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

Jonathan Khalifa, Fatima Tensaouti, Jean Albert Lotterie, Isabelle Catalaa, Leonor Chaltiel, Alexandra Benouaich-Amiel, Carlos Gomez-Roca, Georges Noël, Gilles Truc, Patrice Péran, Isabelle Berry, Marie Pierre Sunyach, Marie Charissoux, Corinne Johnson, Elizabeth Cohen-Jonathan Moyal, Anne Laprie

Research output: Contribution to journal › Article

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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&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&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.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalJournal of Neuro-Oncology
DOIs
Publication statusAccepted/In press - Aug 8 2016
Externally publishedYes

Fingerprint

Diffusion Magnetic Resonance Imaging
Glioblastoma
Perfusion
Recurrence
temozolomide
Radiotherapy
Biomarkers
Clinical Trials
Prospective Studies

Keywords

  • Diffusion weighted magnetic resonance imaging
  • Glioblastoma
  • Perfusion weighted magnetic resonance imaging
  • Sites of relapse
  • Voxel-based quantification

ASJC Scopus subject areas

  • Medicine(all)
  • Oncology
  • Neurology
  • Clinical Neurology
  • Cancer Research

Cite this

Khalifa, J., Tensaouti, F., Lotterie, J. A., Catalaa, I., Chaltiel, L., Benouaich-Amiel, A., ... Laprie, A. (Accepted/In press). Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation? Journal of Neuro-Oncology, 1-12. https://doi.org/10.1007/s11060-016-2232-8

Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation? / Khalifa, Jonathan; Tensaouti, Fatima; Lotterie, Jean Albert; Catalaa, Isabelle; Chaltiel, Leonor; Benouaich-Amiel, Alexandra; Gomez-Roca, Carlos; Noël, Georges; Truc, Gilles; Péran, Patrice; Berry, Isabelle; Sunyach, Marie Pierre; Charissoux, Marie; Johnson, Corinne; Cohen-Jonathan Moyal, Elizabeth; Laprie, Anne.

In: Journal of Neuro-Oncology, 08.08.2016, p. 1-12.

Research output: Contribution to journal › Article

Khalifa, J, Tensaouti, F, Lotterie, JA, Catalaa, I, Chaltiel, L, Benouaich-Amiel, A, Gomez-Roca, C, Noël, G, Truc, G, Péran, P, Berry, I, Sunyach, MP, Charissoux, M, Johnson, C, Cohen-Jonathan Moyal, E & Laprie, A 2016, 'Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation?', Journal of Neuro-Oncology, pp. 1-12. https://doi.org/10.1007/s11060-016-2232-8
Khalifa J, Tensaouti F, Lotterie JA, Catalaa I, Chaltiel L, Benouaich-Amiel A et al. Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation? Journal of Neuro-Oncology. 2016 Aug 8;1-12. https://doi.org/10.1007/s11060-016-2232-8
Khalifa, Jonathan ; Tensaouti, Fatima ; Lotterie, Jean Albert ; Catalaa, Isabelle ; Chaltiel, Leonor ; Benouaich-Amiel, Alexandra ; Gomez-Roca, Carlos ; Noël, Georges ; Truc, Gilles ; Péran, Patrice ; Berry, Isabelle ; Sunyach, Marie Pierre ; Charissoux, Marie ; Johnson, Corinne ; Cohen-Jonathan Moyal, Elizabeth ; Laprie, Anne. / Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation?. In: Journal of Neuro-Oncology. 2016 ; pp. 1-12.
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AU - Khalifa, Jonathan

AU - Tensaouti, Fatima

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AU - Chaltiel, Leonor

AU - Benouaich-Amiel, Alexandra

AU - Gomez-Roca, Carlos

AU - Noël, Georges

AU - Truc, Gilles

AU - Péran, Patrice

AU - Berry, Isabelle

AU - Sunyach, Marie Pierre

AU - Charissoux, Marie

AU - Johnson, Corinne

AU - Cohen-Jonathan Moyal, Elizabeth

AU - Laprie, Anne

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N2 - 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&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&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.

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