Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • AJNR Case Collection
    • Case of the Week Archive
    • Classic Case Archive
    • Case of the Month Archive
  • Special Collections
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
    • 2024 AJNR Journal Awards
    • Most Impactful AJNR Articles
  • Multimedia
    • AJNR Podcast
    • AJNR Scantastics
    • Video Articles
  • For Authors
    • Submit a Manuscript
    • Author Policies
    • Fast publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Manuscript Submission Guidelines
    • Imaging Protocol Submission
    • Submit a Case for the Case Collection
  • About Us
    • About AJNR
    • Editorial Board
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Other Publications
    • ajnr

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • AJNR Case Collection
    • Case of the Week Archive
    • Classic Case Archive
    • Case of the Month Archive
  • Special Collections
    • Spinal CSF Leak Articles (Jan 2020-June 2024)
    • 2024 AJNR Journal Awards
    • Most Impactful AJNR Articles
  • Multimedia
    • AJNR Podcast
    • AJNR Scantastics
    • Video Articles
  • For Authors
    • Submit a Manuscript
    • Author Policies
    • Fast publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Manuscript Submission Guidelines
    • Imaging Protocol Submission
    • Submit a Case for the Case Collection
  • About Us
    • About AJNR
    • Editorial Board
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

Welcome to the new AJNR, Updated Hall of Fame, and more. Read the full announcements.


AJNR is seeking candidates for the position of Associate Section Editor, AJNR Case Collection. Read the full announcement.

 

Research ArticleBrain
Open Access

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

H. Fudaba, T. Shimomura, T. Abe, H. Matsuta, Y. Momii, K. Sugita, H. Ooba, T. Kamida, T. Hikawa and M. Fujiki
American Journal of Neuroradiology November 2014, 35 (11) 2091-2098; DOI: https://doi.org/10.3174/ajnr.A4018
H. Fudaba
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
T. Shimomura
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
T. Abe
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
H. Matsuta
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Y. Momii
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
K. Sugita
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
H. Ooba
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
T. Kamida
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
T. Hikawa
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M. Fujiki
aFrom the Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Fig 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 1.

    A 62-year-old man with a grade II oligoastrocytoma. The contrast-enhanced T1-weighted image shows a nonenhancing mass in the right hippocampus (A). The lesions presented high-intensity signals on FLAIR images (B). The rCBF map on PASL shows no areas of hyperperfusion (C). The FA map shows low FA values (D). The ADC map shows increased tumor diffusion values (E). The tumor MR spectrum shows decreased NAA and slightly increased Cho and Lac (F). The Ki-67 labeling index is 5.0% (original magnification × 400) (G).

  • Fig 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Fig 2.

    A 60-year-old woman with a grade IV glioblastoma. The lesion on the left frontotemporal lobe exhibits strong enhancement on gadolinium T1-weighted image (A). The neoplasm is clearly hyperperfused compared with the healthy parenchyma on the PASL image (B). The FA map shows slightly low FA values (C). The ADC map shows heterogeneous tumor diffusion values (D). The tumor MR spectrum shows decreased NAA with a marked increase in Cho and Lac (E). The Ki-67 labeling index is 27.0% (original magnification × 400) (F).

Tables

  • Figures
    • View popup
    Table 1:

    Threshold values for multiple parameters for differentiating high- and low-grade gliomas

    ParametersBased on Minimum C1 ErrorErrorsBased on Minimum C2 ErrorErrors
    ThresholdSensitivitySpecificityPPVNPVC1C2ThresholdSensitivitySpecificityPPVNPVC1C2
    rCBF ratio mean2.5620.6520.7780.8820.4670.2850.1702.5620.6520.7780.8820.4670.2850.170
    rCBF ratio max2.8450.6090.7780.8750.4380.3070.2022.8450.6090.7780.8750.4380.3070.202
    rCBF ratio min2.0170.7390.6670.8500.5000.2970.1792.0170.7390.6670.8500.5000.2970.179
    rCBF ratio meana1.8000.8240.6670.9330.4010.2550.1421.8000.8240.6670.9330.4010.2550.142
    rCBF ratio maxa2.2580.7650.6670.9290.3340.2840.1662.2580.7650.6670.9290.3340.2840.166
    rCBF ratio mina1.2540.8820.6670.9380.4990.2260.1251.2540.8820.6670.9380.4990.2260.125
    FA ratio mean0.2360.8700.5560.8340.6260.2870.2140.2670.7390.6670.8500.5000.2970.179
    FA ratio max0.2880.8700.6670.8700.6680.2320.1280.2880.8700.6670.8700.6680.2320.128
    FA ratio min0.2790.5650.6670.8130.3750.3840.3000.2790.5650.6670.8130.3750.3840.300
    ADC ratio mean1.6590.9130.6670.8750.7500.2100.1181.6590.9130.6670.8750.7500.2100.118
    ADC ratio max1.5380.8260.5560.8260.5560.3090.2271.5380.8260.5560.8260.5560.3090.227
    ADC ratio min1.5640.9130.6670.8750.7500.2100.1181.5640.9130.6670.8750.7500.2100.118
    Cho/Cr1.7890.9130.7780.9130.7780.1550.0571.7890.9130.7780.9130.7780.1550.057
    NAA/Cho0.3490.6960.7780.8890.5000.2630.1420.3490.6960.7780.8890.5000.2630.142
    NAA/Cr1.2890.3041.0001.0000.3600.3480.4840.8940.4780.7780.8460.3680.3720.322
    Lac/Cr1.7890.7391.0001.0000.6000.1310.0681.7890.7391.0001.0000.6000.1310.068
    • Note:—min indicates minimum; max, maximum.

    • ↵a rCBF ratios derived from purely astrocytomas.

    • View popup
    Table 2:

    Threshold values for multiple parameters for differentiating glioblastomas and other-grade gliomas

    ParametersBased on Minimum C1 ErrorErrorsBased on Minimum C2 ErrorErrors
    ThresholdSensitivitySpecificityPPVNPVC1C2ThresholdSensitivitySpecificityPPVNPVC1C2
    rCBF ratio mean2.5620.8670.7650.7650.8670.1840.0732.5620.8670.7650.7650.8670.1840.073
    rCBF ratio max2.8450.8670.8240.8130.8750.1550.0492.8450.8670.8240.8130.8750.1550.049
    rCBF ratio min2.0170.8670.5880.6500.8340.2730.1872.1640.8000.6470.6670.7860.2770.165
    rCBF ratio meana1.8570.9290.8330.9280.8340.1190.0331.8570.9290.8330.9280.8340.1190.033
    rCBF ratio maxa2.2580.9290.8330.9280.8340.1190.0332.2580.9290.8330.9280.8340.1190.033
    rCBF ratio mina2.1640.7860.8330.9170.6250.1910.0742.1640.7860.8330.9170.6250.1910.074
    FA ratio mean0.3800.7330.7650.7330.7650.2510.1270.3800.7330.7650.7330.7650.2510.127
    FA ratio max0.3710.8000.5880.6310.7690.3060.2100.4180.6670.7060.6670.7060.3140.197
    FA ratio min0.3330.6000.6470.6000.6470.3770.2850.3330.6000.6470.6000.6470.3770.285
    ADC ratio mean1.3050.8000.7650.7500.8130.2180.0951.3050.8000.7650.7500.8130.2180.095
    ADC ratio max1.4940.9330.5290.6360.8990.2690.2261.4940.9330.5290.6360.8990.2690.226
    ADC ratio min1.4490.9330.6470.7000.9160.2100.1291.1480.7330.8240.7860.7780.2220.102
    Cho/Cr1.7890.9330.4710.6090.8880.2980.2842.8130.7330.6470.6470.7330.3100.196
    NAA/Cho0.3380.7330.6470.6470.7330.3100.1960.3380.7330.6470.6470.7330.3100.196
    NAA/Cr1.9220.2001.0001.0000.5860.4000.6400.7250.6000.4120.4740.5390.4940.506
    Lac/Cr2.7780.6670.8820.8330.7500.2260.1252.7780.6670.8820.8330.7500.2260.125
    • ↵a rCBF ratio derived from purely astrocytomas.

    • View popup
    Table 3:

    Combination of the minimum ADC ratio and Cho/Cr for differentiating high- and low-grade gliomas

    Based on Minimum C1 ErrorErrorsBased on Minimum C2 ErrorErrors
    SensitivitySpecificityPPVNPVC1C2SensitivitySpecificityPPVNPVC1C2
    0.8700.8890.9520.7270.1210.0290.8700.8890.9520.7270.1210.029
    • View popup
    Table 4:

    Combination of the maximum rCBF ratio and mean ADC ratio for differentiating glioblastomas and other-grade gliomas

    Based on Minimum C1 ErrorErrorsBased on Minimum C2 ErrorErrors
    SensitivitySpecificityPPVNPVC1C2SensitivitySpecificityPPVNPVC1C2
    0.7330.9410.9170.8000.1630.0750.7330.9410.9170.8000.1630.075
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 35 (11)
American Journal of Neuroradiology
Vol. 35, Issue 11
1 Nov 2014
  • Table of Contents
  • Index by author
  • Complete Issue (PDF)
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
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
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
H. Fudaba, T. Shimomura, T. Abe, H. Matsuta, Y. Momii, K. Sugita, H. Ooba, T. Kamida, T. Hikawa, M. Fujiki
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
American Journal of Neuroradiology Nov 2014, 35 (11) 2091-2098; DOI: 10.3174/ajnr.A4018

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
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
H. Fudaba, T. Shimomura, T. Abe, H. Matsuta, Y. Momii, K. Sugita, H. Ooba, T. Kamida, T. Hikawa, M. Fujiki
American Journal of Neuroradiology Nov 2014, 35 (11) 2091-2098; DOI: 10.3174/ajnr.A4018
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • Materials and Methods
    • Results
    • Discussion
    • Conclusions
    • Footnotes
    • References
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • Application of 7T MRS to High-Grade Gliomas
  • Addition of Amide Proton Transfer Imaging to FDG-PET/CT Improves Diagnostic Accuracy in Glioma Grading: A Preliminary Study Using the Continuous Net Reclassification Analysis
  • 3D Pseudocontinuous Arterial Spin-Labeling MR Imaging in the Preoperative Evaluation of Gliomas
  • Improving the Grading Accuracy of Astrocytic Neoplasms Noninvasively by Combining Timing Information with Cerebral Blood Flow: A Multi-TI Arterial Spin-Labeling MR Imaging Study
  • Crossref (77)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • Current Clinical Brain Tumor Imaging
    Javier E. Villanueva-Meyer, Marc C. Mabray, Soonmee Cha
    Neurosurgery 2017 81 3
  • Pseudoprogression of brain tumors
    Stefanie C. Thust, Martin J. van den Bent, Marion Smits
    Journal of Magnetic Resonance Imaging 2018 48 3
  • Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice
    S. C. Thust, S. Heiland, A. Falini, H. R. Jäger, A. D. Waldman, P. C. Sundgren, C. Godi, V. K. Katsaros, A. Ramos, N. Bargallo, M. W. Vernooij, T. Yousry, M. Bendszus, M. Smits
    European Radiology 2018 28 8
  • Assessment of diffusion tensor imaging metrics in differentiating low-grade from high-grade gliomas
    Lamiaa El-Serougy, Ahmed Abdel Khalek Abdel Razek, Amani Ezzat, Hany Eldawoody, Ahmad El-Morsy
    The Neuroradiology Journal 2016 29 5
  • Clinical Applications of Arterial Spin Labeling in Brain Tumors
    Ahmed Abdel Khalek Abdel Razek, Mona Talaat, Lamiaa El-Serougy, Gada Gaballa, Mohamed Abdelsalam
    Journal of Computer Assisted Tomography 2019 43 4
  • The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: A systematic review and meta-analysis
    Qun Wang, Hui Zhang, JiaShu Zhang, Chen Wu, WeiJie Zhu, FangYe Li, XiaoLei Chen, BaiNan Xu
    European Radiology 2016 26 8
  • Combination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours
    Ji Xiong, Wenli Tan, Jianbo Wen, Jiawei Pan, Yin Wang, Jun Zhang, Daoying Geng
    European Radiology 2016 26 6
  • Apparent diffusion coefficient for molecular subtyping of non-gadolinium-enhancing WHO grade II/III glioma: volumetric segmentation versus two-dimensional region of interest analysis
    S. C. Thust, S. Hassanein, S. Bisdas, J. H. Rees, H. Hyare, J. A. Maynard, S. Brandner, C. Tur, H. R. Jäger, T. A. Yousry, L. Mancini
    European Radiology 2018 28 9
  • Brain Tumor Imaging
    Kevin M. Brindle, José L. Izquierdo-García, David Y. Lewis, Richard J. Mair, Alan J. Wright
    Journal of Clinical Oncology 2017 35 21
  • Bench to bedside molecular functional imaging in translational cancer medicine: to image or to imagine?
    A. Mahajan, V. Goh, S. Basu, R. Vaish, A.J. Weeks, M.H. Thakur, G.J. Cook
    Clinical Radiology 2015 70 10

More in this TOC Section

  • Usefulness of Quantitative Susceptibility Mapping for the Diagnosis of Parkinson Disease
  • Evaluating the Effects of White Matter Multiple Sclerosis Lesions on the Volume Estimation of 6 Brain Tissue Segmentation Methods
  • White Matter Alterations in the Brains of Patients with Active, Remitted, and Cured Cushing Syndrome: A DTI Study
Show more Brain

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editors Choice
  • Fellow Journal Club
  • Letters to the Editor

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

Special Collections

  • Special Collections

Resources

  • News and Updates
  • Turn around Times
  • Submit a Manuscript
  • Author Policies
  • Manuscript Submission Guidelines
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Submit a Case
  • Become a Reviewer/Academy of Reviewers
  • Get Peer Review Credit from Publons

Multimedia

  • AJNR Podcast
  • AJNR SCANtastic
  • Video Articles

About Us

  • About AJNR
  • Editorial Board
  • Not an AJNR Subscriber? Join Now
  • Alerts
  • Feedback
  • Advertise with us
  • Librarian Resources
  • Permissions
  • Terms and Conditions

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire