Literature DB >> 25205290

Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging.

Seunghyun Lee1, Seung Hong Choi, Inseon Ryoo, Tae Jin Yoon, Tae Min Kim, Se-Hoon Lee, Chul-Kee Park, Ji-Hoon Kim, Chul-Ho Sohn, Sung-Hye Park, Il Han Kim.   

Abstract

The purpose of our study was to explore the difference between isocitrate dehydrogenase (IDH)-1/2 gene mutation-positive and -negative high-grade gliomas (HGGs) using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. We enrolled 52 patients with histopathologically confirmed HGGs with IDH1/2 (P) (n = 16) or IDH1/2 (N) (n = 36). Histogram parameters of ADC and nCBV maps were correlated with gene mutations by using the unpaired student's t test and multivariable stepwise logistic regression analysis. The mean ADC value was higher in the IDH1 (P) group than IDH1 (N) (1,282.8 vs. 1,159.6 mm(2)/s, P = .0113). In terms of the cumulative ADC histograms, the 10th and 50th percentile values were also higher in the IDH1 (P) than IDH1 (N) (P = .0104 and .0183, respectively). We observed a higher 90th percentile value (3.121 vs. 2.397, P = .0208) and a steeper slope between the 10th (C10) and 90th (C90) of cumulative nCBV histograms (0.03386 vs. 0.02425/%, P = .0067) in the IDH1 (N) group. Multivariate analysis showed that the mean ADC mean value (P = .0048), the C90 value (P = .0113), and the slope between C10 and C90 (P = .0049) were the significant variables in the differentiation of IDH1 (P) from IDH1 (N). In conclusion, histogram analysis of ADC and nCBV maps based on entire tumor volume can be a useful tool for distinguishing IDH1 (P) and IDH1 (N), and it predicts that IDH (P) tumors have a more heterogeneous microenvironment than IDH (N) ones.

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Year:  2014        PMID: 25205290     DOI: 10.1007/s11060-014-1614-z

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.506


  31 in total

1.  Non-invasive detection of 2-hydroxyglutarate and other metabolites in IDH1 mutant glioma patients using magnetic resonance spectroscopy.

Authors:  Whitney B Pope; Robert M Prins; M Albert Thomas; Rajakumar Nagarajan; Katharine E Yen; Mark A Bittinger; Noriko Salamon; Arthur P Chou; William H Yong; Horacio Soto; Neil Wilson; Edward Driggers; Hyun G Jang; Shinsan M Su; David P Schenkein; Albert Lai; Timothy F Cloughesy; Harley I Kornblum; Hong Wu; Valeria R Fantin; Linda M Liau
Journal:  J Neurooncol       Date:  2011-10-21       Impact factor: 4.130

2.  Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction.

Authors:  Benjamín Garzón; Kyrre E Emblem; Kim Mouridsen; Baard Nedregaard; Paulina Due-Tønnessen; Terje Nome; John K Hald; Atle Bjørnerud; Asta K Håberg; Yngve Kvinnsland
Journal:  Acta Radiol       Date:  2011-10-03       Impact factor: 1.990

3.  Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging--correlation with tumor grade.

Authors:  Yusuhn Kang; Seung Hong Choi; Young-Jae Kim; Kwang Gi Kim; Chul-Ho Sohn; Ji-Hoon Kim; Tae Jin Yun; Kee-Hyun Chang
Journal:  Radiology       Date:  2011-10-03       Impact factor: 11.105

4.  Relationship between tumor enhancement, edema, IDH1 mutational status, MGMT promoter methylation, and survival in glioblastoma.

Authors:  J A Carrillo; A Lai; P L Nghiemphu; H J Kim; H S Phillips; S Kharbanda; P Moftakhar; S Lalaezari; W Yong; B M Ellingson; T F Cloughesy; W B Pope
Journal:  AJNR Am J Neuroradiol       Date:  2012-02-09       Impact factor: 3.825

Review 5.  Molecular diagnostics of gliomas.

Authors:  Marina N Nikiforova; Ronald L Hamilton
Journal:  Arch Pathol Lab Med       Date:  2011-05       Impact factor: 5.534

6.  Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not.

Authors:  J L Boxerman; K M Schmainda; R M Weisskoff
Journal:  AJNR Am J Neuroradiol       Date:  2006-04       Impact factor: 3.825

7.  Analysis of the IDH1 codon 132 mutation in brain tumors.

Authors:  Jörg Balss; Jochen Meyer; Wolf Mueller; Andrey Korshunov; Christian Hartmann; Andreas von Deimling
Journal:  Acta Neuropathol       Date:  2008-11-05       Impact factor: 17.088

8.  Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps.

Authors:  Kyrre E Emblem; Baard Nedregaard; Terje Nome; Paulina Due-Tonnessen; John K Hald; David Scheie; Olivera Casar Borota; Milada Cvancarova; Atle Bjornerud
Journal:  Radiology       Date:  2008-06       Impact factor: 11.105

9.  Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas.

Authors:  Christian Hartmann; Jochen Meyer; Jörg Balss; David Capper; Wolf Mueller; Arne Christians; Jörg Felsberg; Marietta Wolter; Christian Mawrin; Wolfgang Wick; Michael Weller; Christel Herold-Mende; Andreas Unterberg; Judith W M Jeuken; Peter Wesseling; Guido Reifenberger; Andreas von Deimling
Journal:  Acta Neuropathol       Date:  2009-06-25       Impact factor: 17.088

10.  Cerebral blood volume analysis in glioblastomas using dynamic susceptibility contrast-enhanced perfusion MRI: a comparison of manual and semiautomatic segmentation methods.

Authors:  Seung Chai Jung; Seung Hong Choi; Jeong A Yeom; Ji-Hoon Kim; Inseon Ryoo; Soo Chin Kim; Hwaseon Shin; A Leum Lee; Tae Jin Yun; Chul-Kee Park; Chul-Ho Sohn; Sung-Hye Park
Journal:  PLoS One       Date:  2013-08-08       Impact factor: 3.240

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  44 in total

1.  MR imaging phenotype correlates with extent of genome-wide copy number abundance in IDH mutant gliomas.

Authors:  Chih-Chun Wu; Rajan Jain; Lucidio Neto; Seema Patel; Laila M Poisson; Jonathan Serrano; Victor Ng; Sohil H Patel; Dimitris G Placantonakis; David Zagzag; John Golfinos; Andrew S Chi; Matija Snuderl
Journal:  Neuroradiology       Date:  2019-05-27       Impact factor: 2.804

2.  MR Imaging-Based Analysis of Glioblastoma Multiforme: Estimation of IDH1 Mutation Status.

Authors:  K Yamashita; A Hiwatashi; O Togao; K Kikuchi; R Hatae; K Yoshimoto; M Mizoguchi; S O Suzuki; T Yoshiura; H Honda
Journal:  AJNR Am J Neuroradiol       Date:  2015-09-24       Impact factor: 3.825

3.  Predicting IDH mutation status in grade II gliomas using amide proton transfer-weighted (APTw) MRI.

Authors:  Shanshan Jiang; Tianyu Zou; Charles G Eberhart; Maria A V Villalobos; Hye-Young Heo; Yi Zhang; Yu Wang; Xianlong Wang; Hao Yu; Yongxing Du; Peter C M van Zijl; Zhibo Wen; Jinyuan Zhou
Journal:  Magn Reson Med       Date:  2017-07-16       Impact factor: 4.668

4.  Effect of Perfusion on Diffusion Kurtosis Imaging Estimates for In Vivo Assessment of Integrated 2016 WHO Glioma Grades : A Cross-Sectional Observational Study.

Authors:  Johann-Martin Hempel; Jens Schittenhelm; Cornelia Brendle; Benjamin Bender; Georg Bier; Marco Skardelly; Ghazaleh Tabatabai; Salvador Castaneda Vega; Ulrike Ernemann; Uwe Klose
Journal:  Clin Neuroradiol       Date:  2017-07-12       Impact factor: 3.649

5.  Radiomics-based machine learning methods for isocitrate dehydrogenase genotype prediction of diffuse gliomas.

Authors:  Shuang Wu; Jin Meng; Qi Yu; Ping Li; Shen Fu
Journal:  J Cancer Res Clin Oncol       Date:  2019-02-04       Impact factor: 4.553

6.  Advanced imaging parameters improve the prediction of diffuse lower-grade gliomas subtype, IDH mutant with no 1p19q codeletion: added value to the T2/FLAIR mismatch sign.

Authors:  Min Kyoung Lee; Ji Eun Park; Youngheun Jo; Seo Young Park; Sang Joon Kim; Ho Sung Kim
Journal:  Eur Radiol       Date:  2019-08-24       Impact factor: 5.315

7.  MRI radiomics analysis of molecular alterations in low-grade gliomas.

Authors:  Ben Shofty; Moran Artzi; Dafna Ben Bashat; Gilad Liberman; Oz Haim; Alon Kashanian; Felix Bokstein; Deborah T Blumenthal; Zvi Ram; Tal Shahar
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-12-21       Impact factor: 2.924

8.  Imaging-Based Algorithm for the Local Grading of Glioma.

Authors:  E D H Gates; J S Lin; J S Weinberg; S S Prabhu; J Hamilton; J D Hazle; G N Fuller; V Baladandayuthapani; D T Fuentes; D Schellingerhout
Journal:  AJNR Am J Neuroradiol       Date:  2020-02-06       Impact factor: 3.825

9.  Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma.

Authors:  Jinhua Yu; Zhifeng Shi; Yuxi Lian; Zeju Li; Tongtong Liu; Yuan Gao; Yuanyuan Wang; Liang Chen; Ying Mao
Journal:  Eur Radiol       Date:  2016-12-21       Impact factor: 5.315

10.  In vivo molecular profiling of human glioma using diffusion kurtosis imaging.

Authors:  Johann-Martin Hempel; Sotirios Bisdas; Jens Schittenhelm; Cornelia Brendle; Benjamin Bender; Henk Wassmann; Marco Skardelly; Ghazaleh Tabatabai; Salvador Castaneda Vega; Ulrike Ernemann; Uwe Klose
Journal:  J Neurooncol       Date:  2016-09-07       Impact factor: 4.130

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