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“ Advanced MR imaging in diagnosis, treatment planning and therapy monitoring in gliomatous brain tumours : review of the literature ”. Sofie Van Cauter Uwe Himmelreich, Stefaan Van Gool, Stefan Sunaert. Advanced multimodal MRI in gliomas. Introduction Review of the l iterature
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“Advanced MR imaging in diagnosis, treatment planning and therapy monitoring in gliomatous brain tumours: review of the literature” Sofie Van Cauter Uwe Himmelreich, Stefaan Van Gool, Stefan Sunaert
Advancedmultimodal MRI in gliomas • Introduction • Review of the literature • Scope of our research Medical Imaging Research Center July 2010
Advancedmultimodal MRI in gliomas • Introduction • Review of the literature • Scope of our research Medical Imaging Research Center July 2010
1. Introduction Gliomas(arisefromneuroectodermalglialcells): 7/100 000/year Astrocytomas(pilocyticvs diffuse) Oligodendrogliomas Ependymomas Gangliogliomas Low grade (WHO gr I and II) High grade (WHO gr III and IV) Gr IV: glioblastomamultiforme (primary – secondary; 4/100 000/year) Treatment: “watchfullwaiting” (+ biopsy) <-> debulking , radiotherapy, chemotherapy newevolvingtherapies immune therapy, targetedtherapy,….. • Overall bad prognosis LGG: the 5-year survival rate 65-80%, the 10-year survival: 20-45% (heterogeneous group) GBM: overall survival 15 m, at the time of relapse 100% mortalityafter 1.5 y Medical Imaging Research Center July 2010
1. Introduction How to asses? NEUROIMAGING • Computedtomography • Magneticresonanceimaging • Positron emissiontomogrpahy • Single photon emission computed tomography • Diffuse opticalimaging • Event-relatedopticalsignal • Electroencephalography • Mangetoencephalography Radiology Nuclearmedecine Medical Imaging Research Center July 2010
1. Introduction Magneticresonanceimaging Anatomicalimagingtechniques Functionalimagingtechniques * T1 +/- contrast administration, T2, FLAIR * diffusionweightedimaging * diffusiontensorimaging, diffusionkurtosisimaging * perfusionweightedimaging (DCE) * MR spectroscopy * functional MR imaging Medical Imaging Research Center July 2010
1. Introduction Diffusionweightedimaging – Diffusiontensorimaging – Diffusionkurtosisimaging • - Brownianmolecular motion diffusion • In biological tissue, restriction of “mobility” due to tissue cellularity and cellmebraneintegrity • MR derived parameters: ADC, FA, MK, …….. + = Medical Imaging Research Center July 2010
1. Introduction Perfusionweightedimaging • Perfusion-weighted MRI is a non-invasiveimagingmethodforquantification of vascularproperties. • Dynamicsusceptibility contrast magneticresonanceimaging(DSC-MR) is acquiredbyrepetitiveimagingwith high temporal resolutionduring the injection of Gd-Based contrast agent • Derived parameters: rCBV, rCBF, MTT,….. Medical Imaging Research Center July 2010
1. Introduction MR spectroscopy • - Detection of mobile H containing metabolites. • MRS provides information regarding the composition and spatial distribution of cellular metabolites • Variable acquisition techniques: CSI, SV, long TE, short TE. Neuronal marker Membraneturnover Water signal Energy metabolism Medical Imaging Research Center July 2010
1. Introduction MR spectroscopy Different TE SV vs CSI Detection of pathology TE: 35ms TE:144 ms Medical Imaging Research Center July 2010
1. Introduction What to asses in brainneoplasmswithneuroimagingtechniques? - diagnosis • grading • progression / relapseaftertreatment • treatmenteffects Medical Imaging Research Center July 2010
Advancedmultimodal MRI in gliomas • Introduction • Review of the literature • Scope of our research Medical Imaging Research Center July 2010
2. Review of the literature 2.1 Advanced MRI in diagnosinggliomas “ Distinctionbetweenhigh-gradegliomas and solitary metastases usingperitumoral 3T magneticresonancespectroscopy, diffusion and perfusionimaging ” ChanChiang I. et al. Neuroradiology 2004 Medical Imaging Research Center July 2010
2. Review of the literature 2.1 Advanced MRI in diagnosinggliomas “ Distinctionbetweenhigh-gradegliomas and solitary metastases usingperitumoral 3T magneticresonancespectroscopy, diffusion and perfusionimagings ”, ChanChiang I. et al., Neuroradiology 2004 Medical Imaging Research Center July 2010
2. Review of the literature 2.1 Advanced MRI in diagnosinggliomas MR spectroscopy CSI, TE: 270 TR: 1500ms Perfusionweightedimaging rCBV map Diffusionweightedimaging “ Distinctionbetweenhigh-gradegliomas and solitary metastases usingperitumoral 3T magneticresonancespectroscopy, diffusion and perfusionimagings ”, ChanChiang I. et al., Neuroradiology 2004 ADC maps, TE: 100 ms TR: 12000ms, b-value: 1000 mm/s² Medical Imaging Research Center July 2010
2. Review of the literature 2.1 Advanced MRI in diagnosinggliomas Conclusion: Perfusion-weighted MRI, diffusionweighted MRI and MR spectroscopy (Cho/Cr) in the peritumoural regioncanbeused to demonstratedifferences in solitary metastases and high-gradegliomas. The intratumouralrCBV, Cho/Cr, NAA/Cr and peritumoural NAA/Cr do notdifferstatisticallyfromthoseseenwith metastases “ Distinctionbetweenhigh-gradegliomas and solitary metastases usingperitumoral 3T magneticresonancespectroscopy, diffusion and perfusionimagings ”, ChanChiang I. et al., Neuroradiology 2004 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas “ Cerebralgliomas: diffusionalkurtosisimaginganalysis of microstructuraldifferences” Raab P. et al. Neuroradiology 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas “ Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences”, Raab P. et al.; Neuroradiology 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas “The data demonstrate significant differences in MK values among gliomas of different WHO grades” “ Cerebralgliomas: diffusionalkurtosisimaginganalysis of microstructuraldifferences”, Raab P. et al.; Neuroradiology 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas Conclusion: There are significant differences in mean DK betweengliomagrades II through IV, therebyshowing a betterseparationbetweentumourgradesbymean DK thanbyconventional DTI measurements. Thisnewtechniquepotentiallycanbeused as anothernon-invasivebiomarkerfortumourgrading. “ Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences”, Raab P. et al.; Neuroradiology 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas “ Nosologicalimaging of the brain: segmentation and classificationusing MRI and MRSI” Luts J. et al. NMR in Biomedicine 2009 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas “ Nosologicalimaging of the brain: segmentation and classificationusing MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas NAP CSF FLAIR T1 + Gr II Gr III T1 T2 NOS IM Gr IV meningioma Glioblastomamultiforme LEGEND:Light blue: WM; dark blue: GM; green: CSF; yellow gr II; orange: gr III glioma; dark red: GBM “ Nosologicalimaging of the brain: segmentation and classificationusing MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas T1 T2 PD T1 + T1 T2 PD T1 + NOS IM NOS IM Gliomagrade II Gliomagrade II/III LEGEND:Light blue: WM; dark blue: GM; green: CSF; yellow gr II; orange: gr III glioma; dark red: GBM “ Nosologicalimaging of the brain: segmentation and classificationusing MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas Probabilitymaps and contour plots • LEGEND: • the lighter the probability map, the higher the probabilityfor a certain tissue type. • the blue contour lines show higher gr III probabilities, as opposedby the red lines. “ Nosologicalimaging of the brain: segmentation and classificationusing MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008 Medical Imaging Research Center July 2010
2. Review of the literature 2.2 Advanced MRI in gradinggliomas Conclusion: A newmethod to generatenosologic images of the brainbycombining MRI and MRSI in a two-stepapproach. First, abnormal tissue is segmented. Next, the abnormal tissue is classifiedusingpatternrecognition. Classprobabilitiesare generatedfor the diverse tissue types. “ Nosologicalimaging of the brain: segmentation and classificationusing MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008 Medical Imaging Research Center July 2010
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis “ Parametric response map as animagingbiomarker to distinguishprogressionfrompseudoprogression in high-gradeglioma”” Tsien C et al. J ClinOnc 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis “ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma”, Tsien C et al., J Clin Onc 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis Pseudoprogression: transientincrease in contrast enhancement without evidencefortumourrecurrence (hypothesis: inflammatory response to treatment) In HGG, * tumour vasculature is compromised due to rapid tumour growth * angiogenesis leading to a high density of leaky and immature vessels * the tumour core is characterized by regression and low vessel density PP LEGEND: red: significant increase in rCBV, blue: significant decrease; green: unchanged PD “ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma”, Tsien C et al., J Clin Onc 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis Conclusion: “Parametric response mapsapplied to parameters determinedbyperfusion-weighted MRI are a potentially important biomarkerin distinguishingpseudoprogression and progressivediseasein patientswithhigh gradegliomareceiving concurrent chemoradiation.” “ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma”, Tsien C et al., J Clin Onc 2010 Medical Imaging Research Center July 2010
2. Review of the literature 2.4 Advanced MRI in detectingrecurrence “ Predictingpatterns of gliomarecurrenceusingdiffusiontensorimaging” Price SJ et al. EurRadiol 2007 Medical Imaging Research Center July 2010
2. Review of the literature 2.4 Advanced MRI in detectingrecurrence Medical Imaging Research Center July 2010 “ Predictingpatterns of gliomarecurrenceusingdiffusiontensorimaging”, Price SJ et al., EurRadiol 2007
2. Review of the literature 2.4 Advanced MRI in detectingrecurrence P isotropicabnormality Q anisotropicabnormality T2 b0 T2 DIFFUSE PATTERN OF DTI ABNORMALITY T2 T2 b0 T2 LOCALISED PATTERN OF DTI ABNORMALITY T2 b0 T2 MINIMAL PATTERN OF DTI ABNORMALITY “ Predictingpatterns of gliomarecurrenceusingdiffusiontensorimaging”, Price SJ et al., EurRadiol 2007 Medical Imaging Research Center July 2010
2. Review of the literature 2.4 Advanced MRI in detectingrecurrence Conclusion: Diffusiontensorimagingcanpredictpatterns of tumourrecurrence. Looking at patternsfromeithertumourinfiltrationor occult tumour, notseenonconventional images maybehelpful in directingsurgicaltreatments, guidingbiospies and directinglocalchemotherapy and radiotherapytreatments. “ Predictingpatterns of gliomarecurrenceusingdiffusiontensorimaging”, Price SJ et al., EurRadiol 2007 Medical Imaging Research Center July 2010
Advancedmultimodal MRI in gliomas • Introduction • Review of the literature • Scope of our research Medical Imaging Research Center July 2010
3. Scope of our research To monitor treatmenteffectsin immune therapyforhigh gradegliomas • APPLICATION OF ADVANCED MR TECHNIQUES • To differentiateantitumour immune respons fromtumourrelapse/progression tool to assess vaccine efficacy • To propose criteria to distinguishrespondersfromnon-responders in anearly stage. TumourRelapse Immune Response Medical Imaging Research Center July 2010
3. Scope of our research Immune therapy Medical Imaging Research Center July 2010
3. Scope of our research * Translational research program in KU/UZ Leuven proof of principle experiments to demonstrate immunogenicity of patient derived mature DCs loaded with autologous tumour lysate pre-clinical in vivo experiments in a murineorthotopicglioma mouse model phase I/II clinical trials for relapsingpatients as solitary treatment and a phase II trial for patients with newly diagnosed GBM for whom immunotherapy is integrated in the current multimodal treatment laboratory analyses of patient samples Medical Imaging Research Center July 2010
3. Scope of our research • Macrophage labeling with USPIO • MR spectroscopy and DTI in the mouse model pre-clinical in vivo experiments in a murineorthotopicglioma mouse model MoSAIC KUL NEUROIMAGING Department of radiology UZL phase I/II clinical trials for relapsingpatients as solitary treatment and a phase II trial for patients with newly diagnosed GBM for whom immunotherapy is integrated in the current multimodal treatment MR spectroscopy and DKI/DTI in a longitudinalpatientstudy Medical Imaging Research Center July 2010
3. Scope of our research CURRENT STATUS PILOT EXPERIMENT 1: reproducibility of anoptimized CSI protocol MR spectroscopy and DKI/DTI in a longitudinalpatientstudy 10 à 15 patientswith GBM treatedwith immune therapy monthly follow-up anatomicalimaging: (T2, FLAIR, T1 +/- contrast) advancedtechniques : PWI, DKI, CSI PILOT EXPERIMENT 2: DKI and MRS in LGG and HGG in grading and the characterization of tumour infiltration in gliomatous brain tumours. Medical Imaging Research Center July 2010
Acknowledgments MoSAIC: Cindy Leten Ashwini Atre Jesse Trekker Greetje Vandevelde Tom Dresselaers Uwe Himmelreich ESAT: AncaCroitor Maria Isabel Osorio Jan Luts Diana Sima Sabine Van Huffel Thankyoufor the attention ! Questions? MIRC: Caroline Sage Silvia Kovacs Judith Verhoeven Sabine Deprez Thijs Dhollander JanakiRangarajan Ron Peeters Wim Van Hecke Stefan Sunaert Department of radiology UZL: Guido Wilms Philippe Demaerel Raymond Oyen Guy Marchal Medical Imaging Research Center July 2010
