Literature DB >> 29223713

Diagnostic Values of DCE-MRI and DSC-MRI for Differentiation Between High-grade and Low-grade Gliomas: A Comprehensive Meta-analysis.

Jianye Liang1, Dexiang Liu2, Peng Gao1, Dong Zhang1, Hanwei Chen2, Changzheng Shi3, Liangping Luo4.   

Abstract

RATIONALE AND
OBJECTIVES: This study aimed to collect the studies on the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI) in differentiating the grades of gliomas, and evaluate the diagnostic performances of relevant quantitative parameters in glioma grading.
MATERIALS AND METHODS: We systematically searched studies on the diagnosis of gliomas with DCE-MRI or DSC-MRI in Medline, PubMed, China National Knowledge Infrastructure database, Cochrane Library, and Embase published between January 2005 and December 2016. Standardized mean differences and 95% confidence intervals were calculated for volume transfer coefficient (Ktrans), volume fraction of extravascular extracellular space (Ve), rate constant of backflux (Kep), relative cerebral blood volume (rCBV), and relative cerebral blood flow (rCBF) using Review Manager 5.2 software. Sensitivity, specificity, area under the curve (AUC), and Begg test were calculated by Stata 12.0.
RESULTS: Twenty-two studies with available outcome data were included in the analysis. The standardized mean difference of Ktrans values between high-grade glioma and low-grade glioma were 1.18 (0.91, 1.45); Ve values were 1.43 (1.06, 1.80); Kep values were 0.65 (-0.05, 1.36); rCBV values were 1.44 (1.08, 1.81); and rCBF values were 1.17 (0.68, 1.67), respectively. The results were all significant statistically (P < .05) except Kep values (P = .07), and high-grade glioma had higher Ktrans, Ve, rCBV, and rCBF values than low-grade glioma. AUC values of Ktrans, Ve, rCBV, and rCBF were 0.90, 0.88, 0.93, and 0.73, respectively; rCBV had the largest AUC among the four parameters (P < .05).
CONCLUSION: Both DCE-MRI and DSC-MRI are reliable techniques in differentiating the grades of gliomas, and rCBV was found to be the most sensitive one.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  DCE-MRI; DSC-MRI; Gliomas; grading; meta-analysis

Mesh:

Substances:

Year:  2017        PMID: 29223713     DOI: 10.1016/j.acra.2017.10.001

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  16 in total

1.  Volumetric Measurement of Relative CBV Using T1-Perfusion-Weighted MRI with High Temporal Resolution Compared with Traditional T2*-Perfusion-Weighted MRI in Postoperative Patients with High-Grade Gliomas.

Authors:  M Seo; K-J Ahn; Y Choi; N-Y Shin; J Jang; B-S Kim
Journal:  AJNR Am J Neuroradiol       Date:  2022-05-26       Impact factor: 4.966

2.  Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status.

Authors:  Shuangshuang Song; Leiming Wang; Hongwei Yang; Yongzhi Shan; Ye Cheng; Lixin Xu; Chengyan Dong; Guoguang Zhao; Jie Lu
Journal:  Eur Radiol       Date:  2020-11-19       Impact factor: 5.315

3.  Glioma Grading on Conventional MR Images: A Deep Learning Study With Transfer Learning.

Authors:  Yang Yang; Lin-Feng Yan; Xin Zhang; Yu Han; Hai-Yan Nan; Yu-Chuan Hu; Bo Hu; Song-Lin Yan; Jin Zhang; Dong-Liang Cheng; Xiang-Wei Ge; Guang-Bin Cui; Di Zhao; Wen Wang
Journal:  Front Neurosci       Date:  2018-11-15       Impact factor: 4.677

Review 4.  The surgical perspective in precision treatment of diffuse gliomas.

Authors:  Niklas Thon; Joerg-Christian Tonn; Friedrich-Wilhelm Kreth
Journal:  Onco Targets Ther       Date:  2019-02-22       Impact factor: 4.147

5.  Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models.

Authors:  Marianna Inglese; Katherine L Ordidge; Lesley Honeyfield; Tara D Barwick; Eric O Aboagye; Adam D Waldman; Matthew Grech-Sollars
Journal:  Neuroradiology       Date:  2019-08-07       Impact factor: 2.804

6.  Correction to: Advanced imaging in adult diffusely infiltrating low-grade gliomas.

Authors:  Nail Bulakbaşı; Yahya Paksoy
Journal:  Insights Imaging       Date:  2020-04-22

7.  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

8.  Diagnostic Performance of Diffusion Tensor Imaging for Characterizing Breast Tumors: A Comprehensive Meta-Analysis.

Authors:  Kai Wang; Zhipeng Li; Zhifeng Wu; Yucong Zheng; Sihui Zeng; Linning E; Jianye Liang
Journal:  Front Oncol       Date:  2019-11-18       Impact factor: 6.244

Review 9.  Advanced imaging in adult diffusely infiltrating low-grade gliomas.

Authors:  Nail Bulakbaşı; Yahya Paksoy
Journal:  Insights Imaging       Date:  2019-12-18

10.  Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis.

Authors:  Sachi Okuchi; Antonio Rojas-Garcia; Agne Ulyte; Ingeborg Lopez; Jurgita Ušinskienė; Martin Lewis; Sara M Hassanein; Eser Sanverdi; Xavier Golay; Stefanie Thust; Jasmina Panovska-Griffiths; Sotirios Bisdas
Journal:  Cancer Med       Date:  2019-08-07       Impact factor: 4.452

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.