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Hoefnagels FWA, De Witt Hamer P, Sanz-Arigita E, Idema S, Kuijer JPA, Pouwels PJW, Barkhof F, Vandertop WP. Differentiation of edema and glioma infiltration: proposal of a DTI-based probability map. J Neurooncol 2014; 120:187-98. [PMID: 25079117 DOI: 10.1007/s11060-014-1544-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2013] [Accepted: 07/05/2014] [Indexed: 12/22/2022]
Abstract
Conflicting results on differentiating edema and glioma by diffusion tensor imaging (DTI) are possibly attributable to dissimilar spatial distribution of the lesions. Combining DTI-parameters and enhanced registration might improve prediction. Regions of edema surrounding 22 metastases were compared to tumor-infiltrated regions from WHO grade 2 (12), 3 (10) and 4 (18) gliomas. DTI data was co-registered using Tract Based Spatial Statistics (TBSS), to measure Fractional Anisotropy (FA) and Mean Diffusivity (MD) for white matter only, and relative changes compared to matching reference regions (dFA and dMD). A two-factor principal component analysis (PCA) on metastasis and grade 2 glioma was performed to explore a possible differentiating combined factor. Edema demonstrated equal MD and higher FA compared to grade 2 and 3 glioma (P < 0.001), but did not differ from glioblastoma. Differences were non-significant when corrected for spatial distribution, since reference regions differed strongly (P < 0.001). The second component of the PCA (PCA-C2) did differentiate edema and low-grade tumor (sensitivity 91.7%, specificity 86.4%). PCA-C2 scores were plotted voxel-wise as a probability-map, discerning distinct areas of presumed edema or tumor infiltration. Correction of spatial dependency appears essential when differentiating glioma from edema. A tumor-infiltration probability-map is presented, based on supplementary information of multiple DTI parameters and spatial normalization.
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Affiliation(s)
- Friso W A Hoefnagels
- Department Neurosurgery, Neurosurgical Center Amsterdam, VU University Medical Center, P.O. Box 7057, 1007, MB, Amsterdam, The Netherlands,
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Parra NA, Maudsley AA, Gupta RK, Ishkanian F, Huang K, Walker GR, Padgett K, Roy B, Panoff J, Markoe A, Stoyanova R. Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes. Int J Radiat Oncol Biol Phys 2014; 90:376-84. [PMID: 25066215 DOI: 10.1016/j.ijrobp.2014.03.049] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2013] [Revised: 02/27/2014] [Accepted: 03/28/2014] [Indexed: 11/19/2022]
Abstract
PURPOSE Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]). METHODS AND MATERIALS Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV46 and CTV60, respectively). MTVCho and MTVNAA were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue. RESULTS The MRSI coverage of the brain was between 70% and 76%. The MTVNAA were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTVCho was outside of the edema (median, 33%) and for some patients it was also outside of the CTV46 and CTV60. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTVCho for these patients were outside of CTV60. CONCLUSIONS This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on metabolic information.
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Affiliation(s)
- N Andres Parra
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Andrew A Maudsley
- Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida
| | - Rakesh K Gupta
- Department of Radiology & Imaging, Fortis Memorial Research Institute, Gurgaon, Haryana, India
| | - Fazilat Ishkanian
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Kris Huang
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Gail R Walker
- Biostatistics and Bioinformatics Core Resource, Sylvester Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Kyle Padgett
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida; Department of Radiology, University of Miami Miller School of Medicine, Miami, Florida
| | - Bhaswati Roy
- Department of Radiology & Imaging, Fortis Memorial Research Institute, Gurgaon, Haryana, India
| | - Joseph Panoff
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Arnold Markoe
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida
| | - Radka Stoyanova
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida.
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Fudaba H, Shimomura T, Abe T, Matsuta H, Momii Y, Sugita K, Ooba H, Kamida T, Hikawa T, Fujiki M. Comparison of multiple parameters obtained on 3T pulsed arterial spin-labeling, diffusion tensor imaging, and MRS and the Ki-67 labeling index in evaluating glioma grading. AJNR Am J Neuroradiol 2014; 35:2091-8. [PMID: 24994829 DOI: 10.3174/ajnr.a4018] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Pulsed arterial spin-labeling, DTI, and MR spectroscopy provide useful data for tumor evaluation. We evaluated multiple parameters by using these pulse sequences and the Ki-67 labeling index in newly diagnosed supratentorial gliomas. MATERIALS AND METHODS All 32 patients, with grade II (3 each of diffuse astrocytoma, oligodendroglioma, and oligoastrocytoma), grade III (3 anaplastic astrocytomas, 4 anaplastic oligodendrogliomas, and 1 anaplastic oligoastrocytoma), and grade IV (14 glioblastomas and 1 glioblastoma with an oligodendroglioma component) cases underwent pulsed arterial spin-labeling, DTI, and MR spectroscopy studies by using 3T MR imaging. The following variables were used to compare the tumors: relative cerebral blood flow, fractional anisotropy; ADC tumor/normal ratios; and the Cho/Cr, NAA/Cho, NAA/Cr, and lactate/Cr ratios. A logistic regression and receiver operating characteristic analysis were used to assess parameters with a high sensitivity and specificity to identify the threshold values for separate grading. We compared the Ki-67 index with various MR imaging parameters in tumor specimens. RESULTS Significant correlations were observed between the Ki-67 index and the mean, maximum, and minimum ADC, Cho/Cr, and lactate/Cr ratios. The receiver operating characteristic analysis showed that the combination of the minimum ADC and Cho/Cr ratios could differentiate low-grade and high-grade gliomas, with a sensitivity and specificity of 87.0% and 88.9%, respectively. The mean and maximum relative cerebral blood flow ratios were used to classify glioblastomas from other-grade astrocytomas, with a sensitivity and specificity of 92.9% and 83.3%, respectively. CONCLUSIONS Our findings indicate that pulsed arterial spin-labeling, DTI, and MR spectroscopy are useful for predicting glioma grade. Additionally, the parameters obtained on DTI and MR spectroscopy closely correlated with the proliferative potential of gliomas.
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Affiliation(s)
- H Fudaba
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
| | - T Shimomura
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - T Abe
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - H Matsuta
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - Y Momii
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - K Sugita
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - H Ooba
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - T Kamida
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - T Hikawa
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - M Fujiki
- From the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
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Improved Diagnostic Accuracy With Multiparametric Magnetic Resonance Imaging of the Breast Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging, Diffusion-Weighted Imaging, and 3-Dimensional Proton Magnetic Resonance Spectroscopic Imaging. Invest Radiol 2014; 49:421-30. [DOI: 10.1097/rli.0000000000000029] [Citation(s) in RCA: 100] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Maudsley AA, Gupta RK, Stoyanova R, Parra NA, Roy B, Sheriff S, Hussain N, Behari S. Mapping of glycine distributions in gliomas. AJNR Am J Neuroradiol 2014; 35:S31-6. [PMID: 24481330 DOI: 10.3174/ajnr.a3845] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND PURPOSE Increased glycine concentration in the brain is associated with altered metabolism in cancer and can be detected by using in vivo MR spectroscopy. This has been proposed as a marker for grade IV gliomas; however, little is known about the potential significance and frequency of in vivo glycine observation. The purpose of this study was to examine the rate of occurrence and spatial distribution of glycine observation with respect to other MR imaging parameters. MATERIALS AND METHODS Data from volumetric whole-brain MR spectroscopic imaging of 59 subjects with glioma were analyzed with glycine included in the spectral model. The associations of the signal amplitude and spatial distributions of glycine with findings from contrast-enhanced T1, perfusion, and diffusion MR imaging were then examined. RESULTS Glycine was detected in 24% of all studies, though with a wide range of signal amplitude and extent of the spatial distributions. While more commonly seen in grade IV tumors (42% of studies), relatively large concentrations were also detected in grade II and III gliomas. Coanalysis with other metabolites indicated a strong association with choline and that glycine was frequently seen to be overlapping with, and adjacent to, areas of high lactate concentration. Increased glycine was always associated with contrast enhancement and areas of increased cerebral blood flow, but without any clear association with other image parameters. CONCLUSIONS Detection of increased glycine in gliomas appears to identify a subgroup of tumors and areas of increased proliferation.
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Affiliation(s)
- A A Maudsley
- From the Departments of Radiology (A.A.M., S.S.)
| | - R K Gupta
- Department of Radiology and Imaging (R.K.G., B.R.), Fortis Memorial Research Institute, Gurgaon, Haryana, India
| | - R Stoyanova
- Radiation Oncology (R.S., N.A.P.), University of Miami, Miami, Florida
| | - N A Parra
- Radiation Oncology (R.S., N.A.P.), University of Miami, Miami, Florida
| | - B Roy
- Department of Radiology and Imaging (R.K.G., B.R.), Fortis Memorial Research Institute, Gurgaon, Haryana, India
| | - S Sheriff
- From the Departments of Radiology (A.A.M., S.S.)
| | - N Hussain
- Department of Pathology (N.H.), Ram Manohar Lohia, Institute of Medical Sciences, Lucknow, India
| | - S Behari
- Department of Neurosurgery (S.B.), Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
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Chawla S, Wang S, Kim S, Sheriff S, Lee P, Rengan R, Lin A, Melhem E, Maudsley A, Poptani H. Radiation Injury to the Normal Brain Measured by 3D-Echo-Planar Spectroscopic Imaging and Diffusion Tensor Imaging: Initial Experience. J Neuroimaging 2013; 25:97-104. [DOI: 10.1111/jon.12070] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2013] [Revised: 07/08/2013] [Accepted: 08/03/2013] [Indexed: 12/14/2022] Open
Affiliation(s)
- Sanjeev Chawla
- Department of Radiology; University of Pennsylvania; Philadelphia PA
| | - Sumei Wang
- Department of Radiology; University of Pennsylvania; Philadelphia PA
| | - Sungheon Kim
- Department of Radiology; New York University; New York NY
| | | | - Peter Lee
- Department of Radiology; University of Pennsylvania; Philadelphia PA
| | - Ramesh Rengan
- Department of Radiation Oncology; University of Pennsylvania; Philadelphia PA
| | - Alexander Lin
- Department of Radiation Oncology; University of Pennsylvania; Philadelphia PA
| | - Elias Melhem
- Department of Radiology; University of Pennsylvania; Philadelphia PA
| | | | - Harish Poptani
- Department of Radiology; University of Pennsylvania; Philadelphia PA
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Maudsley AA, Roy B, Gupta RK, Sheriff S, Awasthi R, Gu M, Husain N, Mohakud S, Behari S, Spielman DM. Association of metabolite concentrations and water diffusivity in normal appearing brain tissue with glioma grade. J Neuroimaging 2013; 24:585-589. [PMID: 24251857 DOI: 10.1111/jon.12063] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2013] [Revised: 07/09/2013] [Accepted: 08/03/2013] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE Studies of brain tumors have identified altered tissue metabolism and water diffusion in MRI normal appearing tissue regions. In this retrospective study the relationship of these imaging measures with tumor grade in gliomas was investigated. METHODS MR spectroscopic imaging of whole brain and mean diffusivity (MD) measurements were obtained in subjects with untreated glioma and from normal control subjects. Mean metabolite values for N-acetylaspartate (NAA), total creatine (Cre), and total choline (Cho) were obtained in gray- and white-matter regions for the hemisphere contralateral to the tumor location, and MD values were obtained from contralateral normal-appearing white matter. Analyses tested for differences in mean values between subject groups while accounting for age. RESULTS Analysis demonstrated increased NAA/Cre and MD, and decreased Cho/NAA for all tumor grades relative to control values. Differences between tumor grades were also observed for NAA, NAA/Cre, and Cho/NAA. Abnormal values of water diffusion were also observed, but with only a weak association between alterations in diffusion and tissue metabolites. CONCLUSIONS This study supports previous observations of altered tissue metabolism and water diffusion in normal-appearing white matter while additionally finding differences of metabolite values in gray matter and an association with tumor grade.
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Affiliation(s)
| | - Bhaswati Roy
- Departments of Radiodiagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
| | - Rakesh K Gupta
- Departments of Radiodiagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
| | | | - Rishi Awasthi
- Departments of Radiodiagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
| | - Meng Gu
- Department of Radiology, Stanford University, California
| | - Nuzhat Husain
- Department of Pathology, Ram Manohar Lohia, Institute of Medical Sciences, Lucknow, India
| | - Sudipa Mohakud
- Departments of Radiodiagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
| | - Sanjay Behari
- Departments of Neurosurgery, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India
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Yoon JH, Kim JH, Kang WJ, Sohn CH, Choi SH, Yun TJ, Eun Y, Song YS, Chang KH. Grading of Cerebral Glioma with Multiparametric MR Imaging and 18F-FDG-PET: Concordance and Accuracy. Eur Radiol 2013; 24:380-9. [DOI: 10.1007/s00330-013-3019-3] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2013] [Revised: 08/17/2013] [Accepted: 08/31/2013] [Indexed: 10/26/2022]
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