Literature DB >> 31727756

Prognostic Predictions for Patients with Glioblastoma after Standard Treatment: Application of Contrast Leakage Information from DSC-MRI within Nonenhancing FLAIR High-Signal-Intensity Lesions.

S H Kim1, K H Cho1, S H Choi2,3,4, T M Kim5, C K Park6, S H Park7, J K Won7, I H Kim8, S T Lee9.   

Abstract

BACKGROUND AND
PURPOSE: Attempts have been made to quantify the microvascular leakiness of glioblastomas and use it as an imaging biomarker to predict the prognosis of the tumor. The purpose of our study was to evaluate whether the extraction fraction value from DSC-MR imaging within nonenhancing FLAIR hyperintense lesions was a better prognostic imaging biomarker than dynamic contrast-enhanced MR imaging parameters for patients with glioblastoma.
MATERIALS AND METHODS: A total of 102 patients with glioblastoma who received a preoperative dynamic contrast-enhanced MR imaging and DSC-MR imaging were included in this retrospective study. Patients were classified into the progression (n = 87) or nonprogression (n = 15) groups at 24 months after surgery. We extracted the means and 95th percentile values for the contrast leakage information parameters from both modalities within the nonenhancing FLAIR high-signal-intensity lesions.
RESULTS: The extraction fraction 95th percentile value was higher in the progression-free survival group of >24 months than at ≤24 months. The median progression-free survival of the group with an extraction fraction 95th percentile value of >13.32 was 17 months, whereas that of the group of ≤13.32 was 12 months. In addition, it was an independent predictor variable for progression-free survival in the patients regardless of their ages and genetic information.
CONCLUSIONS: The extraction fraction 95th percentile value was the only independent parameter for prognostic prediction in patients with glioblastoma among the contrast leakage information, which has no statistically significant correlations with the DCE-MR imaging parameters.
© 2019 by American Journal of Neuroradiology.

Entities:  

Year:  2019        PMID: 31727756      PMCID: PMC6975364          DOI: 10.3174/ajnr.A6297

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  43 in total

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Authors:  Josien P W Pluim; J B Antoine Maintz; Max A Viergever
Journal:  IEEE Trans Med Imaging       Date:  2003-08       Impact factor: 10.048

Review 2.  DNA alkylation by the haloethylnitrosoureas: nature of modifications produced and their enzymatic repair or removal.

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3.  Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group.

Authors:  Patrick Y Wen; David R Macdonald; David A Reardon; Timothy F Cloughesy; A Gregory Sorensen; Evanthia Galanis; John Degroot; Wolfgang Wick; Mark R Gilbert; Andrew B Lassman; Christina Tsien; Tom Mikkelsen; Eric T Wong; Marc C Chamberlain; Roger Stupp; Kathleen R Lamborn; Michael A Vogelbaum; Martin J van den Bent; Susan M Chang
Journal:  J Clin Oncol       Date:  2010-03-15       Impact factor: 44.544

4.  New algorithm for quantifying vascular changes in dynamic contrast-enhanced MRI independent of absolute T1 values.

Authors:  E Mark Haacke; Cristina L Filleti; Ramtilak Gattu; Carlo Ciulla; Areen Al-Bashir; Krithivasan Suryanarayanan; Meng Li; Zahid Latif; Zach DelProposto; Vivek Sehgal; Tao Li; Vidya Torquato; Rajesh Kanaparti; Jing Jiang; Jaladhar Neelavalli
Journal:  Magn Reson Med       Date:  2007-09       Impact factor: 4.668

5.  Prognosis prediction of non-enhancing T2 high signal intensity lesions in glioblastoma patients after standard treatment: application of dynamic contrast-enhanced MR imaging.

Authors:  Rihyeon Kim; Seung Hong Choi; Tae Jin Yun; Soon-Tae Lee; Chul-Kee Park; Tae Min Kim; Ji-Hoon Kim; Sun-Won Park; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim
Journal:  Eur Radiol       Date:  2016-06-29       Impact factor: 5.315

6.  T(1)- and T(2)(*)-dominant extravasation correction in DSC-MRI: part II-predicting patient outcome after a single dose of cediranib in recurrent glioblastoma patients.

Authors:  Kyrre E Emblem; Atle Bjornerud; Kim Mouridsen; Ronald J H Borra; Tracy T Batchelor; Rakesh K Jain; A Gregory Sorensen
Journal:  J Cereb Blood Flow Metab       Date:  2011-04-20       Impact factor: 6.200

7.  Glioma Angiogenesis and Perfusion Imaging: Understanding the Relationship between Tumor Blood Volume and Leakiness with Increasing Glioma Grade.

Authors:  R Jain; B Griffith; F Alotaibi; D Zagzag; H Fine; J Golfinos; L Schultz
Journal:  AJNR Am J Neuroradiol       Date:  2015-07-23       Impact factor: 3.825

Review 8.  Multidrug resistance in brain tumors: roles of the blood-brain barrier.

Authors:  A Régina; M Demeule; A Laplante; J Jodoin; C Dagenais; F Berthelet; A Moghrabi; R Béliveau
Journal:  Cancer Metastasis Rev       Date:  2001       Impact factor: 9.264

Review 9.  The blood-brain barrier and cancer: transporters, treatment, and Trojan horses.

Authors:  John F Deeken; Wolfgang Löscher
Journal:  Clin Cancer Res       Date:  2007-03-15       Impact factor: 12.531

Review 10.  Assessment of blood-brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review.

Authors:  Anna K Heye; Ross D Culling; Maria Del C Valdés Hernández; Michael J Thrippleton; Joanna M Wardlaw
Journal:  Neuroimage Clin       Date:  2014-09-10       Impact factor: 4.881

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