Literature DB >> 19229590

Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging.

H R Arvinda1, C Kesavadas, P S Sarma, B Thomas, V V Radhakrishnan, A K Gupta, T R Kapilamoorthy, S Nair.   

Abstract

PURPOSE: The purpose of our study was to determine the statistical significance of thresholds of relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and ADC ratios in grading cerebral gliomas.
MATERIALS AND METHODS: In this retrospective study, 51 patients with histopathologically confirmed primary cerebral gliomas who had undergone conventional MR imaging, dynamic contrast-enhanced T2*-weighted perfusion MR imaging and diffusion MR imaging were included. A retrospective blinded analysis of the imaging findings including the perfusion and diffusion parameters was done. The rCBV measurements were obtained from regions of maximum perfusion. Minimum ADC values were obtained from the region of maximum hypointensity within the tumor and from the corresponding opposite white matter. Tumor grade determined with the two methods were then compared with the histopathologic grade. Mann-Whitney tests were performed to compare the DWI and PWI between tumor types. Receiver operating characteristic analyses were performed to determine optimum thresholds for tumor grading and also to calculate the sensitivity, specificity, PPV, and NPV for identifying high-grade gliomas.
RESULTS: Statistical analysis demonstrated a threshold value of 2.91 for rCBV to provide sensitivity, specificity, PPV, and NPV of 94.7, 93.75, 90.0, and 96.8%, respectively, in determining high-grade gliomas. An ADC value of 98.50 mm(2)/s was defined as a threshold below which tumors were classified as high-grade gliomas and a sensitivity, specificity, PPV, and NPV of 90, 87.1, 81.81 and 93.10% respectively, were obtained. Significant differences were noted in the rCBV ratios, ADC and ADC ratios between low- and high-grade gliomas (P < 0.0001).
CONCLUSION: Combining PWI and DWI with conventional MR imaging increases the accuracy of pre-operative imaging grading of glial neoplasms. The rCBV measurements had the most superior diagnostic performance in predicting glioma grade. Absolute ADC values or ADC ratios were also helpful in preoperative grading of gliomas. 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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Mesh:

Year:  2009        PMID: 19229590     DOI: 10.1007/s11060-009-9807-6

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  56 in total

1.  Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; Y Shigematu; T Hirai; T Okuda; L Liang; Y Ge; Y Komohara; Y Ushio; M Takahashi
Journal:  J Magn Reson Imaging       Date:  1999-01       Impact factor: 4.813

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

3.  Perfusion, diffusion and spectroscopy values in newly diagnosed cerebral gliomas.

Authors:  Isabelle Catalaa; Roland Henry; William P Dillon; Edward E Graves; Tracy R McKnight; Ying Lu; Daniel B Vigneron; Sarah J Nelson
Journal:  NMR Biomed       Date:  2006-06       Impact factor: 4.044

4.  Combination of single-voxel proton MR spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumors.

Authors:  Nail Bulakbasi; Murat Kocaoglu; Fatih Ors; Cem Tayfun; Taner Uçöz
Journal:  AJNR Am J Neuroradiol       Date:  2003-02       Impact factor: 3.825

5.  Glial tumor grading and outcome prediction using dynamic spin-echo MR susceptibility mapping compared with conventional contrast-enhanced MR: confounding effect of elevated rCBV of oligodendrogliomas [corrected].

Authors:  Michael H Lev; Yelda Ozsunar; John W Henson; Amjad A Rasheed; Glenn D Barest; Griffith R Harsh; Markus M Fitzek; E Antonio Chiocca; James D Rabinov; Andrew N Csavoy; Bruce R Rosen; Fred H Hochberg; Pamela W Schaefer; R Gilberto Gonzalez
Journal:  AJNR Am J Neuroradiol       Date:  2004-02       Impact factor: 3.825

6.  Clinical NMR imaging of the brain: 140 cases.

Authors:  G M Bydder; R E Steiner; I R Young; A S Hall; D J Thomas; J Marshall; C A Pallis; N J Legg
Journal:  AJR Am J Roentgenol       Date:  1982-08       Impact factor: 3.959

7.  Grading of astrocytomas. A simple and reproducible method.

Authors:  C Daumas-Duport; B Scheithauer; J O'Fallon; P Kelly
Journal:  Cancer       Date:  1988-11-15       Impact factor: 6.860

8.  Diffusion-weighted MR imaging of experimental brain tumors in rats.

Authors:  T Els; M Eis; M Hoehn-Berlage; K A Hossmann
Journal:  MAGMA       Date:  1995-03       Impact factor: 2.310

9.  Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results.

Authors:  Ji Hoon Shin; Ho Kyu Lee; Byung Duk Kwun; Jin-Suh Kim; Weechang Kang; Choong Gon Choi; Dae Chul Suh
Journal:  AJR Am J Roentgenol       Date:  2002-09       Impact factor: 3.959

10.  MR classification of brain gliomas: value of magnetization transfer and conventional imaging.

Authors:  T Kurki; N Lundbom; H Kalimo; S Valtonen
Journal:  Magn Reson Imaging       Date:  1995       Impact factor: 2.546

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  54 in total

Review 1.  Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy.

Authors:  Anwar R Padhani; Aftab Alam Khan
Journal:  Target Oncol       Date:  2010-04-11       Impact factor: 4.493

2.  Dynamic contrast enhanced T1 MRI perfusion differentiates pseudoprogression from recurrent glioblastoma.

Authors:  Alissa A Thomas; Julio Arevalo-Perez; Thomas Kaley; John Lyo; Kyung K Peck; Weiji Shi; Zhigang Zhang; Robert J Young
Journal:  J Neurooncol       Date:  2015-08-15       Impact factor: 4.130

3.  ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain.

Authors:  K Welker; J Boxerman; A Kalnin; T Kaufmann; M Shiroishi; M Wintermark
Journal:  AJNR Am J Neuroradiol       Date:  2015-04-23       Impact factor: 3.825

4.  Apparent diffusion coefficient obtained by magnetic resonance imaging as a prognostic marker in glioblastomas: correlation with MGMT promoter methylation status.

Authors:  Andrea Romano; L F Calabria; F Tavanti; G Minniti; M C Rossi-Espagnet; V Coppola; S Pugliese; D Guida; G Francione; C Colonnese; L M Fantozzi; A Bozzao
Journal:  Eur Radiol       Date:  2012-08-10       Impact factor: 5.315

5.  Grading of supratentorial astrocytic tumors by using the difference of ADC value.

Authors:  Xu Bai; Yunting Zhang; Ying Liu; Tong Han; Li Liu
Journal:  Neuroradiology       Date:  2011-02-19       Impact factor: 2.804

6.  Characterization and therapy monitoring of head and neck carcinomas using diffusion-imaging-based intravoxel incoherent motion parameters-preliminary results.

Authors:  Thomas Hauser; Marco Essig; Alexandra Jensen; Lars Gerigk; Frederik Bernd Laun; Marc Münter; Dirk Simon; Bram Stieltjes
Journal:  Neuroradiology       Date:  2013-02-17       Impact factor: 2.804

7.  Imaging characteristics of oligodendrogliomas that predict grade.

Authors:  L Khalid; M Carone; N Dumrongpisutikul; J Intrapiromkul; D Bonekamp; P B Barker; D M Yousem
Journal:  AJNR Am J Neuroradiol       Date:  2012-01-19       Impact factor: 3.825

8.  Multimodal MR imaging model to predict tumor infiltration in patients with gliomas.

Authors:  Christopher R Durst; Prashant Raghavan; Mark E Shaffrey; David Schiff; M Beatriz Lopes; Jason P Sheehan; Nicholas J Tustison; James T Patrie; Wenjun Xin; W Jeff Elias; Kenneth C Liu; Greg A Helm; A Cupino; Max Wintermark
Journal:  Neuroradiology       Date:  2013-12-15       Impact factor: 2.804

9.  Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival.

Authors:  Valeria Cuccarini; A Erbetta; M Farinotti; L Cuppini; F Ghielmetti; B Pollo; F Di Meco; M Grisoli; G Filippini; G Finocchiaro; M G Bruzzone; M Eoli
Journal:  J Neurooncol       Date:  2016-01       Impact factor: 4.130

10.  Perfusion magnetic resonance imaging in pediatric brain tumors.

Authors:  F Dallery; R Bouzerar; D Michel; C Attencourt; V Promelle; J Peltier; J M Constans; O Balédent; C Gondry-Jouet
Journal:  Neuroradiology       Date:  2017-08-31       Impact factor: 2.804

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