Literature DB >> 29090331

Differentiation of grade II/III and grade IV glioma by combining "T1 contrast-enhanced brain perfusion imaging" and susceptibility-weighted quantitative imaging.

Jitender Saini1, Pradeep Kumar Gupta2, Prativa Sahoo3,4, Anup Singh5, Rana Patir6, Suneeta Ahlawat7, Manish Beniwal8, K Thennarasu9, Vani Santosh10, Rakesh Kumar Gupta11.   

Abstract

PURPOSE: MRI is a useful method for discriminating low- and high-grade glioma using perfusion MRI and susceptibility-weighted imaging (SWI). The purpose of this study is to evaluate the usefulness of T1-perfusion MRI and SWI in discriminating among grade II, III, and IV gliomas.
METHODS: T1-perfusion MRI was used to measure relative cerebral blood volume (rCBV) in 129 patients with glioma (70 grade IV, 33 grade III, and 26 grade II tumors). SWI was also used to measure the intratumoral susceptibility signal intensity (ITSS) scores for each tumor in these patients. rCBV and ITSS values were compared to seek differences between grade II vs. grade III, grade III vs. grade IV, and grade III+II vs. grade IV tumors.
RESULTS: Significant differences in rCBV values of the three grades of the tumors were noted and pairwise comparisons showed significantly higher rCBV values in grade IV tumors as compared to grade III tumors, and similarly increased rCBV was seen in the grade III tumors as compared to grade II tumors (p < 0.001). Grade IV gliomas showed significantly higher ITSS scores on SWI as compared to grade III tumors (p < 0.001) whereas insignificant difference was seen on comparing ITSS scores of grade III with grade II tumors. Combining the rCBV and ITSS resulted in significant improvement in the discrimination of grade III from grade IV tumors.
CONCLUSION: The combination of rCBV values derived from T1-perfusion MRI and SWI derived ITSS scores improves the diagnostic accuracy for discrimination of grade III from grade IV gliomas.

Entities:  

Keywords:  Brain tumor; Glioma; Susceptibility-weighted imaging; T1-perfusion MRI

Mesh:

Substances:

Year:  2017        PMID: 29090331     DOI: 10.1007/s00234-017-1942-8

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  39 in total

1.  Current Management of Adult Diffuse Infiltrative Low Grade Gliomas.

Authors:  Emilie Le Rhun; Sophie Taillibert; Marc C Chamberlain
Journal:  Curr Neurol Neurosci Rep       Date:  2016-02       Impact factor: 5.081

Review 2.  The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Authors:  David N Louis; Arie Perry; Guido Reifenberger; Andreas von Deimling; Dominique Figarella-Branger; Webster K Cavenee; Hiroko Ohgaki; Otmar D Wiestler; Paul Kleihues; David W Ellison
Journal:  Acta Neuropathol       Date:  2016-05-09       Impact factor: 17.088

3.  Magnetic resonance perfusion and permeability imaging in brain tumors.

Authors:  Saulo Lacerda; Meng Law
Journal:  Neuroimaging Clin N Am       Date:  2009-11       Impact factor: 2.264

4.  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

5.  Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; T Hirai; T Okuda; Y Shigematsu; L Liang; Y Ge; Y Ushio; M Takahashi
Journal:  AJR Am J Roentgenol       Date:  1998-12       Impact factor: 3.959

6.  Utility of multiparametric 3-T MRI for glioma characterization.

Authors:  Bhaswati Roy; Rakesh K Gupta; Andrew A Maudsley; Rishi Awasthi; Sulaiman Sheriff; Meng Gu; Nuzhat Husain; Sudipta Mohakud; Sanjay Behari; Chandra M Pandey; Ram K S Rathore; Daniel M Spielman; Jeffry R Alger
Journal:  Neuroradiology       Date:  2013-02-02       Impact factor: 2.804

Review 7.  Understanding high grade glioma: molecular mechanism, therapy and comprehensive management.

Authors:  Yongzhi Wang; Tao Jiang
Journal:  Cancer Lett       Date:  2013-01-20       Impact factor: 8.679

8.  Subcompartmentalization of extracellular extravascular space (EES) into permeability and leaky space with local arterial input function (AIF) results in improved discrimination between high- and low-grade glioma using dynamic contrast-enhanced (DCE) MRI.

Authors:  Prativa Sahoo; Ram K S Rathore; Rishi Awasthi; Bhaswati Roy; Sanjay Verma; Divya Rathore; Sanjay Behari; Mazhar Husain; Nuzhat Husain; Chandra M Pandey; Sudipta Mohakud; Rakesh K Gupta
Journal:  J Magn Reson Imaging       Date:  2013-02-06       Impact factor: 4.813

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.  Expression of vascular endothelial growth factor and its receptors in the anaplastic progression of astrocytoma, oligodendroglioma, and ependymoma.

Authors:  A S Chan; S Y Leung; M P Wong; S T Yuen; N Cheung; Y W Fan; L P Chung
Journal:  Am J Surg Pathol       Date:  1998-07       Impact factor: 6.394

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  7 in total

1.  Comparative evaluation of intracranial oligodendroglioma and astrocytoma of similar grades using conventional and T1-weighted DCE-MRI.

Authors:  Mamta Gupta; Abhinav Gupta; Virendra Yadav; Suhail P Parvaze; Anup Singh; Jitender Saini; Rana Patir; Sandeep Vaishya; Sunita Ahlawat; Rakesh Kumar Gupta
Journal:  Neuroradiology       Date:  2021-01-19       Impact factor: 2.804

2.  Intra-tumoral susceptibility signal: a post-processing technique for objective grading of astrocytoma with susceptibility-weighted imaging.

Authors:  Tzu-Chao Chuang; Yen-Lin Chen; Wan-Pin Shui; Hsiao-Wen Chung; Shu-Shong Hsu; Ping-Hong Lai
Journal:  Quant Imaging Med Surg       Date:  2022-01

3.  Grading of IDH-mutant astrocytoma using diffusion, susceptibility and perfusion-weighted imaging.

Authors:  Xiefeng Yang; Zhen Xing; Dejun She; Yu Lin; Hua Zhang; Yan Su; Dairong Cao
Journal:  BMC Med Imaging       Date:  2022-05-29       Impact factor: 2.795

4.  Differentiating intracranial solitary fibrous tumor/hemangiopericytoma from meningioma using diffusion-weighted imaging and susceptibility-weighted imaging.

Authors:  Tanhui Chen; Bingqing Jiang; Yingyan Zheng; Dejun She; Hua Zhang; Zhen Xing; Dairong Cao
Journal:  Neuroradiology       Date:  2019-10-31       Impact factor: 2.804

5.  Utility of multiparametric pre-operative magnetic resonance imaging in differentiation of chordoid meningioma from the other histopathological subtypes of meningioma-a retrospective study.

Authors:  Sameer Peer; Jitender Saini; Chandrajit Prasad; Karthik Kulanthaivelu; Nishanth Sadashiva; Bevinahalli N Nandeesh; Alok Mohan Uppar; Shilpa Rao
Journal:  Neuroradiology       Date:  2021-04-10       Impact factor: 2.804

6.  Preliminary study of multiple b-value diffusion-weighted images and T1 post enhancement magnetic resonance imaging images fusion with Laplacian Re-decomposition (LRD) medical fusion algorithm for glioma grading.

Authors:  Amir Khorasani; Mohamad Bagher Tavakoli; Masih Saboori; Milad Jalilian
Journal:  Eur J Radiol Open       Date:  2021-09-29

7.  A simple model for glioma grading based on texture analysis applied to conventional brain MRI.

Authors:  José Gerardo Suárez-García; Javier Miguel Hernández-López; Eduardo Moreno-Barbosa; Benito de Celis-Alonso
Journal:  PLoS One       Date:  2020-05-15       Impact factor: 3.240

  7 in total

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