Differences in metabolism of fiber tract alterations in gliomas: a combined fiber density mapping and magnetic resonance spectroscopic imaging study.

BACKGROUND Gliomas propagate diffusely throughout and along white matter structures. Glioma-related changes in structural integrity and metabolism are not detectable by standard magnetic resonance (MR) imaging. OBJECTIVE To investigate differences in the metabolism of fiber tract alterations between gliomas grade II to IV by correlation of fiber density values with metabolite concentrations measured by fiber density mapping and MR spectroscopic imaging. METHODS Fiber density mapping and MR spectroscopic imaging were performed in 48 patients with gliomas WHO grade II to IV. Fiber density mapping data were used to define fiber tracts in tumoral and peritumoral areas. Structural integrity of fiber tracts was assessed as fiber density ipsilateral-to-contralateral ratio (FD ICR). Metabolite concentrations for choline-containing compounds and N-acetyl-aspartate were computed and correlated to FD ICR values after coregistration with anatomic MR imaging. RESULTS In tumoral areas, choline-containing compound concentrations of altered fiber tracts were significantly different between low- and high-grade glioma and showed different courses for the correlations of FD ICR and choline-containing czeompounds. In high-grade glioma, increasing fiber destruction was associated with a massive progression in cell membrane proliferation. Peritumoral fiber structures showed significantly decreased N-acetyl-aspartate concentrations for all patients, but only patients with glioblastoma multiforme had significantly decreased fiber density compared with the contralateral side. Glioma grades II and III had significantly higher peritumoral FD ICR than glioblastoma multiforme. CONCLUSION A multiparametric MR imaging strategy providing information about both structural integrity and metabolism of the tumor is required for detailed assessment of glioma-related fiber tract alterations, which in turn is essential for treatment planning.

[1]  Chris A Clark,et al.  White matter fiber tracking in patients with space-occupying lesions of the brain: a new technique for neurosurgical planning? , 2003, NeuroImage.

[2]  Hangyi Jiang,et al.  DtiStudio: Resource program for diffusion tensor computation and fiber bundle tracking , 2006, Comput. Methods Programs Biomed..

[3]  The need for spatially standardized methods in clinical applications of diffusion tensor imaging of white matter. , 2009, Radiology.

[4]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[5]  K. Hasan.  Diffusion tensor eigenvalues or both mean diffusivity and fractional anisotropy are required in quantitative clinical diffusion tensor MR reports: fractional anisotropy alone is not sufficient. , 2006, Radiology.

[6]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[7]  K. Zou,et al.  Correlation and simple linear regression. , 2003, Radiology.

[8]  G. Kemp,et al.  Non-Invasive Methods for Studying Brain Energy Metabolism: What They Show and What It Means , 2000, Developmental Neuroscience.

[9]  Christopher Nimsky,et al.  Preoperative grading of gliomas by using metabolite quantification with high-spatial-resolution proton MR spectroscopic imaging. , 2006, Radiology.

[10]  M. Tovi,et al.  MR imaging in cerebral gliomas analysis of tumour tissue components. , 1993, Acta radiologica. Supplementum.

[11]  Derek K. Jones,et al.  The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: A Monte Carlo study † , 2004, Magnetic resonance in medicine.

[12]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[13]  T R Brown,et al.  Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study. , 1996, Journal of neurosurgery.

[14]  C. Nimsky,et al.  Proton Magnetic Resonance Spectroscopic Imaging in the Border Zone of Gliomas: Correlation of Metabolic and Histological Changes at Low Tumor Infiltration—Initial Results , 2007, Investigative radiology.

[15]  Jens Frahm,et al.  Regional Age Dependence of Human Brain Metabolites from Infancy to Adulthood as Detected by Quantitative Localized Proton MRS , 1999, Pediatric Research.

[16]  Glyn Johnson,et al.  Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. , 2004, Radiology.

[17]  S. Provencher.  Estimation of metabolite concentrations from localized in vivo proton NMR spectra , 1993, Magnetic resonance in medicine.

[18]  C. Poupon,et al.  Regularization of Diffusion-Based Direction Maps for the Tracking of Brain White Matter Fascicles , 2000, NeuroImage.

[19]  S F Keevil,et al.  Absolute metabolite quantification by in vivo NMR spectroscopy: II. A multicentre trial of protocols for in vivo localised proton studies of human brain. , 1998, Magnetic resonance imaging.

[20]  G Helms,et al.  A precise and user‐independent quantification technique for regional comparison of single volume proton MR spectroscopy of the human brain , 2000, NMR in biomedicine.

[21]  P. Barker,et al.  Diffusion magnetic resonance imaging: Its principle and applications , 1999, The Anatomical record.

[22]  Jens Fiehler,et al.  Low-grade and anaplastic gliomas: differences in architecture evaluated with diffusion-tensor MR imaging. , 2006, Radiology.

[23]  G J Barker,et al.  Quantitative analysis of short echo time 1H‐MRSI of cerebral gray and white matter , 2000, Magnetic resonance in medicine.

[24]  Oliver Ganslandt,et al.  Fiber density mapping of gliomas: histopathologic evaluation of a diffusion-tensor imaging data processing method. , 2010, Radiology.

[25]  Christopher Nimsky,et al.  Integration of biochemical images of a tumor into frameless stereotaxy achieved using a magnetic resonance imaging/magnetic resonance spectroscopy hybrid data set. , 2004, Journal of neurosurgery.

[26]  D. Gadian,et al.  Proton nuclear magnetic resonance spectroscopy unambiguously identifies different neural cell types , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[27]  Carles Arús,et al.  Adult primitive neuroectodermal tumor: proton MR spectroscopic findings with possible application for differential diagnosis. , 2002, Radiology.

[28]  Derek K. Jones,et al.  Diffusion‐tensor MRI: theory, experimental design and data analysis – a technical review , 2002 .

[29]  H. Lanfermann,et al.  DIAGNOSTIC VALUE OF PROTON MAGNETIC RESONANCE SPECTROSCOPY IN THE NONINVASIVE GRADING OF SOLID GLIOMAS: COMPARISON OF MAXIMUM AND MEAN CHOLINE VALUES , 2009, Neurosurgery.

[30]  V D Calhoun,et al.  Rapid method for correction of CSF partial volume in quantitative proton MR spectroscopic imaging , 2002, Magnetic resonance in medicine.

[31]  J Fiehler,et al.  Disarrangement of fiber tracts and decline of neuronal density correlate in glioma patients--a combined diffusion tensor imaging and 1H-MR spectroscopy study. , 2006, AJNR. American journal of neuroradiology.

[32]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[33]  B W Kreher,et al.  Multitensor approach for analysis and tracking of complex fiber configurations , 2005, Magnetic resonance in medicine.

[34]  Christopher Nimsky,et al.  Metabolic Imaging of Cerebral Gliomas: Spatial Correlation of Changes in O-(2-18F-Fluoroethyl)-l-Tyrosine PET and Proton Magnetic Resonance Spectroscopic Imaging , 2008, Journal of Nuclear Medicine.

[35]  Khader M Hasan,et al.  Diffusion tensor eigenvector directional color imaging patterns in the evaluation of cerebral white matter tracts altered by tumor , 2004, Journal of magnetic resonance imaging : JMRI.

[36]  Christopher Nimsky,et al.  Gliomas: histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor MR imaging. , 2006, Radiology.

[37]  Christopher Nimsky,et al.  Classification of Peritumoral Fiber Tract Alterations in Gliomas Using Metabolic and Structural Neuroimaging , 2011, The Journal of Nuclear Medicine.

[38]  Ewald Moser,et al.  Improved delineation of brain tumors: an automated method for segmentation based on pathologic changes of 1H-MRSI metabolites in gliomas , 2004, NeuroImage.

[39]  B J Soher,et al.  Quantitation of automated single‐voxel proton MRS using cerebral water as an internal reference , 1996, Magnetic resonance in medicine.

[40]  A. Kassner,et al.  Fiber density index correlates with reduced fractional anisotropy in white matter of patients with glioblastoma. , 2005, AJNR. American journal of neuroradiology.

[41]  Talma Hendler,et al.  Characterization of displaced white matter by brain tumors using combined DTI and fMRI , 2006, NeuroImage.

[42]  A. Alexander,et al.  Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. , 2004, AJNR. American journal of neuroradiology.

[43]  Maosheng Xu,et al.  Comparison of Magnetic Resonance Spectroscopy and Perfusion-weighted Imaging in Presurgical Grading of Oligodendroglial Tumors , 2005, Neurosurgery.

[44]  M. Kraut,et al.  Comparison of weakness progression in inclusion body myositis during treatment with methotrexate or placebo , 2002, Annals of neurology.

[45]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[46]  Rainer Schrader,et al.  Fast and robust registration of PET and MR images of human brain , 2004, NeuroImage.

[47]  J. Frahm,et al.  Absolute concentrations of metabolites in the adult human brain in vivo: quantification of localized proton MR spectra. , 1993, Radiology.