Literature DB >> 28522666

Discrimination between Glioma Grades II and III Using Dynamic Susceptibility Perfusion MRI: A Meta-Analysis.

Anna F Delgado1, Alberto F Delgado2.   

Abstract

BACKGROUND: DSC perfusion has been evaluated in the discrimination between low-grade and high-grade glioma but the diagnostic potential to discriminate beween glioma grades II and III remains unclear.
PURPOSE: Our aim was to evaluate the diagnostic accuracy of relative maximal CBV from DSC perfusion MR imaging to discriminate glioma grades II and III. DATA SOURCES: A systematic literature search was performed in PubMed/MEDLINE, Embase, Web of Science, and ClinicalTrials.gov. STUDY SELECTION: Eligible studies reported on patients evaluated with relative maximal CBV derived from DSC with a confirmed neuropathologic diagnosis of glioma World Health Organization grades II and III. Studies reporting on mean or individual patient data were considered for inclusion. DATA ANALYSIS: Data were analyzed by using inverse variance with the random-effects model and receiver operating characteristic curves describing optimal cutoffs and areas under the curve. Bivariate diagnostic random-effects meta-analysis was used to calculate diagnostic accuracy. DATA SYNTHESIS: Twenty-eight studies evaluating 727 individuals were included in the meta-analysis. Individual data were available from 10 studies comprising 190 individuals. The mean difference of relative maximal CBV between glioma grades II and III (n = 727) was 1.76 (95% CI, 1.27-2.24; P < .001). Individual patient data (n = 190) had an area under the curve of 0.77 for discriminating glioma grades II and III at an optimal cutoff of 2.02. When we analyzed astrocytomas separately, the area under the curve increased to 0.86 but decreased to 0.61 when we analyzed oligodendrogliomas. LIMITATIONS: A substantial heterogeneity was found among included studies.
CONCLUSIONS: Glioma grade III had higher relative maximal CBV compared with glioma grade II. A high diagnostic accuracy was found for all patients and astrocytomas; however, the diagnostic accuracy was substantially reduced when discriminating oligodendroglioma grades II and III.
© 2017 by American Journal of Neuroradiology.

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Year:  2017        PMID: 28522666      PMCID: PMC7959917          DOI: 10.3174/ajnr.A5218

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


  38 in total

1.  Data-driven grading of brain gliomas: a multiparametric MR imaging study.

Authors:  Massimo Caulo; Valentina Panara; Domenico Tortora; Peter A Mattei; Chiara Briganti; Emanuele Pravatà; Simone Salice; Antonio R Cotroneo; Armando Tartaro
Journal:  Radiology       Date:  2014-03-22       Impact factor: 11.105

2.  Combined value of susceptibility-weighted and perfusion-weighted imaging in assessing who grade for brain astrocytomas.

Authors:  Xiao-chun Wang; Hui Zhang; Yan Tan; Jiang-bo Qin; Xiao-feng Wu; Le Wang; Lei Zhang
Journal:  J Magn Reson Imaging       Date:  2014-06       Impact factor: 4.813

3.  Comparing perfusion metrics obtained from a single compartment versus pharmacokinetic modeling methods using dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade.

Authors:  M Law; R Young; J Babb; M Rad; T Sasaki; D Zagzag; G Johnson
Journal:  AJNR Am J Neuroradiol       Date:  2006-10       Impact factor: 3.825

4.  Histogram analysis of MR imaging-derived cerebral blood volume maps: combined glioma grading and identification of low-grade oligodendroglial subtypes.

Authors:  K E Emblem; D Scheie; P Due-Tonnessen; B Nedregaard; T Nome; J K Hald; K Beiske; T R Meling; A Bjornerud
Journal:  AJNR Am J Neuroradiol       Date:  2008-06-26       Impact factor: 3.825

5.  Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas.

Authors:  T B Nguyen; G O Cron; K Perdrizet; K Bezzina; C H Torres; S Chakraborty; J Woulfe; G H Jansen; J Sinclair; R E Thornhill; C Foottit; B Zanette; I G Cameron
Journal:  AJNR Am J Neuroradiol       Date:  2015-07-30       Impact factor: 3.825

6.  Benefit from procarbazine, lomustine, and vincristine in oligodendroglial tumors is associated with mutation of IDH.

Authors:  J Gregory Cairncross; Meihua Wang; Robert B Jenkins; Edward G Shaw; Caterina Giannini; David G Brachman; Jan C Buckner; Karen L Fink; Luis Souhami; Normand J Laperriere; Jason T Huse; Minesh P Mehta; Walter J Curran
Journal:  J Clin Oncol       Date:  2014-02-10       Impact factor: 44.544

7.  Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas.

Authors:  Sofie Van Cauter; Frederik De Keyzer; Diana M Sima; Anca Croitor Sava; Felice D'Arco; Jelle Veraart; Ronald R Peeters; Alexander Leemans; Stefaan Van Gool; Guido Wilms; Philippe Demaerel; Sabine Van Huffel; Stefan Sunaert; Uwe Himmelreich
Journal:  Neuro Oncol       Date:  2014-07       Impact factor: 12.300

8.  Discrimination between glioma grades II and III in suspected low-grade gliomas using dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging: a histogram analysis approach.

Authors:  Anna Falk; Markus Fahlström; Egill Rostrup; Shala Berntsson; Maria Zetterling; Arvid Morell; Henrik B W Larsson; Anja Smits; Elna-Marie Larsson
Journal:  Neuroradiology       Date:  2014-09-10       Impact factor: 2.804

9.  Grading diffuse gliomas without intense contrast enhancement by amide proton transfer MR imaging: comparisons with diffusion- and perfusion-weighted imaging.

Authors:  Osamu Togao; Akio Hiwatashi; Koji Yamashita; Kazufumi Kikuchi; Jochen Keupp; Koji Yoshimoto; Daisuke Kuga; Masami Yoneyama; Satoshi O Suzuki; Toru Iwaki; Masaya Takahashi; Koji Iihara; Hiroshi Honda
Journal:  Eur Radiol       Date:  2016-03-22       Impact factor: 5.315

10.  Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors.

Authors:  Jeanette E Eckel-Passow; Daniel H Lachance; Annette M Molinaro; Kyle M Walsh; Paul A Decker; Hugues Sicotte; Melike Pekmezci; Terri Rice; Matt L Kosel; Ivan V Smirnov; Gobinda Sarkar; Alissa A Caron; Thomas M Kollmeyer; Corinne E Praska; Anisha R Chada; Chandralekha Halder; Helen M Hansen; Lucie S McCoy; Paige M Bracci; Roxanne Marshall; Shichun Zheng; Gerald F Reis; Alexander R Pico; Brian P O'Neill; Jan C Buckner; Caterina Giannini; Jason T Huse; Arie Perry; Tarik Tihan; Mitchell S Berger; Susan M Chang; Michael D Prados; Joseph Wiemels; John K Wiencke; Margaret R Wrensch; Robert B Jenkins
Journal:  N Engl J Med       Date:  2015-06-10       Impact factor: 176.079

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  18 in total

1.  Prognostic Value of Preoperative MRI Metrics for Diffuse Lower-Grade Glioma Molecular Subtypes.

Authors:  P Darvishi; P P Batchala; J T Patrie; L M Poisson; M-B Lopes; R Jain; C E Fadul; D Schiff; S H Patel
Journal:  AJNR Am J Neuroradiol       Date:  2020-04-23       Impact factor: 3.825

2.  Arterial spin labeling MR imaging for differentiation between high- and low-grade glioma-a meta-analysis.

Authors:  Alberto Falk Delgado; Francesca De Luca; Danielle van Westen; Anna Falk Delgado
Journal:  Neuro Oncol       Date:  2018-10-09       Impact factor: 12.300

3.  Dynamic susceptibility contrast and diffusion MR imaging identify oligodendroglioma as defined by the 2016 WHO classification for brain tumors: histogram analysis approach.

Authors:  Anna Latysheva; Kyrre Eeg Emblem; Petter Brandal; Einar Osland Vik-Mo; Jens Pahnke; Kjetil Røysland; John K Hald; Andrés Server
Journal:  Neuroradiology       Date:  2019-02-02       Impact factor: 2.804

Review 4.  Discrimination between primary low-grade and high-grade glioma with 11C-methionine PET: a bivariate diagnostic test accuracy meta-analysis.

Authors:  Anna Falk Delgado; Alberto Falk Delgado
Journal:  Br J Radiol       Date:  2018-01-22       Impact factor: 3.039

5.  Combining 18F-DOPA PET and MRI with perfusion-weighted imaging improves delineation of high-grade subregions in enhancing and non-enhancing gliomas prior treatment: a biopsy-controlled study.

Authors:  Antoine Girard; Pierre-Jean Le Reste; Alice Metais; Beatrice Carsin Nicol; Dan Cristian Chiforeanu; Elise Bannier; Boris Campillo-Gimenez; Anne Devillers; Xavier Palard-Novello; Florence Le Jeune
Journal:  J Neurooncol       Date:  2021-10-22       Impact factor: 4.130

6.  MRI features predict tumor grade in isocitrate dehydrogenase (IDH)-mutant astrocytoma and oligodendroglioma.

Authors:  David A Joyner; John Garrett; Prem P Batchala; Bharath Rama; Joshua R Ravicz; James T Patrie; Maria-B Lopes; Camilo E Fadul; David Schiff; Rajan Jain; Sohil H Patel
Journal:  Neuroradiology       Date:  2022-08-12       Impact factor: 2.995

7.  Amide proton transfer-weighted MRI in distinguishing high- and low-grade gliomas: a systematic review and meta-analysis.

Authors:  Chong Hyun Suh; Ji Eun Park; Seung Chai Jung; Choong Gon Choi; Sang Joon Kim; Ho Sung Kim
Journal:  Neuroradiology       Date:  2019-01-21       Impact factor: 2.804

Review 8.  MRI biomarkers in neuro-oncology.

Authors:  Marion Smits
Journal:  Nat Rev Neurol       Date:  2021-06-20       Impact factor: 42.937

Review 9.  Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML).

Authors:  Rima Hajjo; Dima A Sabbah; Sanaa K Bardaweel; Alexander Tropsha
Journal:  Diagnostics (Basel)       Date:  2021-04-21

10.  Exploring diagnostic performance of T2 mapping in diffuse glioma grading.

Authors:  Weibin Gu; Shiyuan Fang; Xinyi Hou; Ding Ma; Shaowu Li
Journal:  Quant Imaging Med Surg       Date:  2021-07
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