Literature DB >> 25204450

Discrimination between glioma grades II and III in suspected low-grade gliomas using dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging: a histogram analysis approach.

Anna Falk1, Markus Fahlström, Egill Rostrup, Shala Berntsson, Maria Zetterling, Arvid Morell, Henrik B W Larsson, Anja Smits, Elna-Marie Larsson.   

Abstract

INTRODUCTION: Perfusion magnetic resonance imaging (MRI) can be used in the pre-operative assessment of brain tumours. The aim of this prospective study was to identify the perfusion parameters from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) perfusion imaging that could best discriminate between grade II and III gliomas.
METHODS: MRI (3 T) including morphological ((T2 fluid attenuated inversion recovery (FLAIR) and T1-weighted (T1W)+Gd)) and perfusion (DCE and DSC) sequences was performed in 39 patients with newly diagnosed suspected low-grade glioma after written informed consent in this review board-approved study. Regions of interests (ROIs) in tumour area were delineated on FLAIR images co-registered to DCE and DSC, respectively, in 25 patients with histopathological grade II (n = 18) and III (n = 7) gliomas. Statistical analysis of differences between grade II and grade III gliomas in histogram perfusion parameters was performed, and the areas under the curves (AUC) from the ROC analyses were evaluated.
RESULTS: In DCE, the skewness of transfer constant (k(trans)) was found superior for differentiating grade II from grade III in all gliomas (AUC 0.76). In DSC, the standard deviation of relative cerebral blood flow (rCBF) was found superior for differentiating grade II from grade III gliomas (AUC 0.80).
CONCLUSIONS: Histogram parameters from k(trans) (DCE) and rCBF (DSC) could most efficiently discriminate between grade II and grade III gliomas.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25204450     DOI: 10.1007/s00234-014-1426-z

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


  31 in total

1.  Quantification of cerebral blood flow, cerebral blood volume, and blood-brain-barrier leakage with DCE-MRI.

Authors:  Steven Sourbron; Michael Ingrisch; Axel Siefert; Maximilian Reiser; Karin Herrmann
Journal:  Magn Reson Med       Date:  2009-07       Impact factor: 4.668

Review 2.  Modeling tracer kinetics in dynamic Gd-DTPA MR imaging.

Authors:  P S Tofts
Journal:  J Magn Reson Imaging       Date:  1997 Jan-Feb       Impact factor: 4.813

3.  MR diffusion tensor and perfusion-weighted imaging in preoperative grading of supratentorial nonenhancing gliomas.

Authors:  Xiang Liu; Wei Tian; Balasubramanya Kolar; Gabrielle A Yeaney; Xing Qiu; Mahlon D Johnson; Sven Ekholm
Journal:  Neuro Oncol       Date:  2011-02-04       Impact factor: 12.300

4.  Role of perfusion-weighted imaging at 3T in the histopathological differentiation between astrocytic and oligodendroglial tumors.

Authors:  Taiichi Saito; Fumiyuki Yamasaki; Yoshinori Kajiwara; Nobukazu Abe; Yuji Akiyama; Takako Kakuda; Yukio Takeshima; Kazuhiko Sugiyama; Yoshikazu Okada; Kaoru Kurisu
Journal:  Eur J Radiol       Date:  2011-05-04       Impact factor: 3.528

5.  Dynamic contrast-enhanced quantitative perfusion measurement of the brain using T1-weighted MRI at 3T.

Authors:  Henrik B W Larsson; Adam E Hansen; Hilde K Berg; Egill Rostrup; Olav Haraldseth
Journal:  J Magn Reson Imaging       Date:  2008-04       Impact factor: 4.813

6.  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

7.  Relative cerebral blood volume measurements of low-grade gliomas predict patient outcome in a multi-institution setting.

Authors:  Gisele B Caseiras; Sophie Chheang; James Babb; Jeremy H Rees; Nicole Pecerrelli; Daniel J Tozer; Christopher Benton; David Zagzag; Glyn Johnson; Adam D Waldman; H R Jäger; Meng Law
Journal:  Eur J Radiol       Date:  2009-02-06       Impact factor: 3.528

8.  Evaluating and reducing the impact of white matter lesions on brain volume measurements.

Authors:  Marco Battaglini; Mark Jenkinson; Nicola De Stefano
Journal:  Hum Brain Mapp       Date:  2011-08-31       Impact factor: 5.038

9.  Dynamic contrast-enhanced T2-weighted MR imaging of recurrent malignant gliomas treated with thalidomide and carboplatin.

Authors:  S Cha; E A Knopp; G Johnson; A Litt; J Glass; M L Gruber; S Lu; D Zagzag
Journal:  AJNR Am J Neuroradiol       Date:  2000-05       Impact factor: 4.966

10.  Perfusion and diffusion MRI combined with ¹¹C-methionine PET in the preoperative evaluation of suspected adult low-grade gliomas.

Authors:  Shala Ghaderi Berntsson; Anna Falk; Irina Savitcheva; Andrea Godau; Maria Zetterling; Göran Hesselager; Irina Alafuzoff; Elna-Marie Larsson; Anja Smits
Journal:  J Neurooncol       Date:  2013-06-16       Impact factor: 4.130

View more
  27 in total

Review 1.  State-of-the-art MRI techniques in neuroradiology: principles, pitfalls, and clinical applications.

Authors:  Magalie Viallon; Victor Cuvinciuc; Benedicte Delattre; Laura Merlini; Isabelle Barnaure-Nachbar; Seema Toso-Patel; Minerva Becker; Karl-Olof Lovblad; Sven Haller
Journal:  Neuroradiology       Date:  2015-04-10       Impact factor: 2.804

2.  Reproducibility of dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI in the study of brain gliomas: a comparison of data obtained using different commercial software.

Authors:  Gian Marco Conte; Antonella Castellano; Luisa Altabella; Antonella Iadanza; Marcello Cadioli; Andrea Falini; Nicoletta Anzalone
Journal:  Radiol Med       Date:  2017-01-09       Impact factor: 3.469

3.  Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma.

Authors:  Na-Na Sun; Xiao-Lin Ge; Xi-Sheng Liu; Lu-Lu Xu
Journal:  Radiol Med       Date:  2019-10-11       Impact factor: 3.469

4.  Glioma grading by dynamic susceptibility contrast perfusion and 11C-methionine positron emission tomography using different regions of interest.

Authors:  Cornelia Brendle; Johann-Martin Hempel; Jens Schittenhelm; Marco Skardelly; Gerald Reischl; Benjamin Bender; Ulrike Ernemann; Christian la Fougère; Uwe Klose
Journal:  Neuroradiology       Date:  2018-02-20       Impact factor: 2.804

5.  Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading.

Authors:  Rongli Wu; Yoshiyuki Watanabe; Atsuko Arisawa; Hiroto Takahashi; Hisashi Tanaka; Yasunori Fujimoto; Tadashi Watabe; Kayako Isohashi; Jun Hatazawa; Noriyuki Tomiyama
Journal:  Jpn J Radiol       Date:  2017-09-06       Impact factor: 2.374

Review 6.  Discrimination between Glioma Grades II and III Using Dynamic Susceptibility Perfusion MRI: A Meta-Analysis.

Authors:  Anna F Delgado; Alberto F Delgado
Journal:  AJNR Am J Neuroradiol       Date:  2017-05-18       Impact factor: 3.825

7.  Impact of Software Modeling on the Accuracy of Perfusion MRI in Glioma.

Authors:  L S Hu; Z Kelm; P Korfiatis; A C Dueck; C Elrod; B M Ellingson; T J Kaufmann; J M Eschbacher; J P Karis; K Smith; P Nakaji; D Brinkman; D Pafundi; L C Baxter; B J Erickson
Journal:  AJNR Am J Neuroradiol       Date:  2015-09-10       Impact factor: 3.825

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

Authors:  Jitender Saini; Pradeep Kumar Gupta; Prativa Sahoo; Anup Singh; Rana Patir; Suneeta Ahlawat; Manish Beniwal; K Thennarasu; Vani Santosh; Rakesh Kumar Gupta
Journal:  Neuroradiology       Date:  2017-10-31       Impact factor: 2.804

Review 9.  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

10.  Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology.

Authors:  Zezhong Ye; Richard L Price; Xiran Liu; Joshua Lin; Qingsong Yang; Peng Sun; Anthony T Wu; Liang Wang; Rowland H Han; Chunyu Song; Ruimeng Yang; Sam E Gary; Diane D Mao; Michael Wallendorf; Jian L Campian; Jr-Shin Li; Sonika Dahiya; Albert H Kim; Sheng-Kwei Song
Journal:  Clin Cancer Res       Date:  2020-07-21       Impact factor: 12.531

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.