Literature DB >> 27502603

Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation?

Jonathan Khalifa1,2, Fatima Tensaouti3, Jean-Albert Lotterie3,4, Isabelle Catalaa3,5, Leonor Chaltiel6, Alexandra Benouaich-Amiel7, Carlos Gomez-Roca8, Georges Noël9, Gilles Truc10, Patrice Péran3,11, Isabelle Berry3,4,11, Marie-Pierre Sunyach12, Marie Charissoux13, Corinne Johnson14, Elizabeth Cohen-Jonathan Moyal15,16,17, Anne Laprie3,15,16.   

Abstract

To assess the value of T2* dynamic-susceptibility contrast MRI (DSC-MRI) and diffusion-weighted imaging (DWI) to predict the glioblastoma relapse sites after chemoradiation. From a cohort of 44 patients, primarily treated with radiotherapy (60 Gy) and concomitant temozolomide for glioblastoma, who were included in the reference arm of a prospective clinical trial (NCT01507506), 15 patients relapsed and their imaging data were analyzed. All patients underwent anatomical MRI, DSC-MRI and DWI before radiotherapy and every 2 months thereafter until relapse. Voxels within the sites of relapse were correlated with their perfusion and/or diffusion abnormality (PDA) pretreatment status after rigid co-registration. The relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were used as biomarkers. Several PDA areas were thresholded: hyperperfused voxels using a 1.75 fixed rCBV threshold (HPt); hypoperfused (hPg) and hyperperfused (HPg) voxels using a histogram-based Gaussian method; diffusion-restricted voxels (DRg); and HPg voxels with diffusion restriction (HPg&amp;DRg). Two sets of voxels (2,459,483 and 2,073,880) were analyzed according to these thresholding methods. Positive predictive values (PPV) of PDA voxels were low (between 9.5 and 31.9 %). The best PPV was obtained with HPg&amp;DRg voxels within the FLAIR hyperintensity, as 18.3 % of voxels without initial PDA were within relapse sites, versus 31.9 % with initial PDA (p < 0.0001). This prospective study suggests that DSC and/or DWI-MRI do not predict the glioblastoma relapse sites. However, further investigations with new methodological approaches are needed to better understand the role of these modalities in the prediction of glioblastoma relapse sites.

Entities:  

Keywords:  Diffusion weighted magnetic resonance imaging; Glioblastoma; Perfusion weighted magnetic resonance imaging; Sites of relapse; Voxel-based quantification

Mesh:

Year:  2016        PMID: 27502603     DOI: 10.1007/s11060-016-2232-8

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


  52 in total

1.  Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas.

Authors:  T Sugahara; Y Korogi; M Kochi; I Ikushima; Y Shigematu; T Hirai; T Okuda; L Liang; Y Ge; Y Komohara; Y Ushio; M Takahashi
Journal:  J Magn Reson Imaging       Date:  1999-01       Impact factor: 4.813

2.  Evaluation of peritumoral edema in the delineation of radiotherapy clinical target volumes for glioblastoma.

Authors:  Eric L Chang; Serap Akyurek; Tedde Avalos; Neal Rebueno; Chris Spicer; John Garcia; Robin Famiglietti; Pamela K Allen; K S Clifford Chao; Anita Mahajan; Shiao Y Woo; Moshe H Maor
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-02-15       Impact factor: 7.038

3.  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

4.  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

5.  Evaluation of pre-radiotherapy apparent diffusion coefficient (ADC): patterns of recurrence and survival outcomes analysis in patients treated for glioblastoma multiforme.

Authors:  Andrew Elson; Eric Paulson; Joseph Bovi; Malika Siker; Chris Schultz; Peter S Laviolette
Journal:  J Neurooncol       Date:  2015-04-17       Impact factor: 4.130

6.  Perfusion, diffusion and spectroscopy values in newly diagnosed cerebral gliomas.

Authors:  Isabelle Catalaa; Roland Henry; William P Dillon; Edward E Graves; Tracy R McKnight; Ying Lu; Daniel B Vigneron; Sarah J Nelson
Journal:  NMR Biomed       Date:  2006-06       Impact factor: 4.044

7.  Malignant supratentorial astrocytoma treated with postoperative radiation therapy: prognostic value of pretreatment quantitative diffusion-weighted MR imaging.

Authors:  Ryuji Murakami; Takeshi Sugahara; Hideo Nakamura; Toshinori Hirai; Mika Kitajima; Yoshiko Hayashida; Yuji Baba; Natsuo Oya; Jun-Ichi Kuratsu; Yasuyuki Yamashita
Journal:  Radiology       Date:  2007-03-13       Impact factor: 11.105

8.  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

9.  Evaluation of the lactate-to-N-acetyl-aspartate ratio defined with magnetic resonance spectroscopic imaging before radiation therapy as a new predictive marker of the site of relapse in patients with glioblastoma multiforme.

Authors:  Alexandra Deviers; Soléakhéna Ken; Thomas Filleron; Benjamin Rowland; Andrea Laruelo; Isabelle Catalaa; Vincent Lubrano; Pierre Celsis; Isabelle Berry; Giovanni Mogicato; Elizabeth Cohen-Jonathan Moyal; Anne Laprie
Journal:  Int J Radiat Oncol Biol Phys       Date:  2014-08-04       Impact factor: 7.038

10.  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

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  6 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.  High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques.

Authors:  Otto M Henriksen; María Del Mar Álvarez-Torres; Patricia Figueiredo; Gilbert Hangel; Vera C Keil; Ruben E Nechifor; Frank Riemer; Kathleen M Schmainda; Esther A H Warnert; Evita C Wiegers; Thomas C Booth
Journal:  Front Oncol       Date:  2022-03-03       Impact factor: 5.738

3.  Feasibility of multi-parametric PET and MRI for prediction of tumour recurrence in patients with glioblastoma.

Authors:  Michael Lundemann; Per Munck Af Rosenschöld; Aida Muhic; Vibeke A Larsen; Hans S Poulsen; Svend-Aage Engelholm; Flemming L Andersen; Andreas Kjær; Henrik B W Larsson; Ian Law; Adam E Hansen
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-10-02       Impact factor: 9.236

4.  Pseudoprogression of brain tumors.

Authors:  Stefanie C Thust; Martin J van den Bent; Marion Smits
Journal:  J Magn Reson Imaging       Date:  2018-05-07       Impact factor: 4.813

5.  Meta-analysis of the diagnostic performance of diffusion magnetic resonance imaging with apparent diffusion coefficient measurements for differentiating glioma recurrence from pseudoprogression.

Authors:  Yang Yu; Yue Ma; Mengyao Sun; Wenyan Jiang; Tingting Yuan; Dan Tong
Journal:  Medicine (Baltimore)       Date:  2020-06-05       Impact factor: 1.817

6.  Whole brain apparent diffusion coefficient measurements correlate with survival in glioblastoma patients.

Authors:  Aaron Michael Rulseh; Josef Vymazal
Journal:  J Neurooncol       Date:  2019-12-03       Impact factor: 4.130

  6 in total

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