image variance (LIV) as a new technique for quantification of hypointense microvascular susceptibility-weighted imaging (SWI) structures at 7 Tesla for preoperative glioma characterization. METHODS Adult patients with neuroradiologically suspected diffusely infiltrating gliomas were prospectively recruited and 7 Tesla SWI was performed in addition to standard imaging. After tumour segmentation, quantification of intratumoural SWI hypointensities was conducted by the SWI-LIV technique. Following surgery, the histopathological tumour grade and isocitrate dehydrogenase 1 (IDH1)-R132H mutational status was determined and SWI-LIV values were compared between low-grade gliomas (LGG) and high-grade gliomas (HGG), IDH1-R132H negative and positive tumours, as well as gliomas with significant and non-significant contrast-enhancement (CE) on MRI. RESULTS In 30 patients, 9 LGG and 21 HGG were diagnosed. The calculation of SWI-LIV values was feasible in all tumours. Significantly higher mean SWI-LIV values were found in HGG compared to LGG (92.7 versus 30.8; p < 0.0001), IDH1-R132H negative compared to IDH1-R132H positive gliomas (109.9 versus 38.3; p < 0.0001) and tumours with significant CE compared to non-significant CE (120.1 versus 39.0; p < 0.0001). CONCLUSIONS Our data indicate that 7 Tesla SWI-LIV might improve preoperative characterization of diffusely infiltrating gliomas and thus optimize patient management by quantification of hypointense microvascular structures. KEY POINTS • 7 Tesla local image variance helps to quantify hypointense susceptibility-weighted imaging structures. • SWI-LIV is significantly increased in high-grade and IDH1-R132H negative gliomas. • SWI-LIV is a promising technique for improved preoperative glioma characterization. • Preoperative management of diffusely infiltrating gliomas will be optimized.
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Affiliation(s)
- Günther Grabner
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Health Sciences and Social Work, Carinthia University of Applied Sciences, St. Veiterstraße 47, 9020, Klagenfurt am Wörthersee, Austria
| | - Barbara Kiesel
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Adelheid Wöhrer
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Institute of Neurology, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Matthias Millesi
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Aygül Wurzer
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Sabine Göd
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Ammar Mallouhi
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Radiology, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Engelbert Knosp
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Christine Marosi
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Internal Medicine I, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Siegfried Trattnig
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Stefan Wolfsberger
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Matthias Preusser
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.,Department of Internal Medicine I, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria
| | - Georg Widhalm
- Comprehensive Cancer Center, Central Nervous System Tumours Unit (CCC-CNS), Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria. .,Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1097, Vienna, Austria.
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Kurz FT, Freitag M, Schlemmer HP, Bendszus M, Ziener CH. Grundlagen und Anwendungen der suszeptibilitätsgewichteten Bildgebung. Radiologe 2016; 56:124-36. [DOI: 10.1007/s00117-015-0069-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Di Bonaventura G, Pompilio A, Crocetta V, De Nicola S, Barbaro F, Giuliani L, D'Emilia E, Fiscarelli E, Bellomo RG, Saggini R. Exposure to extremely low-frequency magnetic field affects biofilm formation by cystic fibrosis pathogens. Future Microbiol 2014; 9:1303-17. [DOI: 10.2217/fmb.14.96] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
SUMMARY Aims: To evaluate the in vitro effects of extremely low-frequency magnetic field (ELF-MF) on growth and biofilm formation by Staphylococcus aureus, Pseudomonas aeruginosa, Burkholderia cepacia and Stenotrophomonas maltophilia strains from cystic fibrosis patients. Materials & methods: The motion of selected ions (Fe, Ca, Cu, Zn, Mg, K, Na) was stimulated by the ion resonance effect, then influence on growth and biofilm formation/viability was assessed by spectrophotometry or viability count. Results: Generally, exposure to ELF-MF significantly increased bacterial growth and affected both biofilm formation and viability, although with differences with regard to ions and species considered. Conclusion: Exposure to ELF-MF represents a possible new approach for treatment of biofilm-associated cystic fibrosis lung infections.
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Affiliation(s)
- Giovanni Di Bonaventura
- Department of Experimental & Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
- Center of Excellence on Ageing, G. d'Annunzio University Foundation, Chieti, Italy
| | - Arianna Pompilio
- Department of Experimental & Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
- Center of Excellence on Ageing, G. d'Annunzio University Foundation, Chieti, Italy
| | - Valentina Crocetta
- Department of Experimental & Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
- Center of Excellence on Ageing, G. d'Annunzio University Foundation, Chieti, Italy
| | - Serena De Nicola
- Department of Experimental & Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
- Center of Excellence on Ageing, G. d'Annunzio University Foundation, Chieti, Italy
| | - Filippo Barbaro
- Prometeo S.r.l., Padova, Italy
- Department of Neuroscience & Imaging, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Livio Giuliani
- INAIL, Workers Compensation Authority, Research Center of Monteporzio Catone, Rome, Italy
| | - Enrico D'Emilia
- INAIL, Workers Compensation Authority, Research Center of Monteporzio Catone, Rome, Italy
| | | | - Rosa Grazia Bellomo
- Department of Medicine & Ageing Sciences, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Raoul Saggini
- Department of Neuroscience & Imaging, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
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Keunen O, Taxt T, Grüner R, Lund-Johansen M, Tonn JC, Pavlin T, Bjerkvig R, Niclou SP, Thorsen F. Multimodal imaging of gliomas in the context of evolving cellular and molecular therapies. Adv Drug Deliv Rev 2014; 76:98-115. [PMID: 25078721 DOI: 10.1016/j.addr.2014.07.010] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2014] [Revised: 07/14/2014] [Accepted: 07/22/2014] [Indexed: 01/18/2023]
Abstract
The vast majority of malignant gliomas relapse after surgery and standard radio-chemotherapy. Novel molecular and cellular therapies are thus being developed, targeting specific aspects of tumor growth. While histopathology remains the gold standard for tumor classification, neuroimaging has over the years taken a central role in the diagnosis and treatment follow up of brain tumors. It is used to detect and localize lesions, define the target area for biopsies, plan surgical and radiation interventions and assess tumor progression and treatment outcome. In recent years the application of novel drugs including anti-angiogenic agents that affect the tumor vasculature, has drastically modulated the outcome of brain tumor imaging. To properly evaluate the effects of emerging experimental therapies and successfully support treatment decisions, neuroimaging will have to evolve. Multi-modal imaging systems with existing and new contrast agents, molecular tracers, technological advances and advanced data analysis can all contribute to the establishment of disease relevant biomarkers that will improve disease management and patient care. In this review, we address the challenges of glioma imaging in the context of novel molecular and cellular therapies, and take a prospective look at emerging experimental and pre-clinical imaging techniques that bear the promise of meeting these challenges.
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