scholarly journals Combined Diffusion Tensor and Magnetic Resonance Spectroscopic Imaging Methodology for Automated Regional Brain Analysis: Application in a Normal Pediatric Population

2017 ◽  
Vol 39 (5) ◽  
pp. 413-429 ◽  
Author(s):  
Nirmalya Ghosh ◽  
Barbara Holshouser ◽  
Udo Oyoyo ◽  
Stanley Barnes ◽  
Karen Tong ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Spectroscopic Imaging ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Brain Maturation ◽  
Normal Brain ◽  
Computational Tools ◽  
Percent Change ◽  
Mrsi Data ◽  
Age Range

During human brain development, anatomic regions mature at different rates. Quantitative anatomy-specific analysis of longitudinal diffusion tensor imaging (DTI) and magnetic resonance spectroscopic imaging (MRSI) data may improve our ability to quantify and categorize these maturational changes. Computational tools designed to quickly fuse and analyze imaging information from multiple, technically different datasets would facilitate research on changes during normal brain maturation and for comparison to disease states. In the current study, we developed a complete battery of computational tools to execute such data analyses that include data preprocessing, tract-based statistical analysis from DTI data, automated brain anatomy parsing from T1-weighted MR images, assignment of metabolite information from MRSI data, and co-alignment of these multimodality data streams for reporting of region-specific indices. We present statistical analyses of regional DTI and MRSI data in a cohort of normal pediatric subjects (n = 72; age range: 5-18 years; mean 12.7 ± 3.3 years) to establish normative data and evaluate maturational trends. Several regions showed significant maturational changes for several DTI parameters and MRSI ratios, but the percent change over the age range tended to be small. In the subcortical region (combined basal ganglia [BG], thalami [TH], and corpus callosum [CC]), the largest combined percent change was a 10% increase in fractional anisotropy (FA) primarily due to increases in the BG (12.7%) and TH (9%). The largest significant percent increase in N-acetylaspartate (NAA)/creatine (Cr) ratio was seen in the brain stem (BS) (18.8%) followed by the subcortical regions in the BG (11.9%), CC (8.9%), and TH (6.0%). We found consistent, significant (p < 0.01), but weakly positive correlations (r = 0.228-0.329) between NAA/Cr ratios and mean FA in the BS, BG, and CC regions. Age- and region-specific normative MR diffusion and spectroscopic metabolite ranges show brain maturation changes and are requisite for detecting abnormalities in an injured or diseased population.

scholarly journals USE OF PROTON MAGNETIC RESONANCE SPECTROSCOPIC IMAGING DATA IN PLANNING FOCAL RADIATION THERAPIES FOR BRAIN TUMORS

2011 ◽  
Vol 21 (2) ◽  
pp. 69 ◽  
Author(s):  
Edward E Graves ◽  
Andrea Pirzkall ◽  
Tracy R Mcknight ◽  
Daniel B Vigneron ◽  
David A Larson ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Gamma Knife ◽  
Gamma Knife Radiosurgery ◽  
Spectroscopic Imaging ◽  
Target Volume ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Malignant Neoplasms ◽  
Resonance Spectroscopy ◽  
Normal Brain ◽  
Imaging Data

Advances in radiation therapy for malignant neoplasms have produced techniques such as Gamma Knife radiosurgery, capable of delivering an ablative dose to a specific, irregular volume of tissue. However, efficient use of these techniques requires the identification of a target volume that will produce the best therapeutic response while sparing surrounding normal brain tissue. Accomplishing this task using conventional computed tomography (CT) and contrast-enhanced magnetic resonance imaging (MRI) techniques has proven difficult because of the difficulties in identifying the effective tumor margin. Magnetic resonance spectroscopic imaging (MRSI) has been shown to offer a clinically-feasible metabolic assessment of the presence and extent of neoplasm that can complement conventional anatomic imaging. This paper reviews current Gamma Knife protocols and MRSI acquisition, reconstruction, and interpretation techniques, and discusses the motivation for including magnetic resonance spectroscopy findings while planning focal radiation therapies. A treatment selection and planning strategy incorporating MRSI is then proposed, which can be used in the future to assess the efficacy of spectroscopy-based therapy planning.

Proton Magnetic Resonance Spectroscopic Imaging Can Predict Length of Survival in Patients with Supratentorial Gliomas

Neurosurgery ◽  
2003 ◽  
Vol 53 (3) ◽  
pp. 565-576 ◽  
Author(s):  
Yevgeniy E. Kuznetsov ◽  
Zografos Caramanos ◽  
Samson B. Antel ◽  
Mark C. Preul ◽  
Richard Leblanc ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Proton Magnetic Resonance ◽  
Patient Survival ◽  
Characteristic Curve ◽  
Spectroscopic Imaging ◽  
Clinicopathological Features ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Supratentorial Gliomas ◽  
Leave One Out ◽  
Mrsi Data

Abstract OBJECTIVE We compared the ability of proton magnetic resonance spectroscopic imaging (1H-MRSI) measures with that of standard clinicopathological measures to predict length of survival in patients with supratentorial gliomas. METHODS We developed two sets of leave-one-out logistic regression models based on either 1) intratumoral 1H-MRSI features, including maximum values of a) choline and b) lactate-lipid, c) number of 1H-MRSI voxels with low N-acetyl group values, and d) number of 1H-MRSI voxels with high lactate-lipid values, all (a–d) of which were normalized to creatine in normal-appearing brain, or 2) standard clinicopathological features, including a) tumor histopathological grade, b) patient age, c) performance of surgical debulking, and d) tumor diagnosis (i.e., oligodendroglioma, astrocytoma). We assessed the accuracy of these two models in predicting patient survival for 6, 12, 24, and 48 months by performing receiver operating characteristic curve analysis. Cox proportional hazards analysis was performed to assess the extent to which patient survival could be explained by the above predictors. We then performed a series of leave-one-out linear multiple regression analyses to determine how well patient survival could be predicted in a continuous fashion. RESULTS The results of using the models based on 1H-MRSI and clinicopathological features were equally good, accounting for 81 and 64% of the variability (r2) in patients' actual survival durations. All features except number of 1H-MRSI voxels with lactate-lipid/creatine values of at least 1 were significant predictors of survival in the 1H-MRSI model. Two features (tumor grade and debulking) were found to be significant predictors in the clinicopathological model. Survival as a continuous variable was predicted accurately on the basis of the 1H-MRSI data (r = 0.77, P &lt; 0.001; median prediction error, 1.7 mo). CONCLUSION Our results suggest that appropriate analysis of 1H-MRSI data can predict survival in patients with supratentorial gliomas at least as accurately as data derived from more invasive clinicopathological features.

Longitudinal magnetic resonance spectroscopic imaging of primary progressive multiple sclerosis patients treated with glatiramer acetate: multicenter study

2008 ◽  
Vol 14 (1) ◽  
pp. 73-80 ◽  
Author(s):  
B.R. Sajja ◽  
P.A. Narayana ◽  
J.S. Wolinsky ◽  
C.W. Ahn ◽  
the PROMiSe Trial MRSI Group N/A
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Glatiramer Acetate ◽  
Spectroscopic Imaging ◽  
Progressive Multiple Sclerosis ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Primary Progressive Multiple Sclerosis ◽  
Primary Progressive ◽  
Significant Difference ◽  
Mrsi Data

Multicenter proton magnetic resonance spectroscopic imaging (MRSI) studies were performed on 58 primary progressive multiple sclerosis (PPMS) patients from four centers for investigating the efficacy of glatiramer acetate (GA) treatment. These patients were drawn from 943 subjects who participated in the PROMiSe trial. In these MRSI studies, patients were followed over a period of 3 years. MRSI data were acquired by all the centers using the same pulse sequence, and spectral analysis was performed at a single site using a customized analysis software package. Quantitative metabolite ratios, N-acetyl aspartate (NAA)/creatine (Cr) and choline (Cho)/Cr, were compared between GA-treated and placebo-treated PPMS patients. There was no significant difference in metabolite ratios between GA-treated and placebo-treated patients. The difference in metabolite ratios between the normal-appearing tissues (NAT) and lesion-containing regions (LCR) in GA treated patients was not significantly different from placebo treated patients. Strong lipid resonances, even in the absence of lesions, were observed on MRSI data in both gray matter and white matter in placebo- and GA-treated PPMS patients. No significant difference in number of patients with lipids between the two groups over a period of 3 years was found. Multiple Sclerosis 2008; 14: 73—80. http://msj.sagepub.com

Grey matter abnormalities in multiple sclerosis: proton magnetic resonance spectroscopic imaging

2001 ◽  
Vol 7 (4) ◽  
pp. 221-226 ◽  
Author(s):  
Rakesh Sharma ◽  
Ponnada A Narayana ◽  
Jerry S Wolinsky
Keyword(s):  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Proton Magnetic Resonance ◽  
Magnetization Transfer ◽  
Spectroscopic Imaging ◽  
Magnetic Resonance Spectroscopic Imaging ◽  
Relapsing Remitting ◽  
Cortical Gray Matter ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Characteristics

Pathologically defined abnormalities in the cortical gray matter (GM) are well described in multiple sclerosis (MS) but are infrequently seen by conventional magnetic resonance imaging (MRI). We systematically evaluated 52 relapsing - remitting MS patients and 20 normal volunteers with high resolution MRI and short echo proton magnetic resonance spectroscopic imaging (MRSI). Individual tissue contributions to the spectroscopic voxels were estimated based on MRI that incorporated both CSF suppression and magnetization transfer, or double inversion images in which both CSF and GM were suppressed. Strong resonances in the 0.8 to 1.5 p.p.m. spectral region were observed in 13 MS patients. Image segmentation based on the MRI characteristics of tissues contributing to the spectroscopic voxels showed that these additional peaks originated mainly from GM. The presence of these additional peaks suggests that the normal appearance GM on MRI, is biochemically abnormal in a substantial proportion of relapsing-remitting MS patients.

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