Literature DB >> 26843012

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

J Khalifa1,2, F Tensaouti3, L Chaltiel4, J-A Lotterie3,5, I Catalaa3,6, M P Sunyach7, D Ibarrola8, G Noël9, G Truc10, P Walker11, N Magné12, M Charissoux13, S Ken3,14, P Peran3,15, I Berry3,5,15, E Cohen-Jonathan Moyal16,17,18, A Laprie3,16,17.   

Abstract

OBJECTIVE: To identify relevant relative cerebral blood volume biomarkers from T2* dynamic-susceptibility contrast magnetic resonance imaging to anticipate glioblastoma progression after chemoradiation.
METHODS: Twenty-five patients from a prospective study with glioblastoma, primarily treated by chemoradiation, were included. According to the last follow-up MRI confirmed status, patients were divided into: relapse group (n = 13) and control group (n = 12). The time of last MR acquisition was tend; MR acquisitions performed at tend-2M, tend-4M and tend-6M (respectively 2, 4 and 6 months before tend) were analyzed to extract relevant variations among eleven perfusion biomarkers (B). These variations were assessed through R(B), as the absolute value of the ratio between ∆B from tend-4M to tend-2M and ∆B from tend-6M to tend-4M. The optimal cut-off for R(B) was determined using receiver-operating-characteristic curve analysis.
RESULTS: The fraction of hypoperfused tumor volume (F_hPg) was a relevant biomarker. A ratio R(F_hPg) ≥ 0.61 would have been able to anticipate relapse at the next follow-up with a sensitivity/specificity/accuracy of 92.3 %/63.6 %/79.2 %. High R(F_hPg) (≥0.61) was associated with more relapse at tend compared to low R(F_hPg) (75 % vs 12.5 %, p = 0.008).
CONCLUSION: Iterative analysis of F_hPg from consecutive examinations could provide surrogate markers to predict progression at the next follow-up. KEY POINTS: • Related rCBV biomarkers from DSC were assessed to anticipate GBM progression. • Biomarkers were assessed through their patterns of variation during the follow-up. • The fraction of hypoperfused tumour volume (F_hP g ) seemed to be a relevant biomarker. • An innovative ratio R(F_hP g ) could be an early surrogate marker of relapse. • A significant time gain could be achieved in the management of GBM patients.

Entities:  

Keywords:  Biomarker; Glioblastoma; Perfusion weighted magnetic resonance imaging; Radiotherapy; rCBV

Mesh:

Substances:

Year:  2016        PMID: 26843012     DOI: 10.1007/s00330-016-4234-5

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  47 in total

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Authors:  Hee Ho Chu; Seung Hong Choi; Inseon Ryoo; Soo Chin Kim; Jeong A Yeom; Hwaseon Shin; Seung Chai Jung; A Leum Lee; Tae Jin Yoon; Tae Min Kim; Se-Hoon Lee; Chul-Kee Park; Ji-Hoon Kim; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim
Journal:  Radiology       Date:  2013-10-28       Impact factor: 11.105

2.  Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumab treatment.

Authors:  Whitney B Pope; Hyun J Kim; Jing Huo; Jeffry Alger; Matthew S Brown; David Gjertson; Victor Sai; Jonathan R Young; Leena Tekchandani; Timothy Cloughesy; Paul S Mischel; Albert Lai; Phioanh Nghiemphu; Syed Rahmanuddin; Jonathan Goldin
Journal:  Radiology       Date:  2009-07       Impact factor: 11.105

3.  Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations.

Authors:  C R Meyer; J L Boes; B Kim; P H Bland; K R Zasadny; P V Kison; K Koral; K A Frey; R L Wahl
Journal:  Med Image Anal       Date:  1997-04       Impact factor: 8.545

4.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis.

Authors:  L Ostergaard; R M Weisskoff; D A Chesler; C Gyldensted; B R Rosen
Journal:  Magn Reson Med       Date:  1996-11       Impact factor: 4.668

5.  Magnetic resonance imaging at 3.0 tesla detects more lesions in acute optic neuritis than at 1.5 tesla.

Authors:  Kirsten Nielsen; Egill Rostrup; Jette L Frederiksen; Stine Knudsen; Henrik K Mathiesen; Lars G Hanson; Olaf B Paulson
Journal:  Invest Radiol       Date:  2006-02       Impact factor: 6.016

6.  Brain tumors: full- and half-dose contrast-enhanced MR imaging at 3.0 T compared with 1.5 T--Initial Experience.

Authors:  Carsten Krautmacher; Winfried A Willinek; Henriette J Tschampa; Mark Born; Frank Träber; Jürgen Gieseke; Hans J Textor; Hans H Schild; Christiane K Kuhl
Journal:  Radiology       Date:  2005-10-19       Impact factor: 11.105

7.  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

8.  Pretreatment ADC histogram analysis is a predictive imaging biomarker for bevacizumab treatment but not chemotherapy in recurrent glioblastoma.

Authors:  B M Ellingson; S Sahebjam; H J Kim; W B Pope; R J Harris; D C Woodworth; A Lai; P L Nghiemphu; W P Mason; T F Cloughesy
Journal:  AJNR Am J Neuroradiol       Date:  2013-10-17       Impact factor: 3.825

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.  Multimodality therapy approaches, local and systemic treatment, compared with chemotherapy alone in recurrent glioblastoma.

Authors:  Marta Scorsetti; Pierina Navarria; Federico Pessina; Anna Maria Ascolese; Giuseppe D'Agostino; Stefano Tomatis; Fiorenza De Rose; Elisa Villa; Giulia Maggi; Matteo Simonelli; Elena Clerici; Riccardo Soffietti; Armando Santoro; Luca Cozzi; Lorenzo Bello
Journal:  BMC Cancer       Date:  2015-06-30       Impact factor: 4.430

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  7 in total

1.  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

2.  Pre- and early postoperative GFAP serum levels in glioma and brain metastases.

Authors:  Peter Baumgarten; Johanna Quick-Weller; Florian Gessler; Marlies Wagner; Julia Tichy; Marie-Therese Forster; Christian Foerch; Volker Seifert; Michel Mittelbronn; Christian Senft
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3.  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

4.  Response Assessment in Neuro-Oncology criteria, contrast enhancement and perfusion MRI for assessing progression in glioblastoma.

Authors:  Fatima Tensaouti; Jonathan Khalifa; Amélie Lusque; Benjamin Plas; Jean Albert Lotterie; Isabelle Berry; Anne Laprie; Elizabeth Cohen-Jonathan Moyal; Vincent Lubrano
Journal:  Neuroradiology       Date:  2017-08-25       Impact factor: 2.804

5.  Spatial discrimination of glioblastoma and treatment effect with histologically-validated perfusion and diffusion magnetic resonance imaging metrics.

Authors:  Melissa A Prah; Mona M Al-Gizawiy; Wade M Mueller; Elizabeth J Cochran; Raymond G Hoffmann; Jennifer M Connelly; Kathleen M Schmainda
Journal:  J Neurooncol       Date:  2017-09-12       Impact factor: 4.130

6.  Magnetic Resonance Imaging Parameters and Their Impact on Survival of Patients with Glioblastoma: Tumor Perfusion Predicts Survival.

Authors:  Bob L Hou; Sijin Wen; Gennadiy A Katsevman; Hui Liu; Ogaga Urhie; Ryan C Turner; Jeffrey Carpenter; Sanjay Bhatia
Journal:  World Neurosurg       Date:  2018-12-27       Impact factor: 2.104

7.  Classifying Glioblastoma Multiforme Follow-Up Progressive vs. Responsive Forms Using Multi-Parametric MRI Features.

Authors:  Adrian Ion-Mărgineanu; Sofie Van Cauter; Diana M Sima; Frederik Maes; Stefan Sunaert; Uwe Himmelreich; Sabine Van Huffel
Journal:  Front Neurosci       Date:  2017-01-11       Impact factor: 4.677

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