Literature DB >> 14625221

Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging.

Meng Law1, Stanley Yang, Hao Wang, James S Babb, Glyn Johnson, Soonmee Cha, Edmond A Knopp, David Zagzag.   

Abstract

BACKGROUND AND
PURPOSE: Sensitivity, positive predictive value (PPV), and negative predictive value (NPV) of conventional MR imaging in predicting glioma grade are not high. Relative cerebral blood volume (rCBV) measurements derived from perfusion MR imaging and metabolite ratios from proton MR spectroscopy are useful in predicting glioma grade. We evaluated the sensitivity, specificity, PPV, and NPV of perfusion MR imaging and MR spectroscopy compared with conventional MR imaging in grading primary gliomas.
METHODS: One hundred sixty patients with a primary cerebral glioma underwent conventional MR imaging, dynamic contrast-enhanced T2*-weighted perfusion MR imaging, and proton MR spectroscopy. Gliomas were graded as low or high based on conventional MR imaging findings. The rCBV measurements were obtained from regions of maximum perfusion. Metabolite ratios (choline [Cho]/creatine [Cr], Cho/N-acetylaspartate [NAA], and NAA/Cr) were measured at a TE of 144 ms. Tumor grade determined with the three methods was then compared with that from histopathologic grading. Logistic regression and receiver operating characteristic analyses were performed to determine optimum thresholds for tumor grading. Sensitivity, specificity, PPV, and NPV for identifying high-grade gliomas were also calculated.
RESULTS: Sensitivity, specificity, PPV, and NPV for determining a high-grade glioma with conventional MR imaging were 72.5%, 65.0%, 86.1%, and 44.1%, respectively. Statistical analysis demonstrated a threshold value of 1.75 for rCBV to provide sensitivity, specificity, PPV, and NPV of 95.0%, 57.5%, 87.0%, and 79.3%, respectively. Threshold values of 1.08 and 1.56 for Cho/Cr and 0.75 and 1.60 for Cho/NAA provided the minimum C2 and C1 errors, respectively, for determining a high-grade glioma. The combination of rCBV, Cho/Cr, and Cho/NAA resulted in sensitivity, specificity, PPV, and NPV of 93.3%, 60.0%, 87.5%, and 75.0%, respectively. Significant differences were noted in the rCBV and Cho/Cr, Cho/NAA, and NAA/Cr ratios between low- and high-grade gliomas (P <.0001,.0121,.001, and.0038, respectively).
CONCLUSION: The rCBV measurements and metabolite ratios both individually and in combination can increase the sensitivity and PPV when compared with conventional MR imaging alone in determining glioma grade. The rCBV measurements had the most superior diagnostic performance (either with or without metabolite ratios) in predicting glioma grade. Threshold values can be used in a clinical setting to evaluate tumors preoperatively for histologic grade and provide a means for guiding treatment and predicting postoperative patient outcome.

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Year:  2003        PMID: 14625221      PMCID: PMC8148904     

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  76 in total

Review 1.  MR perfusion imaging of the brain: techniques and applications.

Authors:  J R Petrella; J M Provenzale
Journal:  AJR Am J Roentgenol       Date:  2000-07       Impact factor: 3.959

Review 2.  Clinical applications of intracranial perfusion MR imaging.

Authors:  M H Lev; B R Rosen
Journal:  Neuroimaging Clin N Am       Date:  1999-05       Impact factor: 2.264

Review 3.  Malignant astrocytic neoplasms: classification, pathologic anatomy, and response to treatment.

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4.  An automated technique for the quantitative assessment of 3D-MRSI data from patients with glioma.

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Review 5.  Value of dynamic susceptibility contrast magnetic resonance imaging in the evaluation of intracranial tumors.

Authors:  T Sugahara; Y Korogi; Y Shigematsu; L Liang; K Yoshizumi; M Kitajima; M Takahashi
Journal:  Top Magn Reson Imaging       Date:  1999-04

6.  Volume MRI and MRSI techniques for the quantitation of treatment response in brain tumors: presentation of a detailed case study.

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7.  The effect of Gd-DTPA on T(1)-weighted choline signal in human brain tumours.

Authors:  Philip S Murphy; Andrzej S K Dzik-Jurasz; Martin O Leach; Ian J Rowland
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8.  Quantification of cerebral metabolites in glioma patients with proton MR spectroscopy using T2 relaxation time correction.

Authors:  Tomonori Isobe; Akira Matsumura; Izumi Anno; Takashi Yoshizawa; Yasushi Nagatomo; Yuji Itai; Tadao Nose
Journal:  Magn Reson Imaging       Date:  2002-05       Impact factor: 2.546

9.  Characterization of intracranial mass lesions with in vivo proton MR spectroscopy.

Authors:  H Poptani; R K Gupta; R Roy; R Pandey; V K Jain; D K Chhabra
Journal:  AJNR Am J Neuroradiol       Date:  1995-09       Impact factor: 3.825

10.  Mapping of brain tumor metabolites with proton MR spectroscopic imaging: clinical relevance.

Authors:  M J Fulham; A Bizzi; M J Dietz; H H Shih; R Raman; G S Sobering; J A Frank; A J Dwyer; J R Alger; G Di Chiro
Journal:  Radiology       Date:  1992-12       Impact factor: 11.105

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  378 in total

1.  Stripe-like increase of rCBV beyond the visible border of glioblastomas: site of tumor infiltration growing after neurosurgery.

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Journal:  J Neurooncol       Date:  2010-10-07       Impact factor: 4.130

2.  New similarity search based glioma grading.

Authors:  Katrin Haegler; Martin Wiesmann; Christian Böhm; Jessica Freiherr; Oliver Schnell; Hartmut Brückmann; Jörg-Christian Tonn; Jennifer Linn
Journal:  Neuroradiology       Date:  2011-12-14       Impact factor: 2.804

3.  Proton MR spectroscopy in a 1T open MR imaging system.

Authors:  C G Filippi; T Pace; T G Perkins; J B Murdoch; T Andrews
Journal:  AJNR Am J Neuroradiol       Date:  2010-12-16       Impact factor: 3.825

4.  MR imaging characteristics of protoplasmic astrocytomas.

Authors:  Kevin L Tay; Alpha Tsui; Pramit M Phal; Katharine J Drummond; Brian M Tress
Journal:  Neuroradiology       Date:  2010-07-20       Impact factor: 2.804

Review 5.  Multimodality Brain Tumor Imaging: MR Imaging, PET, and PET/MR Imaging.

Authors:  James R Fink; Mark Muzi; Melinda Peck; Kenneth A Krohn
Journal:  J Nucl Med       Date:  2015-08-20       Impact factor: 10.057

6.  Survival analysis in patients with newly diagnosed primary glioblastoma multiforme using pre- and post-treatment peritumoral perfusion imaging parameters.

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Journal:  J Neurooncol       Date:  2014-08-07       Impact factor: 4.130

7.  Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas.

Authors:  Sanjeev Chawla; Seung-Cheol Lee; Suyash Mohan; Sumei Wang; MacLean Nasrallah; Arastoo Vossough; Jaroslaw Krejza; Elias R Melhem; S Ali Nabavizadeh
Journal:  Neuroradiol J       Date:  2019-05-03

8.  Evaluation of pseudoprogression in patients with glioblastoma multiforme using dynamic magnetic resonance imaging with ferumoxytol calls RANO criteria into question.

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Journal:  Neuro Oncol       Date:  2014-02-11       Impact factor: 12.300

9.  High- and low-grade glioma differentiation: the role of percentage signal recovery evaluation in MR dynamic susceptibility contrast imaging.

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Journal:  Radiol Med       Date:  2015-03-12       Impact factor: 3.469

Review 10.  Current and potential imaging applications of ferumoxytol for magnetic resonance imaging.

Authors:  Gerda B Toth; Csanad G Varallyay; Andrea Horvath; Mustafa R Bashir; Peter L Choyke; Heike E Daldrup-Link; Edit Dosa; John Paul Finn; Seymur Gahramanov; Mukesh Harisinghani; Iain Macdougall; Alexander Neuwelt; Shreyas S Vasanawala; Prakash Ambady; Ramon Barajas; Justin S Cetas; Jeremy Ciporen; Thomas J DeLoughery; Nancy D Doolittle; Rongwei Fu; John Grinstead; Alexander R Guimaraes; Bronwyn E Hamilton; Xin Li; Heather L McConnell; Leslie L Muldoon; Gary Nesbit; Joao P Netto; David Petterson; William D Rooney; Daniel Schwartz; Laszlo Szidonya; Edward A Neuwelt
Journal:  Kidney Int       Date:  2017-04-20       Impact factor: 10.612

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