Literature DB >> 26732081

The diagnostic accuracy of multiparametric MRI to determine pediatric brain tumor grades and types.

Mériam Koob1,2, Nadine Girard3,4, Badih Ghattas5, Slim Fellah6, Sylviane Confort-Gouny4, Dominique Figarella-Branger7,8, Didier Scavarda9.   

Abstract

Childhood brain tumors show great histological variability. The goal of this retrospective study was to assess the diagnostic accuracy of multimodal MR imaging (diffusion, perfusion, MR spectroscopy) in the distinction of pediatric brain tumor grades and types. Seventy-six patients (range 1 month to 18 years) with brain tumors underwent multimodal MR imaging. Tumors were categorized by grade (I-IV) and by histological type (A-H). Multivariate statistical analysis was performed to evaluate the diagnostic accuracy of single and combined MR modalities, and of single imaging parameters to distinguish the different groups. The highest diagnostic accuracy for tumor grading was obtained with diffusion-perfusion (73.24%) and for tumor typing with diffusion-perfusion-MR spectroscopy (55.76%). The best diagnostic accuracy was obtained for tumor grading in I and IV and for tumor typing in embryonal tumor and pilocytic astrocytoma. Poor accuracy was seen in other grades and types. ADC and rADC were the best parameters for tumor grading and typing followed by choline level with an intermediate echo time, CBV for grading and Tmax for typing. Multiparametric MR imaging can be accurate in determining tumor grades (primarily grades I and IV) and types (mainly pilocytic astrocytomas and embryonal tumors) in children.

Entities:  

Keywords:  Brain neoplasms; Child; Diffusion magnetic resonance imaging; Magnetic resonance angiography; Magnetic resonance spectroscopy

Mesh:

Year:  2016        PMID: 26732081     DOI: 10.1007/s11060-015-2042-4

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


  29 in total

1.  Value and limitations of diffusion-weighted imaging in grading and diagnosis of pediatric posterior fossa tumors.

Authors:  J L Jaremko; L B O Jans; L T Coleman; M R Ditchfield
Journal:  AJNR Am J Neuroradiol       Date:  2010-06-10       Impact factor: 3.825

2.  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

3.  Minimum apparent diffusion coefficients in the evaluation of brain tumors.

Authors:  Omer Kitis; Hakan Altay; Cem Calli; Nilgun Yunten; Taner Akalin; Taskin Yurtseven
Journal:  Eur J Radiol       Date:  2005-09       Impact factor: 3.528

4.  Accurate classification of childhood brain tumours by in vivo ¹H MRS - a multi-centre study.

Authors:  Javier Vicente; Elies Fuster-Garcia; Salvador Tortajada; Juan M García-Gómez; Nigel Davies; Kal Natarajan; Martin Wilson; Richard G Grundy; Pieter Wesseling; Daniel Monleón; Bernardo Celda; Montserrat Robles; Andrew C Peet
Journal:  Eur J Cancer       Date:  2012-10-02       Impact factor: 9.162

5.  Multimodal MR imaging (diffusion, perfusion, and spectroscopy): is it possible to distinguish oligodendroglial tumor grade and 1p/19q codeletion in the pretherapeutic diagnosis?

Authors:  S Fellah; D Caudal; A M De Paula; P Dory-Lautrec; D Figarella-Branger; O Chinot; P Metellus; P J Cozzone; S Confort-Gouny; B Ghattas; V Callot; N Girard
Journal:  AJNR Am J Neuroradiol       Date:  2012-12-06       Impact factor: 3.825

6.  Intraaxial brain masses: MR imaging-based diagnostic strategy--initial experience.

Authors:  Riyadh N Al-Okaili; Jaroslaw Krejza; John H Woo; Ronald L Wolf; Donald M O'Rourke; Kevin D Judy; Harish Poptani; Elias R Melhem
Journal:  Radiology       Date:  2007-05       Impact factor: 11.105

7.  Differentiation of primary central nervous system lymphomas and glioblastomas: comparisons of diagnostic performance of dynamic susceptibility contrast-enhanced perfusion MR imaging without and with contrast-leakage correction.

Authors:  C H Toh; K-C Wei; C-N Chang; S-H Ng; H-F Wong
Journal:  AJNR Am J Neuroradiol       Date:  2013-01-24       Impact factor: 3.825

Review 8.  Neuroimaging of pediatric brain tumors: from basic to advanced magnetic resonance imaging (MRI).

Authors:  Ashok Panigrahy; Stefan Blüml
Journal:  J Child Neurol       Date:  2009-11       Impact factor: 1.987

Review 9.  Pediatric brain tumors.

Authors:  Lara A Brandão; Tina Young Poussaint
Journal:  Neuroimaging Clin N Am       Date:  2013-05-18       Impact factor: 2.264

10.  Preoperative grading of presumptive low-grade astrocytomas on MR imaging: diagnostic value of minimum apparent diffusion coefficient.

Authors:  E J Lee; S K Lee; R Agid; J M Bae; A Keller; K Terbrugge
Journal:  AJNR Am J Neuroradiol       Date:  2008-08-21       Impact factor: 3.825

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  10 in total

Review 1.  Magnetic resonance perfusion for differentiating low-grade from high-grade gliomas at first presentation.

Authors:  Jill M Abrigo; Daniel M Fountain; James M Provenzale; Eric K Law; Joey Sw Kwong; Michael G Hart; Wilson Wai San Tam
Journal:  Cochrane Database Syst Rev       Date:  2018-01-22

2.  Perfusion-weighted techniques in MRI grading of pediatric cerebral tumors: efficiency of dynamic susceptibility contrast and arterial spin labeling.

Authors:  B Testud; G Brun; A Varoquaux; J F Hak; R Appay; A Le Troter; N Girard; J P Stellmann
Journal:  Neuroradiology       Date:  2021-01-27       Impact factor: 2.804

3.  Differentiation of paediatric posterior fossa tumours by the multiregional and multiparametric MRI radiomics approach: a study on the selection of optimal multiple sequences and multiregions.

Authors:  Jie Dong; Suxiao Li; Lei Li; Shengxiang Liang; Bin Zhang; Yun Meng; Xiaofang Zhang; Yong Zhang; Shujun Zhao
Journal:  Br J Radiol       Date:  2021-11-19       Impact factor: 3.039

Review 4.  Radiohistogenomics of pediatric low-grade neuroepithelial tumors.

Authors:  Asim K Bag; Jason Chiang; Zoltan Patay
Journal:  Neuroradiology       Date:  2021-03-29       Impact factor: 2.804

5.  Dynamic susceptibility-contrast magnetic resonance imaging with contrast agent leakage correction aids in predicting grade in pediatric brain tumours: a multicenter study.

Authors:  Stephanie B Withey; Lesley MacPherson; Adam Oates; Stephen Powell; Jan Novak; Laurence Abernethy; Barry Pizer; Richard Grundy; Paul S Morgan; Simon Bailey; Dipayan Mitra; Theodoros N Arvanitis; Dorothee P Auer; Shivaram Avula; Andrew C Peet
Journal:  Pediatr Radiol       Date:  2022-03-15

6.  Perfusion, Diffusion, Or Brain Tumor Barrier Integrity: Which Represents The Glioma Features Best?

Authors:  Lin-Feng Yan; Ying-Zhi Sun; Sha-Sha Zhao; Yu-Chuan Hu; Yu Han; Gang Li; Xin Zhang; Qiang Tian; Zhi-Cheng Liu; Yang Yang; Hai-Yan Nan; Ying Yu; Qian Sun; Jin Zhang; Ping Chen; Bo Hu; Fei Li; Teng-Hui Han; Wen Wang; Guang-Bin Cui
Journal:  Cancer Manag Res       Date:  2019-11-27       Impact factor: 3.989

7.  The Diagnostic Value of Apparent Diffusion Coefficient and Proton Magnetic Resonance Spectroscopy in the Grading of Pediatric Gliomas.

Authors:  Rong Yao; Ailan Cheng; Menglin Liu; Zhengwei Zhang; Biao Jin; Hong Yu
Journal:  J Comput Assist Tomogr       Date:  2021 Mar-Apr 01       Impact factor: 2.081

8.  The impact of magnetic resonance imaging spectroscopy parameters on differentiating between paediatric medulloblastoma and ependymoma.

Authors:  Nguyen Minh Duc
Journal:  Contemp Oncol (Pozn)       Date:  2021-05-06

Review 9.  The role of artificial intelligence in paediatric neuroradiology.

Authors:  Catherine Pringle; John-Paul Kilday; Ian Kamaly-Asl; Stavros Michael Stivaros
Journal:  Pediatr Radiol       Date:  2022-03-26

10.  MRI feature analysis of uncommon prostatic malignant tumors.

Authors:  Zhao-Yan Feng; Xiang-De Min; Liang Wang; Ba-Sen Li; Zan Ke; Pei-Pei Zhang; Zhen Kang
Journal:  Asian J Androl       Date:  2018 May-Jun       Impact factor: 3.285

  10 in total

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