Literature DB >> 26275367

Dynamic contrast enhanced T1 MRI perfusion differentiates pseudoprogression from recurrent glioblastoma.

Alissa A Thomas1, Julio Arevalo-Perez2, Thomas Kaley1,3, John Lyo2,3, Kyung K Peck4, Weiji Shi5, Zhigang Zhang5, Robert J Young6,7.   

Abstract

Pseudoprogression may present as transient new or increasing enhancing lesions that mimic recurrent tumors in treated glioblastoma. The purpose of this study was to examine the utility of dynamic contrast enhanced T1 magnetic resonance imaging (DCE MRI) in differentiating between pseudoprogression and tumor progression and devise a cut-off value sensitive for pseudoprogression. We retrospectively examined 37 patients with glioblastoma treated with radiation and temozolomide after surgical resection that then developed new or increasing enhancing lesion(s) indeterminate for pseudoprogression versus progression. Volumetric plasma volume (Vp) and time-dependent leakage constant (Ktrans) maps were measured for the enhancing lesion and the mean and ninetieth percentile histogram values recorded. Lesion outcome was determined by clinical follow up with pseudoprogression defined as stable disease not requiring new treatment. Statistical analysis was performed with Wilcoxon rank-sum tests. Patients with pseudoprogression (n = 13) had Vp (mean) = 2.4 and Vp (90 %tile) = 3.2; and Ktrans (mean) = 3.5 and Ktrans (90 %tile) = 4.2. Patients with tumor progression (n = 24) had Vp (mean) = 5.3 and Vp (90 %tile) = 6.6; and Ktrans (mean) = 7.4 and Ktrans (90 %tile) = 9.1. Compared with tumor progression, pseudoprogression demonstrated lower Vp perfusion values (p = 0.0002) with a Vp (mean) cutoff <3.7 yielding 85% sensitivity and 79% specificity for pseudoprogression. Ktrans (mean) of >3.6 had a 69% sensitivity and 79% specificity for disease progression. DCE MRI shows lower plasma volume and time dependent leakage constant values in pseudoprogression than in tumor progression. A cut-off value with high sensitivity for pseudoprogression can be applied to aid in interpretation of DCE MRI.

Entities:  

Keywords:  DCE MRI; Glioblastoma; Perfusion; Pseudoprogression

Mesh:

Substances:

Year:  2015        PMID: 26275367      PMCID: PMC4726629          DOI: 10.1007/s11060-015-1893-z

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  23 in total

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Journal:  J Clin Oncol       Date:  2010-03-15       Impact factor: 44.544

2.  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
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Review 3.  Neurologic complications of radiation.

Authors:  Lisa R Rogers
Journal:  Continuum (Minneap Minn)       Date:  2012-04

4.  Glioma: Application of histogram analysis of pharmacokinetic parameters from T1-weighted dynamic contrast-enhanced MR imaging to tumor grading.

Authors:  S C Jung; J A Yeom; J-H Kim; I Ryoo; S C Kim; H Shin; A L Lee; T J Yun; C-K Park; C-H Sohn; S-H Park; S H Choi
Journal:  AJNR Am J Neuroradiol       Date:  2014-01-02       Impact factor: 3.825

5.  Longitudinal DSC-MRI for Distinguishing Tumor Recurrence From Pseudoprogression in Patients With a High-grade Glioma.

Authors:  Jerrold L Boxerman; Benjamin M Ellingson; Suriya Jeyapalan; Heinrich Elinzano; Robert J Harris; Jeffrey M Rogg; Whitney B Pope; Howard Safran
Journal:  Am J Clin Oncol       Date:  2017-06       Impact factor: 2.339

6.  MGMT promoter methylation status can predict the incidence and outcome of pseudoprogression after concomitant radiochemotherapy in newly diagnosed glioblastoma patients.

Authors:  Alba A Brandes; Enrico Franceschi; Alicia Tosoni; Valeria Blatt; Annalisa Pession; Giovanni Tallini; Roberta Bertorelle; Stefania Bartolini; Fabio Calbucci; Alvaro Andreoli; Giampiero Frezza; Marco Leonardi; Federica Spagnolli; Mario Ermani
Journal:  J Clin Oncol       Date:  2008-05-01       Impact factor: 44.544

7.  Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging.

Authors:  H R Arvinda; C Kesavadas; P S Sarma; B Thomas; V V Radhakrishnan; A K Gupta; T R Kapilamoorthy; S Nair
Journal:  J Neurooncol       Date:  2009-02-20       Impact factor: 4.130

Review 8.  Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols.

Authors:  P S Tofts; G Brix; D L Buckley; J L Evelhoch; E Henderson; M V Knopp; H B Larsson; T Y Lee; N A Mayr; G J Parker; R E Port; J Taylor; R M Weisskoff
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9.  True progression versus pseudoprogression in the treatment of glioblastomas: a comparison study of normalized cerebral blood volume and apparent diffusion coefficient by histogram analysis.

Authors:  Yong Sub Song; Seung Hong Choi; Chul-Kee Park; Kyung Sik Yi; Woong Jae Lee; Tae Jin Yun; Tae Min Kim; Se-Hoon Lee; Ji-Hoon Kim; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim; Geon-Ho Jahng; Kee-Hyun Chang
Journal:  Korean J Radiol       Date:  2013-07-17       Impact factor: 3.500

10.  Treatment-related brain tumor imaging changes: So-called "pseudoprogression" vs. tumor progression: Review and future research opportunities.

Authors:  Diem Kieu Thi Tran; Randy L Jensen
Journal:  Surg Neurol Int       Date:  2013-04-17
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  45 in total

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Journal:  Curr Treat Options Neurol       Date:  2017-03       Impact factor: 3.598

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4.  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.

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5.  Comparison of Dynamic Contrast-Enhancement Parameters between Gadobutrol and Gadoterate Meglumine in Posttreatment Glioma: A Prospective Intraindividual Study.

Authors:  J E Park; J Y Kim; H S Kim; W H Shim
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Review 6.  MR perfusion-weighted imaging in the evaluation of high-grade gliomas after treatment: a systematic review and meta-analysis.

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7.  High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients.

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8.  T1-Weighted Dynamic Contrast-Enhanced MR Perfusion Imaging Characterizes Tumor Response to Radiation Therapy in Chordoma.

Authors:  P Santos; K K Peck; J Arevalo-Perez; S Karimi; E Lis; Y Yamada; A I Holodny; J Lyo
Journal:  AJNR Am J Neuroradiol       Date:  2017-09-14       Impact factor: 3.825

Review 9.  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

10.  Joint arterial input function and tracer kinetic parameter estimation from undersampled dynamic contrast-enhanced MRI using a model consistency constraint.

Authors:  Yi Guo; Sajan Goud Lingala; Yannick Bliesener; R Marc Lebel; Yinghua Zhu; Krishna S Nayak
Journal:  Magn Reson Med       Date:  2017-09-14       Impact factor: 4.668

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