Literature DB >> 25907688

Perfusion MRI in the Evaluation of Suspected Glioblastoma Recurrence.

Stella Blasel1, Andrea Zagorcic1, Alina Jurcoane1, Oliver Bähr2, Marlies Wagner1, Patrick N Harter3, Elke Hattingen1.   

Abstract

PURPOSE: Treatment-related changes (TRC) often imitate tumor progression in glioblastomas. Increased regional cerebral blood volume (rCBV) can differentiate tumor progression from TRC after the standardized first-line radiochemotherapy, but information about diagnostic accuracy of rCBV for patients without any clinical selection criteria is limited. Therefore, we aimed to evaluate if rCBV can differentiate between TRC and tumor progression irrespective of preceding therapies and number of tumor progressions.
METHODS: We analyzed mean and maximum rCBV from the enhancing areas normalized to the contralateral white matter in 44 pretreated glioblastomas with MR-morphological tumor progression. The diagnosis (real progression vs. TRC) was determined by histopathology or by clinical/MRI-follow-up. We performed nonparametric tests, receiver operating characteristics (ROC), and Kaplan-Meier analysis.
RESULTS: Significant differences between tumor progression (N = 37) and TRC (N = 7) were found for rCBVmean (2.44 ± 1.05 vs. 1.69 ± .56, P < .03) and rCBVmax (3.40 ± 1.25 vs. 2.21 ± .62, P < .0007). A rCBVmax of 2.6 had 78% sensitivity and 86% specificity to detect tumor progression. Neither rCBVmean nor rCBVmax was predictive for the patient overall survival (OS). There were no statistically different rCBVmean and rCBVmax between the first and further tumor progressions.
CONCLUSIONS: The rCBVmax differentiates tumor progression from TRC in unselected recurrent glioblastomas, but it is not predictive for the OS.
Copyright © 2015 by the American Society of Neuroimaging.

Entities:  

Keywords:  MR perfusion; glioblastoma; rCBV; treatment-related changes; tumor progression

Mesh:

Year:  2015        PMID: 25907688     DOI: 10.1111/jon.12247

Source DB:  PubMed          Journal:  J Neuroimaging        ISSN: 1051-2284            Impact factor:   2.486


  10 in total

Review 1.  The Role of Standard and Advanced Imaging for the Management of Brain Malignancies From a Radiation Oncology Standpoint.

Authors:  Robert H Press; Jim Zhong; Saumya S Gurbani; Brent D Weinberg; Bree R Eaton; Hyunsuk Shim; Hui-Kuo G Shu
Journal:  Neurosurgery       Date:  2019-08-01       Impact factor: 4.654

Review 2.  Conventional and advanced imaging throughout the cycle of care of gliomas.

Authors:  Gilles Reuter; Martin Moïse; Wolfgang Roll; Didier Martin; Arnaud Lombard; Félix Scholtes; Walter Stummer; Eric Suero Molina
Journal:  Neurosurg Rev       Date:  2021-01-07       Impact factor: 3.042

Review 3.  Response Assessment in Neuro-Oncology Criteria for Gliomas: Practical Approach Using Conventional and Advanced Techniques.

Authors:  D J Leao; P G Craig; L F Godoy; C C Leite; B Policeni
Journal:  AJNR Am J Neuroradiol       Date:  2019-12-19       Impact factor: 3.825

Review 4.  Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature.

Authors:  N Soni; M Ora; N Mohindra; Y Menda; G Bathla
Journal:  AJNR Am J Neuroradiol       Date:  2020-08-27       Impact factor: 3.825

Review 5.  Conventional and advanced magnetic resonance imaging in patients with high-grade glioma.

Authors:  Whitney B Pope; Garth Brandal
Journal:  Q J Nucl Med Mol Imaging       Date:  2018-04-26       Impact factor: 2.346

6.  Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation.

Authors:  J Khalifa; F Tensaouti; L Chaltiel; J-A Lotterie; I Catalaa; M P Sunyach; D Ibarrola; G Noël; G Truc; P Walker; N Magné; M Charissoux; S Ken; P Peran; I Berry; E Cohen-Jonathan Moyal; A Laprie
Journal:  Eur Radiol       Date:  2016-02-02       Impact factor: 5.315

7.  The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: A meta-analysis.

Authors:  Bing Wan; Siqi Wang; Mengqi Tu; Bo Wu; Ping Han; Haibo Xu
Journal:  Medicine (Baltimore)       Date:  2017-03       Impact factor: 1.889

Review 8.  Diagnostic performance of DSC perfusion MRI to distinguish tumor progression and treatment-related changes: a systematic review and meta-analysis.

Authors:  Rongwei Fu; Laszlo Szidonya; Ramon F Barajas; Prakash Ambady; Csanad Varallyay; Edward A Neuwelt
Journal:  Neurooncol Adv       Date:  2022-03-01

Review 9.  [Current Applications and Future Perspectives of Brain Tumor Imaging].

Authors:  Ji Eun Park; Ho Sung Kim
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2020-05-29

10.  Sequential implementation of DSC-MR perfusion and dynamic [18F]FET PET allows efficient differentiation of glioma progression from treatment-related changes.

Authors:  Eike Steidl; Karl-Josef Langen; Sarah Abu Hmeidan; Nenad Polomac; Christian P Filss; Norbert Galldiks; Philipp Lohmann; Fee Keil; Katharina Filipski; Felix M Mottaghy; Nadim Jon Shah; Joachim P Steinbach; Elke Hattingen; Gabriele D Maurer
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-11-26       Impact factor: 9.236

  10 in total

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