Literature DB >> 23994941

Differentiation of primary central nervous system lymphomas from high-grade gliomas by rCBV and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging.

Z Xing1, R X You, J Li, Y Liu, D R Cao.   

Abstract

PURPOSE: Primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) may have similar enhancement patterns on magnetic resonance imaging (MRI), making the differential diagnosis difficult or even impractical. Relative cerebral blood volume (rCBV) and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MR imaging may help distinguish PCNSL from HGG. The purpose of this study was to evaluate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of these two imaging parameters used alone or in combination for differentiating PCNSL from HGG.
METHODS: A total of 12 patients with PCNSL and 26 patients with HGG were examined using a 3T scanner. rCBV and percentage of signal intensity recovery were obtained and receiver operating characteristic (ROC) analysis was performed to determine optimum thresholds for tumor differentiation. Sensitivity, specificity, PPV, NPV, and accuracy for identifying the tumor types were also calculated.
RESULTS: The optimum threshold of 2.56 for rCBV provided sensitivity, specificity, PPV, NPV, and accuracy of 96.2, 90, 92.6, 94.7, and 93.5%, respectively, for determining PCNSL. A threshold value of 0.89 for percentage of signal intensity recovery optimized differentiation of PCNSL and HGG with a sensitivity, specificity, PPV, NPV, and accuracy of 100, 88.5, 87, 100, and 93.5%, respectively. Combining rCBV with the percentage of signal intensity recovery further improved the differentiation of PCNSL and HGG with a specificity of 98.5% and an accuracy of 95.7%.
CONCLUSIONS: The combination of rCBV measurement with percentage of signal intensity recovery can help in more accurate differentiation of PCNSL from HGG.

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Year:  2013        PMID: 23994941     DOI: 10.1007/s00062-013-0255-5

Source DB:  PubMed          Journal:  Clin Neuroradiol        ISSN: 1869-1439            Impact factor:   3.649


  43 in total

Review 1.  Methodology of brain perfusion imaging.

Authors:  E L Barbier; L Lamalle; M Décorps
Journal:  J Magn Reson Imaging       Date:  2001-04       Impact factor: 4.813

Review 2.  Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging.

Authors:  Soonmee Cha; Edmond A Knopp; Glyn Johnson; Stephan G Wetzel; Andrew W Litt; David Zagzag
Journal:  Radiology       Date:  2002-04       Impact factor: 11.105

3.  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

4.  Angiogenic patterns and their quantitation in high grade astrocytic tumors.

Authors:  Suash Sharma; Mehar C Sharma; Deepak Kumar Gupta; Chitra Sarkar
Journal:  J Neurooncol       Date:  2006-06-29       Impact factor: 4.130

5.  Evaluation of different cerebral mass lesions by perfusion-weighted MR imaging.

Authors:  Bahattin Hakyemez; Cuneyt Erdogan; Naile Bolca; Nalan Yildirim; Gokhan Gokalp; Mufit Parlak
Journal:  J Magn Reson Imaging       Date:  2006-10       Impact factor: 4.813

6.  Proton magnetic resonance spectroscopy in differentiating glioblastomas from primary cerebral lymphomas and brain metastases.

Authors:  Sanjeev Chawla; Yu Zhang; Sumei Wang; Sangeeta Chaudhary; Chou Chou; Donald M O'Rourke; Arastoo Vossough; Elias R Melhem; Harish Poptani
Journal:  J Comput Assist Tomogr       Date:  2010 Nov-Dec       Impact factor: 1.826

7.  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

8.  Primary cerebral lymphoma and glioblastoma multiforme: differences in diffusion characteristics evaluated with diffusion tensor imaging.

Authors:  C-H Toh; M Castillo; A M-C Wong; K-C Wei; H-F Wong; S-H Ng; Y-L Wan
Journal:  AJNR Am J Neuroradiol       Date:  2007-12-07       Impact factor: 3.825

9.  Perfusion MR imaging: clinical utility for the differential diagnosis of various brain tumors.

Authors:  Sung Ki Cho; Dong Gyu Na; Jae Wook Ryoo; Hong Gee Roh; Chan Hong Moon; Hong Sik Byun; Jong Hyun Kim
Journal:  Korean J Radiol       Date:  2002 Jul-Sep       Impact factor: 3.500

10.  Diffusion-weighted MR imaging derived apparent diffusion coefficient is predictive of clinical outcome in primary central nervous system lymphoma.

Authors:  R F Barajas; J L Rubenstein; J S Chang; J Hwang; S Cha
Journal:  AJNR Am J Neuroradiol       Date:  2009-09-03       Impact factor: 4.966

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  15 in total

1.  Role of rCBV values derived from dynamic susceptibility contrast-enhanced magnetic resonance imaging in differentiating CNS lymphoma from high grade glioma: a meta-analysis.

Authors:  Ruofei Liang; Mao Li; Xiang Wang; Jiewen Luo; Yuan Yang; Qing Mao; Yanhui Liu
Journal:  Int J Clin Exp Med       Date:  2014-12-15

2.  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

Review 3.  Accuracy of percentage of signal intensity recovery and relative cerebral blood volume derived from dynamic susceptibility-weighted, contrast-enhanced MRI in the preoperative diagnosis of cerebral tumours.

Authors:  Ananya Chakravorty; Timothy Steel; Joga Chaganti
Journal:  Neuroradiol J       Date:  2015-10-16

4.  Presurgical Identification of Primary Central Nervous System Lymphoma with Normalized Time-Intensity Curve: A Pilot Study of a New Method to Analyze DSC-PWI.

Authors:  A Pons-Escoda; A Garcia-Ruiz; P Naval-Baudin; M Cos; N Vidal; G Plans; J Bruna; R Perez-Lopez; C Majos
Journal:  AJNR Am J Neuroradiol       Date:  2020-09-17       Impact factor: 3.825

5.  Utility of Percentage Signal Recovery and Baseline Signal in DSC-MRI Optimized for Relative CBV Measurement for Differentiating Glioblastoma, Lymphoma, Metastasis, and Meningioma.

Authors:  M D Lee; G L Baird; L C Bell; C C Quarles; J L Boxerman
Journal:  AJNR Am J Neuroradiol       Date:  2019-08-01       Impact factor: 3.825

6.  High Resolution Imaging of Viscoelastic Properties of Intracranial Tumours by Multi-Frequency Magnetic Resonance Elastography.

Authors:  M Reiss-Zimmermann; K-J Streitberger; I Sack; J Braun; F Arlt; D Fritzsch; K-T Hoffmann
Journal:  Clin Neuroradiol       Date:  2014-06-12       Impact factor: 3.649

7.  Diagnostic Accuracy of T1-Weighted Dynamic Contrast-Enhanced-MRI and DWI-ADC for Differentiation of Glioblastoma and Primary CNS Lymphoma.

Authors:  X Lin; M Lee; O Buck; K M Woo; Z Zhang; V Hatzoglou; A Omuro; J Arevalo-Perez; A A Thomas; J Huse; K Peck; A I Holodny; R J Young
Journal:  AJNR Am J Neuroradiol       Date:  2016-12-08       Impact factor: 3.825

Review 8.  The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: A systematic review and meta-analysis.

Authors:  Weilin Xu; Qun Wang; Anwen Shao; Bainan Xu; Jianmin Zhang
Journal:  PLoS One       Date:  2017-03-16       Impact factor: 3.240

Review 9.  Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges.

Authors:  Junfeng Zhang; Heng Liu; Haipeng Tong; Sumei Wang; Yizeng Yang; Gang Liu; Weiguo Zhang
Journal:  Contrast Media Mol Imaging       Date:  2017-03-20       Impact factor: 3.161

10.  Performance of diffusion and perfusion MRI in evaluating primary central nervous system lymphomas of different locations.

Authors:  Zhen Xing; Nannan Kang; Yu Lin; Xiaofang Zhou; Zebin Xiao; Dairong Cao
Journal:  BMC Med Imaging       Date:  2020-06-09       Impact factor: 1.930

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