Literature DB >> 24675671

Parametric response maps of perfusion MRI may identify recurrent glioblastomas responsive to bevacizumab and irinotecan.

Domenico Aquino1, Anna Luisa Di Stefano2, Alessandro Scotti1, Lucia Cuppini3, Elena Anghileri3, Gaetano Finocchiaro3, Maria Grazia Bruzzone1, Marica Eoli3.   

Abstract

BACKGROUND: Perfusion weighted imaging (PWI) can be used to measure key aspects of tumor vascularity in vivo and recent studies suggest that perfusion imaging may be useful in the early assessment of response to angiogenesis inhibitors. Aim of this work is to compare Parametric Response Maps (PRMs) with the Region Of Interest (ROI) approach in the analysis of tumor changes induced by bevacizumab and irinotecan in recurrent glioblastomas (rGBM), and to evaluate if changes in tumor blood volume measured by perfusion MRI may predict clinical outcome.
METHODS: 42 rGBM patients with KPS ≥ 50 were treated until progression, as defined by MRI with RANO criteria. Relative cerebral blood volume (rCBV) variation after 8 weeks of treatment was calculated through semi-automatic ROI placement in the same anatomic region as in baseline. Alternatively, rCBV variations with respect to baseline were calculated into the evolving tumor region using a voxel-by-voxel difference. PRMs were created showing where rCBV significantly increased, decreased or remained unchanged.
RESULTS: An increased blood volume in PRM (PRMCBV+) higher than 18% (first quartile) after 8 weeks of treatment was associated with increased progression free survival (PFS; 24 versus 13 weeks, p = 0.045) and overall survival (OS; 38 versus 25 weeks, p = 0.016). After 8 weeks of treatment ROI analysis showed that mean rCBV remained elevated in non responsive patients (4.8 ± 0.9 versus 5.1 ± 1.2, p = 0.38), whereas decreased in responsive patients (4.2 ± 1.3 versus 3.8 ± 1.6 p = 0.04), and re-increased progressively when patients approached tumor progression.
CONCLUSIONS: Our data suggest that PRMs can provide an early marker of response to antiangiogenic treatment and warrant further confirmation in a larger cohort of GBM patients.

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Year:  2014        PMID: 24675671      PMCID: PMC3968002          DOI: 10.1371/journal.pone.0090535

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  33 in total

1.  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

2.  Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma.

Authors:  Christina Tsien; Craig J Galbán; Thomas L Chenevert; Timothy D Johnson; Daniel A Hamstra; Pia C Sundgren; Larry Junck; Charles R Meyer; Alnawaz Rehemtulla; Theodore Lawrence; Brian D Ross
Journal:  J Clin Oncol       Date:  2010-04-05       Impact factor: 44.544

3.  Glioblastoma: a method for predicting response to antiangiogenic chemotherapy by using MR perfusion imaging--pilot study.

Authors:  Rahul N Sawlani; Jeffrey Raizer; Sandra W Horowitz; Wanyong Shin; Sean A Grimm; James P Chandler; Robert Levy; Christopher Getch; Timothy J Carroll
Journal:  Radiology       Date:  2010-05       Impact factor: 11.105

4.  Enhancing fraction in glioma and its relationship to the tumoral vascular microenvironment: A dynamic contrast-enhanced MR imaging study.

Authors:  S J Mills; C Soh; J P B O'Connor; C J Rose; G Buonaccorsi; S Cheung; S Zhao; G J M Parker; A Jackson
Journal:  AJNR Am J Neuroradiol       Date:  2009-12-17       Impact factor: 3.825

5.  Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging.

Authors:  Meng Law; Robert J Young; James S Babb; Nicole Peccerelli; Sophie Chheang; Michael L Gruber; Douglas C Miller; John G Golfinos; David Zagzag; Glyn Johnson
Journal:  Radiology       Date:  2008-03-18       Impact factor: 11.105

6.  Expression of CD109 in human cancer.

Authors:  Mizuo Hashimoto; Masatoshi Ichihara; Tsuyoshi Watanabe; Kumi Kawai; Katsumi Koshikawa; Norihiro Yuasa; Takashi Takahashi; Yasushi Yatabe; Yoshiki Murakumo; Jing-Min Zhang; Yuji Nimura; Masahide Takahashi
Journal:  Oncogene       Date:  2004-04-29       Impact factor: 9.867

7.  Improved tumor oxygenation and survival in glioblastoma patients who show increased blood perfusion after cediranib and chemoradiation.

Authors:  Tracy T Batchelor; Elizabeth R Gerstner; Kyrre E Emblem; Dan G Duda; Jayashree Kalpathy-Cramer; Matija Snuderl; Marek Ancukiewicz; Pavlina Polaskova; Marco C Pinho; Dominique Jennings; Scott R Plotkin; Andrew S Chi; April F Eichler; Jorg Dietrich; Fred H Hochberg; Christine Lu-Emerson; A John Iafrate; S Percy Ivy; Bruce R Rosen; Jay S Loeffler; Patrick Y Wen; A Greg Sorensen; Rakesh K Jain
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-04       Impact factor: 11.205

8.  Comparison of region-of-interest analysis with three different histogram analysis methods in the determination of perfusion metrics in patients with brain gliomas.

Authors:  Robert Young; James Babb; Meng Law; Erica Pollack; Glyn Johnson
Journal:  J Magn Reson Imaging       Date:  2007-10       Impact factor: 4.813

9.  The parametric response map is an imaging biomarker for early cancer treatment outcome.

Authors:  Craig J Galbán; Thomas L Chenevert; Charles R Meyer; Christina Tsien; Theodore S Lawrence; Daniel A Hamstra; Larry Junck; Pia C Sundgren; Timothy D Johnson; David J Ross; Alnawaz Rehemtulla; Brian D Ross
Journal:  Nat Med       Date:  2009-04-19       Impact factor: 53.440

10.  Histogram analysis versus region of interest analysis of dynamic susceptibility contrast perfusion MR imaging data in the grading of cerebral gliomas.

Authors:  M Law; R Young; J Babb; E Pollack; G Johnson
Journal:  AJNR Am J Neuroradiol       Date:  2007-04       Impact factor: 3.825

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  11 in total

1.  Early Biomarkers from Conventional and Delayed-Contrast MRI to Predict the Response to Bevacizumab in Recurrent High-Grade Gliomas.

Authors:  D Daniels; D Guez; D Last; C Hoffmann; D Nass; A Talianski; G Tsarfaty; S Salomon; A A Kanner; D T Blumenthal; F Bokstein; S Harnof; D Yekutieli; S Zamir; Z R Cohen; L Zach; Y Mardor
Journal:  AJNR Am J Neuroradiol       Date:  2016-07-07       Impact factor: 3.825

Review 2.  Perfusion MRI as the predictive/prognostic and pharmacodynamic biomarkers in recurrent malignant glioma treated with bevacizumab: a systematic review and a time-to-event meta-analysis.

Authors:  Sang Hyun Choi; Seung Chai Jung; Kyung Won Kim; Ja Youn Lee; Yoonseok Choi; Seong Ho Park; Ho Sung Kim
Journal:  J Neurooncol       Date:  2016-04-23       Impact factor: 4.130

3.  Lessons from anti-vascular endothelial growth factor and anti-vascular endothelial growth factor receptor trials in patients with glioblastoma.

Authors:  Christine Lu-Emerson; Dan G Duda; Kyrre E Emblem; Jennie W Taylor; Elizabeth R Gerstner; Jay S Loeffler; Tracy T Batchelor; Rakesh K Jain
Journal:  J Clin Oncol       Date:  2015-02-23       Impact factor: 44.544

4.  Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas.

Authors:  Jerrold L Boxerman; Chad C Quarles; Leland S Hu; Bradley J Erickson; Elizabeth R Gerstner; Marion Smits; Timothy J Kaufmann; Daniel P Barboriak; Raymond H Huang; Wolfgang Wick; Michael Weller; Evanthia Galanis; Jayashree Kalpathy-Cramer; Lalitha Shankar; Paula Jacobs; Caroline Chung; Martin J van den Bent; Susan Chang; W K Al Yung; Timothy F Cloughesy; Patrick Y Wen; Mark R Gilbert; Bruce R Rosen; Benjamin M Ellingson; Kathleen M Schmainda
Journal:  Neuro Oncol       Date:  2020-09-29       Impact factor: 12.300

5.  Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI.

Authors:  S Wang; M Martinez-Lage; Y Sakai; S Chawla; S G Kim; M Alonso-Basanta; R A Lustig; S Brem; S Mohan; R L Wolf; A Desai; H Poptani
Journal:  AJNR Am J Neuroradiol       Date:  2015-10-08       Impact factor: 3.825

6.  Assessment of early response to tumor-treating fields in newly diagnosed glioblastoma using physiologic and metabolic MRI: initial experience.

Authors:  Suyash Mohan; Sanjeev Chawla; Sumei Wang; Gaurav Verma; Aaron Skolnik; Steven Brem; Katherine B Peters; Harish Poptani
Journal:  CNS Oncol       Date:  2016-04-14

7.  Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis.

Authors:  R Kurokawa; A Baba; M Kurokawa; A Capizzano; O Hassan; T Johnson; Y Ota; J Kim; A Hagiwara; T Moritani; A Srinivasan
Journal:  AJNR Am J Neuroradiol       Date:  2022-01-20       Impact factor: 3.825

Review 8.  Emerging treatment strategies for glioblastoma multiforme.

Authors:  Steven K Carlsson; Shaun P Brothers; Claes Wahlestedt
Journal:  EMBO Mol Med       Date:  2014-11       Impact factor: 12.137

9.  Geometrical Measures Obtained from Pretreatment Postcontrast T1 Weighted MRIs Predict Survival Benefits from Bevacizumab in Glioblastoma Patients.

Authors:  David Molina; Julián Pérez-Beteta; Alicia Martínez-González; Juan M Sepúlveda; Sergi Peralta; Miguel J Gil-Gil; Gaspar Reynes; Ana Herrero; Ramón De Las Peñas; Raquel Luque; Jaume Capellades; Carmen Balaña; Víctor M Pérez-García
Journal:  PLoS One       Date:  2016-08-24       Impact factor: 3.240

Review 10.  MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives.

Authors:  Domenico Aquino; Andrea Gioppo; Gaetano Finocchiaro; Maria Grazia Bruzzone; Valeria Cuccarini
Journal:  J Immunol Res       Date:  2017-04-20       Impact factor: 4.818

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