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Nguyen TTT, Greene LA, Mnatsakanyan H, Badr CE. Revolutionizing Brain Tumor Care: Emerging Technologies and Strategies. Biomedicines 2024; 12:1376. [PMID: 38927583 PMCID: PMC11202201 DOI: 10.3390/biomedicines12061376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/16/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024] Open
Abstract
Glioblastoma multiforme (GBM) is one of the most aggressive forms of brain tumor, characterized by a daunting prognosis with a life expectancy hovering around 12-16 months. Despite a century of relentless research, only a select few drugs have received approval for brain tumor treatment, largely due to the formidable barrier posed by the blood-brain barrier. The current standard of care involves a multifaceted approach combining surgery, irradiation, and chemotherapy. However, recurrence often occurs within months despite these interventions. The formidable challenges of drug delivery to the brain and overcoming therapeutic resistance have become focal points in the treatment of brain tumors and are deemed essential to overcoming tumor recurrence. In recent years, a promising wave of advanced treatments has emerged, offering a glimpse of hope to overcome the limitations of existing therapies. This review aims to highlight cutting-edge technologies in the current and ongoing stages of development, providing patients with valuable insights to guide their choices in brain tumor treatment.
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Affiliation(s)
- Trang T. T. Nguyen
- Ronald O. Perelman Department of Dermatology, Perlmutter Cancer Center, NYU Grossman School of Medicine, NYU Langone Health, New York, NY 10016, USA
| | - Lloyd A. Greene
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032, USA;
| | - Hayk Mnatsakanyan
- Department of Neurology, Massachusetts General Hospital, Neuroscience Program, Harvard Medical School, Boston, MA 02129, USA; (H.M.); (C.E.B.)
| | - Christian E. Badr
- Department of Neurology, Massachusetts General Hospital, Neuroscience Program, Harvard Medical School, Boston, MA 02129, USA; (H.M.); (C.E.B.)
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Chekhonin IV, Cohen O, Otazo R, Young RJ, Holodny AI, Pronin IN. Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review. Neuroradiol J 2024; 37:267-275. [PMID: 37133228 PMCID: PMC11138331 DOI: 10.1177/19714009231173100] [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] [Indexed: 05/04/2023] Open
Abstract
Magnetic resonance (MR) relaxometry is a quantitative imaging method that measures tissue relaxation properties. This review discusses the state of the art of clinical proton MR relaxometry for glial brain tumors. Current MR relaxometry technology also includes MR fingerprinting and synthetic MRI, which solve the inefficiencies and challenges of earlier techniques. Despite mixed results regarding its capability for brain tumor differential diagnosis, there is growing evidence that MR relaxometry can differentiate between gliomas and metastases and between glioma grades. Studies of the peritumoral zones have demonstrated their heterogeneity and possible directions of tumor infiltration. In addition, relaxometry offers T2* mapping that can define areas of tissue hypoxia not discriminated by perfusion assessment. Studies of tumor therapy response have demonstrated an association between survival and progression terms and dynamics of native and contrast-enhanced tumor relaxometric profiles. In conclusion, MR relaxometry is a promising technique for glial tumor diagnosis, particularly in association with neuropathological studies and other imaging techniques.
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Affiliation(s)
- Ivan V Chekhonin
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
- Federal State Budgetary Institution V.P. Serbsky National Medical Research Centre for Psychiatry and Narcology of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Ouri Cohen
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrei I Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
- Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY, USA
| | - Igor N Pronin
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
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Reiter JT, Schulte F, Bauer T, David B, Endler C, Isaak A, Schuch F, Bitzer F, Witt JA, Hattingen E, Deichmann R, Attenberger U, Becker AJ, Helmstaedter C, Radbruch A, Surges R, Friedman A, Rüber T. Evidence for interictal blood-brain barrier dysfunction in people with epilepsy. Epilepsia 2024; 65:1462-1474. [PMID: 38436479 DOI: 10.1111/epi.17929] [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: 10/08/2023] [Revised: 02/11/2024] [Accepted: 02/12/2024] [Indexed: 03/05/2024]
Abstract
OBJECTIVE Interictal blood-brain barrier dysfunction in chronic epilepsy has been demonstrated in animal models and pathological specimens. Ictal blood-brain barrier dysfunction has been shown in humans in vivo using an experimental quantitative magnetic resonance imaging (MRI) protocol. Here, we hypothesized that interictal blood-brain barrier dysfunction is also present in people with drug-resistant epilepsy. METHODS Thirty-nine people (21 females, mean age at MRI ± SD = 30 ± 8 years) with drug-resistant epilepsy were prospectively recruited and underwent interictal T1-relaxometry before and after administration of a paramagnetic contrast agent. Likewise, quantitative T1 was acquired in 29 people without epilepsy (12 females, age at MRI = 48 ± 18 years). Quantitative T1 difference maps were calculated and served as a surrogate imaging marker for blood-brain barrier dysfunction. Values of quantitative T1 difference maps inside hemispheres ipsilateral to the presumed seizure onset zone were then compared, on a voxelwise level and within presumed seizure onset zones, to the contralateral side of people with epilepsy and to people without epilepsy. RESULTS Compared to the contralateral side, ipsilateral T1 difference values were significantly higher in white matter (corrected p < .05), gray matter (uncorrected p < .05), and presumed seizure onset zones (p = .04) in people with epilepsy. Compared to people without epilepsy, significantly higher T1 difference values were found in the anatomical vicinity of presumed seizure onset zones (p = .004). A subgroup of people with hippocampal sclerosis demonstrated significantly higher T1 difference values in the ipsilateral hippocampus and in regions strongly interconnected with the hippocampus compared to people without epilepsy (corrected p < .01). Finally, z-scores reflecting the deviation of T1 difference values within the presumed seizure onset zone were associated with verbal memory performance (p = .02) in people with temporal lobe epilepsy. SIGNIFICANCE Our results indicate a blood-brain barrier dysfunction in drug-resistant epilepsy that is detectable interictally in vivo, anatomically related to the presumed seizure onset zone, and associated with cognitive deficits.
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Affiliation(s)
- Johannes T Reiter
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Freya Schulte
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Tobias Bauer
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Bastian David
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Christoph Endler
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Alexander Isaak
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Fabiane Schuch
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Felix Bitzer
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | | | - Elke Hattingen
- Institute of Neuroradiology, University Hospital and Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Ulrike Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany
| | - Albert J Becker
- Department of Neuropathology, University Hospital Bonn, Bonn, Germany
| | | | | | - Rainer Surges
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Alon Friedman
- Department of Medical Neuroscience, Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
- Departments of Cognitive and Brain Sciences, Physiology, and Cell Biology, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Theodor Rüber
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
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4
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Ge X, Ma Y, Huang X, Gan T, Ma W, Liu G, Xiong Y, Li M, Wang X, Zhang J. Distinguishment between high-grade gliomas and solitary brain metastases in peritumoural oedema: quantitative analysis using synthetic MRI at 3 T. Clin Radiol 2024; 79:e361-e368. [PMID: 38103981 DOI: 10.1016/j.crad.2023.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 09/12/2023] [Accepted: 10/21/2023] [Indexed: 12/19/2023]
Abstract
AIM To investigate the efficacy of synthetic magnetic resonance imaging (MRI) in distinguishing high-grade gliomas (HGGs) from solitary brain metastases (SBMs) in peritumoural oedema. MATERIALS AND METHODS Thirty-five patients with HGGs and 25 patients with SBMs were recruited and scanned using synthetic MRI using a 3 T scanner. Two radiologists measured synthetic MRI-derived relaxation values independently (T1, T2, proton density [PD]) in the peritumoural oedema, which was used to generate quantitative metrics before (T1native, T2native, and PDnative) and after (T1post, T2post, and PDpost) contrast agent injection. Student's t-test or the Mann-Whitney U-test was performed to detect statistically significant differences in the aforementioned metrics in peritumoural oedema between HGGs and SBMs. The receiver operating characteristic (ROC) curves were plotted to evaluate the efficacy of each metric in distinguishing the two groups, and the areas under the curves (AUCs) were compared pairwise by performing the Delong test. RESULTS The mean T1native, T2native, and T1post values in the peritumoural oedema of HGGs were significantly lower compared with SBMs (all p<0.05). The T1post value had a higher AUC (0.843) in differentiating HGGs and SBMs than all other individual metrics (all p<0.05). The combined T1native, T2native, and T1post model had the best distinguishing performance with an AUC, sensitivity, and specificity of 0.987, 94.3%, and 100%, respectively. CONCLUSIONS Synthetic MRI may be a potential supplement to the preoperative diagnosis of HGGs and SBMs in clinical practice, as the synthetic MRI-derived tri-parametric model in the peritumoural oedema showed significantly improved diagnostic performance in distinguishing HGGs from SBMs.
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Affiliation(s)
- X Ge
- Second Clinical School, Lanzhou University, Lanzhou 70030, China; Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - Y Ma
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - X Huang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750003, China
| | - T Gan
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - W Ma
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, China
| | - G Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
| | - Y Xiong
- GE Healthcare, MR Research, Beijing 100004, China
| | - M Li
- GE Healthcare, MR Enhancement Application, Beijing 100004, China
| | - X Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan 750003, China.
| | - J Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 70030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
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Pham J, Ng FC. Novel advanced imaging techniques for cerebral oedema. Front Neurol 2024; 15:1321424. [PMID: 38356883 PMCID: PMC10865379 DOI: 10.3389/fneur.2024.1321424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 01/09/2024] [Indexed: 02/16/2024] Open
Abstract
Cerebral oedema following acute ischemic infarction has been correlated with poor functional outcomes and is the driving mechanism of malignant infarction. Measurements of midline shift and qualitative assessment for herniation are currently the main CT indicators for cerebral oedema but have limited sensitivity for small cortical infarcts and are typically a delayed sign. In contrast, diffusion-weighted (DWI) or T2-weighted magnetic resonance imaging (MRI) are highly sensitive but are significantly less accessible. Due to the need for early quantification of cerebral oedema, several novel imaging biomarkers have been proposed. Based on neuroanatomical shift secondary to space-occupying oedema, measures such as relative hemispheric volume and cerebrospinal fluid displacement are correlated with poor outcomes. In contrast, other imaging biometrics, such as net water uptake, T2 relaxometry and blood brain barrier permeability, reflect intrinsic tissue changes from the influx of fluid into the ischemic region. This review aims to discuss quantification of cerebral oedema using current and developing advanced imaging techniques, and their role in predicting clinical outcomes.
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Affiliation(s)
- Jenny Pham
- Department of Radiology, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Felix C. Ng
- Department of Neurology, Royal Melbourne Hospital, Parkville, VIC, Australia
- Department of Neurology, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine at Royal Melbourne Hospital, Melbourne Brain Centre, University of Melbourne, Parkville, VIC, Australia
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Guillevin R, Naudin M, Fayolle P, Giraud C, Le Guillou X, Thomas C, Herpe G, Miranville A, Fernandez-Maloigne C, Pellerin L, Guillevin C. Diagnostic and Therapeutic Issues in Glioma Using Imaging Data: The Challenge of Numerical Twinning. J Clin Med 2023; 12:7706. [PMID: 38137775 PMCID: PMC10744312 DOI: 10.3390/jcm12247706] [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: 11/06/2023] [Revised: 11/28/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023] Open
Abstract
Glial tumors represent the leading etiology of primary brain tumors. Their particularities lie in (i) their location in a highly functional organ that is difficult to access surgically, including for biopsy, and (ii) their rapid, anisotropic mode of extension, notably via the fiber bundles of the white matter, which further limits the possibilities of resection. The use of mathematical tools enables the development of numerical models representative of the oncotype, genotype, evolution, and therapeutic response of lesions. The significant development of digital technologies linked to high-resolution NMR exploration, coupled with the possibilities offered by AI, means that we can envisage the creation of digital twins of tumors and their host organs, thus reducing the use of physical sampling.
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Affiliation(s)
- Rémy Guillevin
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | - Mathieu Naudin
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | - Pierre Fayolle
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | - Clément Giraud
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | - Xavier Le Guillou
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
- Department of Genetic, University Hospital Center of Poitiers, 86000 Poitiers, France
| | - Clément Thomas
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | - Guillaume Herpe
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | - Alain Miranville
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
| | | | - Luc Pellerin
- IRMETIST Laboratory, INSERM U1313, University of Poitiers and University Hospital Center of Poitiers, 86000 Poitiers, France
| | - Carole Guillevin
- Department of Imaging, University Hospital Center of Poitiers, 86000 Poitiers, France
- Labcom I3M, University of Poitiers, 86000 Poitiers, France
- DACTIM-MIS Team, Laboratoire de Mathématiques Appliquées LMA, CNRS UMR 7348, 86021 Poitiers, France
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Teunissen WHT, Lavrova A, van den Bent M, van der Hoorn A, Warnert EAH, Smits M. Arterial spin labelling MRI for brain tumour surveillance: do we really need cerebral blood flow maps? Eur Radiol 2023; 33:8005-8013. [PMID: 37566264 PMCID: PMC10598159 DOI: 10.1007/s00330-023-10099-z] [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: 01/04/2023] [Revised: 06/09/2023] [Accepted: 07/01/2023] [Indexed: 08/12/2023]
Abstract
OBJECTIVES Arterial spin labelling (ASL) perfusion MRI is one of the available advanced MRI techniques for brain tumour surveillance. The first aim of this study was to investigate the correlation between quantitative cerebral blood flow (CBF) and non-quantitative perfusion weighted imaging (ASL-PWI) measurements. The second aim was to investigate the diagnostic accuracy of ASL-CBF and ASL-PWI measurements as well as visual assessment for identifying tumour progression. METHODS A consecutive cohort of patients who underwent 3-T MRI surveillance containing ASL for treated brain tumours was used. ROIs were drawn in representative parts of tumours in the ASL-CBF maps and copied to the ASL-PWI. ASL-CBF ratios and ASL-PWI ratios of the tumour ROI versus normal appearing white matter (NAWM) were correlated (Pearson correlation) and AUCs were calculated to assess diagnostic accuracy. Additionally, lesions were visually classified as hypointense, isointense, or hyperintense. We calculated accuracy at two thresholds: low threshold (between hypointense-isointense) and high threshold (between isointense-hyperintense). RESULTS A total of 173 lesions, both enhancing and non-enhancing, measured in 115 patients (93 glioma, 16 metastasis, and 6 lymphoma) showed a very high correlation of 0.96 (95% CI: 0.88-0.99) between ASL-CBF ratios and ASL-PWI ratios. AUC was 0.76 (95%CI: 0.65-0.88) for ASL-CBF ratios and 0.72 (95%CI: 0.58-0.85) for ASL-PWI ratios. Diagnostic accuracy of visual assessment for enhancing lesions was 0.72. CONCLUSION ASL-PWI ratios and ASL-CBF ratios showed a high correlation and comparable AUCs; therefore, quantification of ASL-CBF could be omitted in these patients. Visual classification had comparable diagnostic accuracy to the ASL-PWI or ASL-CBF ratios. CLINICAL RELEVANCE STATEMENT This study shows that CBF quantification of ASL perfusion MRI could be omitted for brain tumour surveillance and that visual assessment provides the same diagnostic accuracy. This greatly reduces the complexity of the use of ASL in routine clinical practice. KEY POINTS • Arterial spin labelling MRI for clinical brain tumour surveillance is undervalued and underinvestigated. • Non-quantitative and quantitative arterial spin labelling assessments show high correlation and comparable diagnostic accuracy. • Quantification of arterial spin labelling MRI could be omitted to improve daily clinical workflow.
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Affiliation(s)
- Wouter H T Teunissen
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
- Medical Delta, Delft, The Netherlands.
| | - Anna Lavrova
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology, University of Michigan Hospital, Ann Arbor, MI, USA
| | - Martin van den Bent
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC, Rotterdam, The Netherlands
| | - Anouk van der Hoorn
- Medical Imaging Center, Department of Radiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
- Medical Delta, Delft, The Netherlands.
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Zheng Z, Liu Y, Yin H, Ren P, Zhang T, Yang J, Wang Z. Evaluating T1, T2 Relaxation, and Proton Density in Normal Brain Using Synthetic MRI with Fast Imaging Protocol. Magn Reson Med Sci 2023:tn.2022-0161. [PMID: 37690836 DOI: 10.2463/mrms.tn.2022-0161] [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: 09/12/2023] Open
Abstract
Synthetic MRI is being increasingly used for the quantification of brain longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD) values. However, the effect of fast imaging protocols on these quantitative values has not been fully estimated. The purpose of this study was to investigate the effect of fast scan parameters on T1, T2, and PD measured with a multi-dynamic multi-echo (MDME) sequence of normal brain at 3.0T. Thirty-four volunteers were scanned using 3 MDME sequences with different scan times (named Fast, 2 min, 29 sec; Routine, 4 min, 07 sec; and Research, 7 min, 46 sec, respectively). The measured T1, T2, and PD in 18 volumes of interest (VOI) of brain were compared between the 3 sequences using rank sum test, t test, coefficients of variation (CVs) analysis, correlation analysis, and Bland-Altman analysis. We found that even though T1, T2, and PD were significantly different between the 3 sequences in most of the brain regions, the intersequence CVs were relatively low and linear correlation were high. Bland-Altman plots showed that most of the values fall within the 95% prediction limits. We concluded that fast imaging protocols of MDME sequence used in our study can potentially be used for quantitative evaluation of brain tissues. Since changing scan parameters can affect the measured T1, T2, and PD values, it is necessary to use consistent scan parameter for comparing or following up cases quantitatively.
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Affiliation(s)
- Zuofeng Zheng
- Department of Radiology, Beijing ChuiYangLiu Hospital
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
| | - Yawen Liu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
- School of Biological Science and Medical Engineering, Beihang University
| | - Hongxia Yin
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
| | - Pengling Ren
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
| | - Tingting Zhang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
- School of Biological Science and Medical Engineering, Beihang University
| | - Jiafei Yang
- Department of Radiology, Beijing ChuiYangLiu Hospital
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University
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9
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Hirschler L, Sollmann N, Schmitz‐Abecassis B, 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 K, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Emblem KE, Smits M, Petr J, Hangel G. Advanced MR Techniques for Preoperative Glioma Characterization: Part 1. J Magn Reson Imaging 2023; 57:1655-1675. [PMID: 36866773 PMCID: PMC10946498 DOI: 10.1002/jmri.28662] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/04/2023] Open
Abstract
Preoperative clinical magnetic resonance imaging (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 or lack thereof. 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 first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.
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Affiliation(s)
- Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenThe 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
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
- Medical Delta FoundationDelftThe Netherlands
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamThe Netherlands
- 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 UniversityKrems an der DonauAustria
| | - 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
| | - Nazmiye 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 UniversiteitAmsterdamThe Netherlands
- Cancer Center AmsterdamAmsterdamThe Netherlands
| | - 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 CenterThe HagueThe Netherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchLondonUK
| | - 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 PsychotherapyInternational Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes‐Bolyai UniversityCluj‐NapocaRomania
| | - 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
| | - Kathleen Schmainda
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - 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 MCRotterdamThe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftThe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University Hospital, BrnoBrnoCzech Republic
- Faculty of Medicine, Masaryk UniversityBrnoCzech Republic
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
| | - Marion Smits
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamThe Netherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamThe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - 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
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10
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Nabavizadeh A, Barkovich MJ, Mian A, Ngo V, Kazerooni AF, Villanueva-Meyer JE. Current state of pediatric neuro-oncology imaging, challenges and future directions. Neoplasia 2023; 37:100886. [PMID: 36774835 PMCID: PMC9945752 DOI: 10.1016/j.neo.2023.100886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/20/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
Imaging plays a central role in neuro-oncology including primary diagnosis, treatment planning, and surveillance of tumors. The emergence of quantitative imaging and radiomics provided an uprecedented opportunity to compile mineable databases that can be utilized in a variety of applications. In this review, we aim to summarize the current state of conventional and advanced imaging techniques, standardization efforts, fast protocols, contrast and sedation in pediatric neuro-oncologic imaging, radiomics-radiogenomics, multi-omics and molecular imaging approaches. We will also address the existing challenges and discuss future directions.
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Affiliation(s)
- Ali Nabavizadeh
- Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
| | - Matthew J Barkovich
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Ali Mian
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri, USA
| | - Van Ngo
- Saint Louis University School of Medicine, St. Louis, Missouri, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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11
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Martucci M, Russo R, Schimperna F, D’Apolito G, Panfili M, Grimaldi A, Perna A, Ferranti AM, Varcasia G, Giordano C, Gaudino S. Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives. Biomedicines 2023; 11:biomedicines11020364. [PMID: 36830900 PMCID: PMC9953338 DOI: 10.3390/biomedicines11020364] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/20/2023] [Accepted: 01/22/2023] [Indexed: 01/28/2023] Open
Abstract
MRI is undoubtedly the cornerstone of brain tumor imaging, playing a key role in all phases of patient management, starting from diagnosis, through therapy planning, to treatment response and/or recurrence assessment. Currently, neuroimaging can describe morphologic and non-morphologic (functional, hemodynamic, metabolic, cellular, microstructural, and sometimes even genetic) characteristics of brain tumors, greatly contributing to diagnosis and follow-up. Knowing the technical aspects, strength and limits of each MR technique is crucial to correctly interpret MR brain studies and to address clinicians to the best treatment strategy. This article aimed to provide an overview of neuroimaging in the assessment of adult primary brain tumors. We started from the basilar role of conventional/morphological MR sequences, then analyzed, one by one, the non-morphological techniques, and finally highlighted future perspectives, such as radiomics and artificial intelligence.
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Affiliation(s)
- Matia Martucci
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico “A. Gemelli” IRCCS, 00168 Rome, Italy
- Correspondence:
| | - Rosellina Russo
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico “A. Gemelli” IRCCS, 00168 Rome, Italy
| | | | - Gabriella D’Apolito
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico “A. Gemelli” IRCCS, 00168 Rome, Italy
| | - Marco Panfili
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico “A. Gemelli” IRCCS, 00168 Rome, Italy
| | - Alessandro Grimaldi
- Istituto di Radiologia, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Alessandro Perna
- Istituto di Radiologia, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | | | - Giuseppe Varcasia
- Istituto di Radiologia, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Carolina Giordano
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico “A. Gemelli” IRCCS, 00168 Rome, Italy
| | - Simona Gaudino
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico “A. Gemelli” IRCCS, 00168 Rome, Italy
- Istituto di Radiologia, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
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12
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Moya-Sáez E, de Luis-García R, Alberola-López C. Toward deep learning replacement of gadolinium in neuro-oncology: A review of contrast-enhanced synthetic MRI. FRONTIERS IN NEUROIMAGING 2023; 2:1055463. [PMID: 37554645 PMCID: PMC10406200 DOI: 10.3389/fnimg.2023.1055463] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/04/2023] [Indexed: 08/10/2023]
Abstract
Gadolinium-based contrast agents (GBCAs) have become a crucial part of MRI acquisitions in neuro-oncology for the detection, characterization and monitoring of brain tumors. However, contrast-enhanced (CE) acquisitions not only raise safety concerns, but also lead to patient discomfort, the need of more skilled manpower and cost increase. Recently, several proposed deep learning works intend to reduce, or even eliminate, the need of GBCAs. This study reviews the published works related to the synthesis of CE images from low-dose and/or their native -non CE- counterparts. The data, type of neural network, and number of input modalities for each method are summarized as well as the evaluation methods. Based on this analysis, we discuss the main issues that these methods need to overcome in order to become suitable for their clinical usage. We also hypothesize some future trends that research on this topic may follow.
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Affiliation(s)
- Elisa Moya-Sáez
- Laboratorio de Procesado de Imagen, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain
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13
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Nunez-Gonzalez L, van Garderen KA, Smits M, Jaspers J, Romero AM, Poot DHJ, Hernandez-Tamames JA. Pre-contrast MAGiC in treated gliomas: a pilot study of quantitative MRI. Sci Rep 2022; 12:21820. [PMID: 36528673 PMCID: PMC9759533 DOI: 10.1038/s41598-022-24276-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 11/14/2022] [Indexed: 12/23/2022] Open
Abstract
Quantitative MR imaging is becoming more feasible to be used in clinical work since new approaches have been proposed in order to substantially accelerate the acquisition and due to the possibility of synthetically deriving weighted images from the parametric maps. However, their applicability has to be thoroughly validated in order to be included in clinical practice. In this pilot study, we acquired Magnetic Resonance Image Compilation scans to obtain T1, T2 and PD maps in 14 glioma patients. Abnormal tissue was segmented based on conventional images and using a deep learning segmentation technique to define regions of interest (ROIs). The quantitative T1, T2 and PD values inside ROIs were analyzed using the mean, the standard deviation, the skewness and the kurtosis and compared to the quantitative T1, T2 and PD values found in normal white matter. We found significant differences in pre-contrast T1 and T2 values between abnormal tissue and healthy tissue, as well as between T1w-enhancing and non-enhancing regions. ROC analysis was used to evaluate the potential of quantitative T1 and T2 values for voxel-wise classification of abnormal/normal tissue (AUC = 0.95) and of T1w enhancement/non-enhancement (AUC = 0.85). A cross-validated ROC analysis found high sensitivity (73%) and specificity (73%) with AUCs up to 0.68 on the a priori distinction between abnormal tissue with and without T1w-enhancement. These results suggest that normal tissue, abnormal tissue, and tissue with T1w-enhancement are distinguishable by their pre-contrast quantitative values but further investigation is needed.
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Affiliation(s)
- Laura Nunez-Gonzalez
- grid.5645.2000000040459992XRadiology and Nuclear Medicine, Erasmus MC - University Medical Center, Rotterdam, The Netherlands
| | - Karin A. van Garderen
- grid.5645.2000000040459992XRadiology and Nuclear Medicine, Erasmus MC - University Medical Center, Rotterdam, The Netherlands ,grid.508717.c0000 0004 0637 3764Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Marion Smits
- grid.5645.2000000040459992XRadiology and Nuclear Medicine, Erasmus MC - University Medical Center, Rotterdam, The Netherlands ,grid.508717.c0000 0004 0637 3764Brain Tumor Center, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Jaap Jaspers
- grid.508717.c0000 0004 0637 3764Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Alejandra Méndez Romero
- grid.508717.c0000 0004 0637 3764Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Dirk H. J. Poot
- grid.5645.2000000040459992XRadiology and Nuclear Medicine, Erasmus MC - University Medical Center, Rotterdam, The Netherlands
| | - Juan A. Hernandez-Tamames
- grid.5645.2000000040459992XRadiology and Nuclear Medicine, Erasmus MC - University Medical Center, Rotterdam, The Netherlands
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14
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Hasse A, Bertini J, Foxley S, Jeong Y, Javed A, Carroll TJ. Application of a novel T1 retrospective quantification using internal references (T1-REQUIRE) algorithm to derive quantitative T1 relaxation maps of the brain. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2022; 32:1903-1915. [PMID: 36591562 PMCID: PMC9796586 DOI: 10.1002/ima.22768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 05/05/2022] [Accepted: 05/23/2022] [Indexed: 06/17/2023]
Abstract
Most MRI sequences used clinically are qualitative or weighted. While such images provide useful information for clinicians to diagnose and monitor disease progression, they lack the ability to quantify tissue damage for more objective assessment. In this study, an algorithm referred to as the T1-REQUIRE is presented as a proof-of-concept which uses nonlinear transformations to retrospectively estimate T1 relaxation times in the brain using T1-weighted MRIs, the appropriate signal equation, and internal, healthy tissues as references. T1-REQUIRE was applied to two T1-weighted MR sequences, a spin-echo and a MPRAGE, and validated with a reference standard T1 mapping algorithm in vivo. In addition, a multiscanner study was run using MPRAGE images to determine the effectiveness of T1-REQUIRE in conforming the data from different scanners into a more uniform way of analyzing T1-relaxation maps. The T1-REQUIRE algorithm shows good agreement with the reference standard (Lin's concordance correlation coefficients of 0.884 for the spin-echo and 0.838 for the MPRAGE) and with each other (Lin's concordance correlation coefficient of 0.887). The interscanner studies showed improved alignment of cumulative distribution functions after T1-REQUIRE was performed. T1-REQUIRE was validated with a reference standard and shown to be an effective estimate of T1 over a clinically relevant range of T1 values. In addition, T1-REQUIRE showed excellent data conformity across different scanners, providing evidence that T1-REQUIRE could be a useful addition to big data pipelines.
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Affiliation(s)
- Adam Hasse
- Graduate Program in Medical PhysicsUniversity of ChicagoChicagoIllinoisUSA
- Department of RadiologyUniversity of ChicagoChicagoIllinois
| | - Julian Bertini
- Graduate Program in Medical PhysicsUniversity of ChicagoChicagoIllinoisUSA
- Department of RadiologyUniversity of ChicagoChicagoIllinois
| | - Sean Foxley
- Department of RadiologyUniversity of ChicagoChicagoIllinois
| | - Yong Jeong
- Department of RadiologyUniversity of ChicagoChicagoIllinois
| | - Adil Javed
- Department of NeurologyUniversity of ChicagoChicagoIllinoisUSA
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15
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A Head-to-Head Comparison of 18F-Fluorocholine PET/CT and Conventional MRI as Predictors of Outcome in IDH Wild-Type High-Grade Gliomas. J Clin Med 2022; 11:jcm11206065. [PMID: 36294385 PMCID: PMC9605635 DOI: 10.3390/jcm11206065] [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: 08/22/2022] [Revised: 10/01/2022] [Accepted: 10/06/2022] [Indexed: 01/24/2023] Open
Abstract
(1) Aim: To study the associations between imaging parameters derived from contrast-enhanced MRI (CE-MRI) and 18F-fluorocholine PET/CT and their performance as prognostic predictors in isocitrate dehydrogenase wild-type (IDH-wt) high-grade gliomas. (2) Methods: A prospective, multicenter study (FuMeGA: Functional and Metabolic Glioma Analysis) including patients with baseline CE-MRI and 18F-fluorocholine PET/CT and IDH wild-type high-grade gliomas. Clinical variables such as performance status, extent of surgery and adjuvant treatments (Stupp protocol vs others) were obtained and used to discriminate overall survival (OS) and progression-free survival (PFS) as end points. Multilesionality was assessed on the visual analysis of PET/CT and CE-MRI images. After tumor segmentation, standardized uptake value (SUV)-based variables for PET/CT and volume-based and geometrical variables for PET/CT and CE-MRI were calculated. The relationships among imaging techniques variables and their association with prognosis were evaluated using Pearson’s chi-square test and the t-test. Receiver operator characteristic, Kaplan−Meier and Cox regression were used for the survival analysis. (3) Results: 54 patients were assessed. The median PFS and OS were 5 and 11 months, respectively. Significant strong relationships between volume-dependent variables obtained from PET/CT and CE-MRI were found (r > 0.750, p < 0.05). For OS, significant associations were found with SUVmax, SUVpeak, SUVmean and sphericity (HR: 1.17, p = 0.035; HR: 1.24, p = 0.042; HR: 1.62, p = 0.040 and HR: 0.8, p = 0.022, respectively). Among clinical variables, only Stupp protocol and age showed significant associations with OS and PFS. No CE-MRI derived variables showed significant association with prognosis. In multivariate analysis, age (HR: 1.04, p = 0.002), Stupp protocol (HR: 2.81, p = 0.001), multilesionality (HR: 2.20, p = 0.013) and sphericity (HR: 0.79, p = 0.027) derived from PET/CT showed independent associations with OS. For PFS, only age (HR: 1.03, p = 0.021) and treatment protocol (HR: 2.20, p = 0.008) were significant predictors. (4) Conclusions: 18F-fluorocholine PET/CT metabolic and radiomic variables were robust prognostic predictors in patients with IDH-wt high-grade gliomas, outperforming CE-MRI derived variables.
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16
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Konar AS, Paudyal R, Shah AD, Fung M, Banerjee S, Dave A, Lee N, Hatzoglou V, Shukla-Dave A. Qualitative and Quantitative Performance of Magnetic Resonance Image Compilation (MAGiC) Method: An Exploratory Analysis for Head and Neck Imaging. Cancers (Basel) 2022; 14:cancers14153624. [PMID: 35892883 PMCID: PMC9331960 DOI: 10.3390/cancers14153624] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 01/27/2023] Open
Abstract
The present exploratory study investigates the performance of a new, rapid, synthetic MRI method for diagnostic image quality assessment and measurement of relaxometry metric values in head and neck (HN) tumors and normal-appearing masseter muscle. The multi-dynamic multi-echo (MDME) sequence was used for data acquisition, followed by synthetic image reconstruction on a 3T MRI scanner for 14 patients (3 untreated and 11 treated). The MDME enables absolute quantification of physical tissue properties, including T1 and T2, with a shorter scan time than the current state-of-the-art methods used for relaxation measurements. The vendor termed the combined package MAGnetic resonance imaging Compilation (MAGiC). In total, 48 regions of interest (ROIs) were analyzed, drawn on normal-appearing masseter muscle and tumors in the HN region. Mean T1 and T2 values obtained from normal-appearing muscle were 880 ± 52 ms and 46 ± 3 ms, respectively. Mean T1 and T2 values obtained from tumors were 1930 ± 422 ms and 77 ± 13 ms, respectively, for the untreated group, 1745 ± 410 ms and 107 ± 61 ms, for the treated group. A total of 1552 images from both synthetic MRI and conventional clinical imaging were assessed by the radiologists to provide the rating for T1w and T2w image contrasts. The synthetically generated qualitative T2w images were acceptable and comparable to conventional diagnostic images (93% acceptability rating for both). The acceptability ratings for MAGiC-generated T1w, and conventional images were 64% and 100%, respectively. The benefit of MAGiC in HN imaging is twofold, providing relaxometry maps in a clinically feasible time and the ability to generate a different combination of contrast images in a single acquisition.
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Affiliation(s)
- Amaresha Shridhar Konar
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (A.S.K.); (R.P.)
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (A.S.K.); (R.P.)
| | - Akash Deelip Shah
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (A.D.S.); (V.H.)
| | - Maggie Fung
- General Electric Health Care, New York, NY 10065, USA; (M.F.); (S.B.)
| | | | - Abhay Dave
- Touro College of Osteopathic Medicine, New York, NY 10027, USA;
| | - Nancy Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (A.D.S.); (V.H.)
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (A.S.K.); (R.P.)
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (A.D.S.); (V.H.)
- Correspondence: ; Tel.: +1-212-639-3184
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17
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Quantitative Synthetic Magnetic Resonance Imaging for Brain Metastases: A Feasibility Study. Cancers (Basel) 2022; 14:cancers14112651. [PMID: 35681631 PMCID: PMC9179589 DOI: 10.3390/cancers14112651] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/16/2022] [Accepted: 05/20/2022] [Indexed: 02/01/2023] Open
Abstract
Simple Summary This preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. In addition, synthetic MR could provide contrast images analogous to standard T1- and T2-weighted images. The reproducibility and repeatability of this method have been previously established for brain imaging. This study reports and analyzes the quantitative T1 and T2 values for 11 BM patients (17 BM lesions) with a total of 82 regions of interest (ROIs) delineated by an experienced neuroradiologist. The initial results, which need to be further validated in a larger patient cohort, demonstrated the ability of T1 and T2 metric values to characterize BMs and normal-appearing brain tissues. The T1 and T2 metrics could be potential surrogate biomarkers for BM free water content (cellularity) and tumor morphology, respectively. Abstract The present preliminary study aims to characterize brain metastases (BM) using T1 and T2 maps generated from newer, rapid, synthetic MRI (MAGnetic resonance image Compilation; MAGiC) in a clinical setting. We acquired synthetic MRI data from 11 BM patients on a 3T scanner. A multiple-dynamic multiple-echo (MDME) sequence was used for data acquisition and synthetic image reconstruction, including post-processing. MDME is a multi-contrast sequence that enables absolute quantification of physical tissue properties, including T1 and T2, independent of the scanner settings. In total, 82 regions of interest (ROIs) were analyzed, which were obtained from both normal-appearing brain tissue and BM lesions. The mean values obtained from the 48 normal-appearing brain tissue regions and 34 ROIs of BM lesions (T1 and T2) were analyzed using standard statistical methods. The mean T1 and T2 values were 1143 ms and 78 ms, respectively, for normal-appearing gray matter, 701 ms and 64 ms for white matter, and 4206 ms and 390 ms for cerebrospinal fluid. For untreated BMs, the mean T1 and T2 values were 1868 ms and 100 ms, respectively, and 2211 ms and 114 ms for the treated group. The quantitative T1 and T2 values generated from synthetic MRI can characterize BM and normal-appearing brain tissues.
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Ge X, Wang M, Ma H, Zhu K, Wei X, Li M, Zhai X, Shen Y, Huang X, Hou M, Liu W, Wang M, Wang X. Investigated diagnostic value of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling and diffusion-weighted imaging in the grading of glioma. Magn Reson Imaging 2021; 86:20-27. [PMID: 34808303 DOI: 10.1016/j.mri.2021.11.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/27/2021] [Accepted: 11/15/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND To investigate the performance of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling (pCASL) and diffusion-weighted imaging (DWI) in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs) and to compare with the conventional MRI. METHODS Seventy-two patients with gliomas (including 27 LGGs and 45 HGGs) were studied using synthetic magnetic resonance imaging (sy-MRI), pCASL, and DWI with a 3.0 T MR scanner. T1 relaxometry (T1), T2 relaxometry (T2), as well as proton density (PD) from sy-MRI, cerebral blood flow (CBF) from pCASL, apparent diffusion coefficient (ADC) from DWI and enhancement quality (EQ), proportion enhancing (PE) from conventional contrast enhanced image based Visually-Accessible-Rembrandt-Images (VASARI) scoring system, were all analyzed by two radiologists. The Student's t-test, Mann-Whitney U test or Fisher's exact test was used to compare the parameters between LGGs and HGGs. The diagnostic performance of each parameter and their combination for glioma grading were analyzed. RESULTS Significant statistical differences in T1, PD, CBF, ADC, EQ and PE are observed between LGGs and HGGs (all P < 0.001). The ADC values have higher discrimination abilities compared with other univariable parameters, with the AUC of 0.905. AUC values for conventional contrast-enhanced method, EQ and PE from VASARI, and conventional contrast-free method, CBF + ADC, are 0.873 and 0.912 respectively. The combined T1, PD, CBF and ADC model had the best performance for differentiating LGGs and HGGs with AUC, sensitivity and specificity of 0.993, 95.5%, 100%, respectively. CONCLUSIONS Relaxometry parameters derived from synthetic MRI contributed to the discrimination of low-grade gliomas from high-grade gliomas. Proposed contrast-free approach combining T1, PD, CBF and ADC showed a strong discriminative power, and outperformed conventional approaches.
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Affiliation(s)
- Xin Ge
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, China
| | - Minglei Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Hui Ma
- Department of Neurosurgery, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Kai Zhu
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
| | | | - Min Li
- GE Healthcare, MR Enhancement Application, Beijing, China
| | - Xuefeng Zhai
- Department of Pathology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Ying Shen
- School of Nursing, Ningxia Medical University, Yinchuan, China
| | - Xueying Huang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Mingli Hou
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Wenxiao Liu
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, China
| | - Minxing Wang
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, China
| | - Xiaodong Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China.
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19
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Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas. Cancer J 2021; 27:344-352. [PMID: 34570448 DOI: 10.1097/ppo.0000000000000545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
ABSTRACT Advanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.
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20
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Chekhonin IV, Batalov AI, Zakharova NE, Pogosbekyan EL, Nikitin PV, Bykanov AE, Pitskhelauri DI, Pronin IN. [Magnetic resonance relaxometry in high-grade glioma subregion assessment - neuroimaging and morphological correlates]. ZHURNAL VOPROSY NEĬROKHIRURGII IMENI N. N. BURDENKO 2021; 85:41-48. [PMID: 34463449 DOI: 10.17116/neiro20218504141] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To analyze the differences of high-grade glioma subregions using magnetic resonance relaxometry with compilation of images (MAGiC) and arterial spin labeling (ASL), as well as to compare quantitative measurements of these techniques with morphological data. MATERIAL AND METHODS The study enrolled 35 patients with newly diagnosed supratentorial gliomas (23 - grade IV, 12 - grade III). We measured relaxometric values (T1, T2, proton density), tumor blood flow (TBF) in glioma subregions and normal-appearing brain matter. Neuronavigation was intraoperatively used to obtain tissue samples from active tumor growth zone, perifocal infiltrative edema zone and adjacent brain matter along surgical approach. RESULTS ASL perfusion revealed higher tumor blood flow (TBF) in active tumor growth region compared to perifocal infiltrative edema zone (p<0.01). Relaxometric values (T1, T2, proton density) in perifocal zone were higher (p<0.01) compared to adjacent intact white matter along surgical approach. However, there were no differences in TBF between these zones. Proton density in tumor-adjacent intact white matter was higher (p<0.01) compared to normal-appearing white matter in ipsilateral hemisphere. There was inverse correlation between T2 and TBF in active tumor growth zone (Spearman rank R= -0.58; p=0.0016). We found inverse correlation between T2 and Ki67 proliferative index and direct correlation between TBF and Ki67 in this zone. Nevertheless, these relationships were insignificant after multiple test adjustment. CONCLUSION Our study advocates for complementary power of ASL perfusion and MR relaxometry in assessment of high-grade brain glioma subregions. More malignant tumor zones tend to have higher TBF and shorter T2. Further investigation is needed to prove the capability of MAGiC to reveal foci of increased relaxometric values in tumor-adjacent normal-appearing white matter.
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Affiliation(s)
| | - A I Batalov
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | | | - P V Nikitin
- Burdenko Neurosurgical Center, Moscow, Russia
| | - A E Bykanov
- Burdenko Neurosurgical Center, Moscow, Russia
| | | | - I N Pronin
- Burdenko Neurosurgical Center, Moscow, Russia
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21
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Maurer GD, Tichy J, Harter PN, Nöth U, Weise L, Quick-Weller J, Deichmann R, Steinbach JP, Bähr O, Hattingen E. Matching Quantitative MRI Parameters with Histological Features of Treatment-Naïve IDH Wild-Type Glioma. Cancers (Basel) 2021; 13:cancers13164060. [PMID: 34439213 PMCID: PMC8392045 DOI: 10.3390/cancers13164060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 08/05/2021] [Accepted: 08/10/2021] [Indexed: 11/16/2022] Open
Abstract
Quantitative MRI allows to probe tissue properties by measuring relaxation times and may thus detect subtle changes in tissue composition. In this work we analyzed different relaxation times (T1, T2, T2* and T2') and histological features in 321 samples that were acquired from 25 patients with newly diagnosed IDH wild-type glioma. Quantitative relaxation times before intravenous application of gadolinium-based contrast agent (GBCA), T1 relaxation time after GBCA as well as the relative difference between T1 relaxation times pre-to-post GBCA (T1rel) were compared with histopathologic features such as the presence of tumor cells, cell and vessel density, endogenous markers for hypoxia and cell proliferation. Image-guided stereotactic biopsy allowed for the attribution of each tissue specimen to its corresponding position in the respective relaxation time map. Compared to normal tissue, T1 and T2 relaxation times and T1rel were prolonged in samples containing tumor cells. The presence of vascular proliferates was associated with higher T1rel values. Immunopositivity for lactate dehydrogenase A (LDHA) involved slightly longer T1 relaxation times. However, low T2' values, suggesting high amounts of deoxyhemoglobin, were found in samples with elevated vessel densities, but not in samples with increased immunopositivity for LDHA. Taken together, some of our observations were consistent with previous findings but the correlation of quantitative MRI and histologic parameters did not confirm all our pathophysiology-based assumptions.
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Affiliation(s)
- Gabriele D. Maurer
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
- Correspondence:
| | - Julia Tichy
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
| | - Patrick N. Harter
- Institute of Neurology (Edinger Institute), Goethe University Hospital, 60528 Frankfurt am Main, Germany;
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, 60590 Frankfurt am Main, Germany
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), 60596 Frankfurt am Main, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, 60528 Frankfurt am Main, Germany; (U.N.); (R.D.)
| | - Lutz Weise
- Division of Neurosurgery, Dalhousie University Halifax, Halifax, NS B3H 4R2, Canada;
| | - Johanna Quick-Weller
- Department of Neurosurgery, Goethe University Hospital, 60528 Frankfurt am Main, Germany;
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, 60528 Frankfurt am Main, Germany; (U.N.); (R.D.)
| | - Joachim P. Steinbach
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
| | - Oliver Bähr
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
- Department of Neurology, Klinikum Aschaffenburg-Alzenau, 63739 Aschaffenburg, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University Hospital, 60528 Frankfurt am Main, Germany;
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22
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Sun Y, Wang X, Bu X. LINC02381 contributes to cell proliferation and hinders cell apoptosis in glioma by transcriptionally enhancing CBX5. Brain Res Bull 2021; 176:121-129. [PMID: 34274429 DOI: 10.1016/j.brainresbull.2021.07.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 05/25/2021] [Accepted: 07/12/2021] [Indexed: 01/11/2023]
Abstract
Glioma, featured with high incidence and low survival rate, is the most common type of primary brain tumor, severely affecting human life worldwide. LINC02381 is an interesting lncRNA functioning as oncogenic lncRNA in some cancers but as tumor-suppressor in others, but no report demonstrates its association with and function in glioma. Intriguingly, we found in a bioinformatics website LncRNADisease that LINC02381 was closely related to malignant glioma, so this study aimed to figure out the expression and function of LINC02381 in glioma. By RT-qPCR, we confirmed LINC02381 upregulation in glioma cells. Functional experiments demonstrated that LINC02381 knockdown repressed glioma cell proliferation and induced apoptosis. Boinformatics tools and RT-qPCR revealed the positive correlation between LINC02381 and CBX5 in glioma cells. More importantly, we confirmed that LINC02381 could interact and work synergistically with CEBPβ to bind to CBX5 promoter and activate CBX5 transcriptionally. Additionally, rescue experiments indicated that CBX5 up-regulation reversed the decline in cell proliferation and the augment in cell apoptosis caused by LINC02381 knockdown. To conclude, LINC02381 could facilitate CBX5 transcription via interaction with CEBPβ, thus exerting its oncogenic role in glioma cells, which could contribute to better understanding of glioma.
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Affiliation(s)
- Yong Sun
- Department of Neurosurgery, Henan Provincial People's Hospital, No.7 Weiwu Road, Jinshui District, Zhengzhou, 450003, Henan, China
| | - Xinjun Wang
- Department of Neurosurgery, Fifth Affiliated Hospital of Zhengzhou University, No.3 Kangfuqian Street, Erqi District, Zhengzhou, Henan, 450052, China
| | - Xingyao Bu
- Department of Neurosurgery, Henan Provincial People's Hospital, No.7 Weiwu Road, Jinshui District, Zhengzhou, 450003, Henan, China.
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23
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Quantitative mapping of individual voxels in the peritumoral region of IDH-wildtype glioblastoma to distinguish between tumor infiltration and edema. J Neurooncol 2021; 153:251-261. [PMID: 33905055 DOI: 10.1007/s11060-021-03762-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 04/20/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE The peritumoral region (PTR) in glioblastoma (GBM) represents a combination of infiltrative tumor and vasogenic edema, which are indistinguishable on magnetic resonance imaging (MRI). We developed a radiomic signature by using imaging data from low grade glioma (LGG) (marker of tumor) and PTR of brain metastasis (BM) (marker of edema) and applied it on the GBM PTR to generate probabilistic maps. METHODS 270 features were extracted from T1-weighted, T2-weighted, and apparent diffusion coefficient maps in over 3.5 million voxels of LGG (36 segments) and BM (45 segments) scanned in a 1.5T MRI. A support vector machine classifier was used to develop the radiomics model from approximately 50% voxels (downsampled to 10%) and validated with the remaining. The model was applied to over 575,000 voxels of the PTR of 10 patients with GBM to generate a quantitative map using Platt scaling (infiltrative tumor vs. edema). RESULTS The radiomics model had an accuracy of 0.92 and 0.79 in the training and test set, respectively (LGG vs. BM). When extrapolated on the GBM PTR, 9 of 10 patients had a higher percentage of voxels with a tumor-like signature over radiological recurrence areas. In 7 of 10 patients, the areas under curves (AUC) were > 0.50 confirming a positive correlation. Including all the voxels from the GBM patients, the infiltration signature had an AUC of 0.61 to predict recurrence. CONCLUSION A radiomic signature can demarcate areas of microscopic tumors from edema in the PTR of GBM, which correlates with areas of future recurrence.
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Auer TA. Advanced MR techniques in glioblastoma imaging-upcoming challenges and how to face them. Eur Radiol 2021; 31:6652-6654. [PMID: 33890147 PMCID: PMC8379107 DOI: 10.1007/s00330-021-07978-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 03/11/2021] [Accepted: 04/01/2021] [Indexed: 12/29/2022]
Abstract
KEY POINTS • The management of gliomas has changed dramatically since the presentation of the revised WHO Classification of Tumors of the Central Nervous System in 2016 emphasizing the tumor heterogeneity based on their molecular profile.• The need for a more noninvasive characterization of glioblastomas (GBM) by establishing reliable imaging biomarkers to predict patient outcome and improve therapy monitoring is bigger than ever.• Multiparametric MRI, including promising newer techniques like electrical property tomography and mapping, may have the potential to provide enough information for intelligent imaging postprocessing algorithms to face the challenge by decoding GBM heterogeneity noninvasively.
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Affiliation(s)
- Timo A Auer
- Department of Radiology, Campus Virchow-Klinikum, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany. .,Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Straße 2, 10178, Berlin, Germany.
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