sofie van cauter uwe himmelreich, stefaan van gool, stefan sunaert
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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 - PowerPoint PPT PresentationTRANSCRIPT
“Advanced MR imaging in diagnosis, treatment planning and therapy monitoring in gliomatous brain
tumours: review of the literature”
Sofie Van CauterUwe Himmelreich, Stefaan Van Gool, Stefan Sunaert
Advanced multimodal MRI in gliomas
1. Introduction
2. Review of the literature
3. Scope of our research
Medical Imaging Research Center July 2010
Advanced multimodal MRI in gliomas
1. Introduction
2. Review of the literature
3. Scope of our research
Medical Imaging Research Center July 2010
1. Introduction
Gliomas (arise from neuroectodermal glial cells): 7/100 000/year
Astrocytomas (pilocytic vs diffuse) Oligodendrogliomas Ependymomas Gangliogliomas
Low grade (WHO gr I and II) High grade (WHO gr III and IV)
Gr IV: glioblastoma multiforme (primary – secondary; 4/100 000/year)
Treatment: “watchfull waiting” (+ biopsy) <-> debulking , radiotherapy, chemotherapy new evolving therapies immune therapy, targeted therapy,…..
Overall bad prognosisLGG: 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% mortality after 1.5 y
Medical Imaging Research Center July 2010
1. Introduction
How to asses?
NEUROIMAGING
• Computed tomography• Magnetic resonance imaging
• Positron emission tomogrpahy• Single photon emission computed tomography
• Diffuse optical imaging• Event-related optical signal• Electroencephalography• Mangetoencephalography
Radiology
Nuclear medecine
Medical Imaging Research Center July 2010
1. Introduction
Anatomical imaging techniques Functional imaging techniques
Magnetic resonance imaging
* diffusion weighted imaging
* diffusion tensor imaging, diffusion kurtosis imaging
* perfusion weighted imaging (DCE)
* MR spectroscopy
* functional MR imagingMedical Imaging Research Center July 2010
* T1 +/- contrast administration, T2, FLAIR
1. Introduction
Medical Imaging Research Center July 2010
Diffusion weighted imaging – Diffusion tensor imaging – Diffusion kurtosis imaging
- Brownian molecular motion diffusion - In biological tissue, restriction of “mobility” due to tissue cellularity and cell mebrane integrity- MR derived parameters: ADC, FA, MK, ……..
+ =
1. Introduction
Medical Imaging Research Center July 2010
Perfusion weighted imaging
- Perfusion-weighted MRI is a non-invasive imaging method for quantification of vascular properties.
- Dynamic susceptibility contrast magnetic resonance imaging (DSC-MR) is acquired by repetitive imaging with high temporal resolution during the injection of Gd-Based contrast agent
- Derived parameters: rCBV, rCBF, MTT,…..
1. Introduction
Medical Imaging Research Center July 2010
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.
Water signal
Membrane turnover
Energy metabolism
Neuronal marker
1. Introduction
Medical Imaging Research Center July 2010
MR spectroscopy
Different TE
TE: 35ms TE:144 ms
Detection of pathology SV vs CSI
1. Introduction
What to asses in brain neoplasms with neuroimaging techniques?
- diagnosis - grading - progression / relapse after treatment - treatment effects
Medical Imaging Research Center July 2010
Advanced multimodal MRI in gliomas
1. Introduction
2. Review of the literature
3. Scope of our research
Medical Imaging Research Center July 2010
2. Review of the literature 2.1 Advanced MRI in diagnosing gliomas
“ Distinction between high-grade gliomas and solitary metastases using peritumoral 3T
magnetic resonance spectroscopy, diffusion and perfusion imaging ”
Chan Chiang I. et al.Neuroradiology 2004
Medical Imaging Research Center July 2010
2. Review of the literature 2.1 Advanced MRI in diagnosing gliomas
Subjects 26 patients: 14 high grade gliomas and 12 metastases presurgical histopathology confirmed
Methodology - Prospective study / biopsy or surgical resection histopathological confirmation- 3T; conventional MR, MRS, DWI 12 pts PWI
PWI: rCBV in 3 regions (tumoral region, peritumoral edema and NAPWM)CSI: Cho/Cre and NAA/Cre (maximal values in 3 regions)DWI: ADC maps
Results - PWI: rCBV is significantly higher in peritumoral edema of HGG
- CSI: Cho/Cre is significantly higher in peritumoral edema of HGG
- DWI: ADC in peritumoral edema and contrast enhancing areas of metastases significantly higher than in HGG
Medical Imaging Research Center July 2010
“ Distinction between high-grade gliomas and solitary metastases using peritumoral 3T magnetic resonance spectroscopy, diffusion and perfusion imagings ”, Chan Chiang I. et al., Neuroradiology 2004
2. Review of the literature 2.1 Advanced MRI in diagnosing gliomas
MR spectroscopy
Perfusion weighted imaging
Diffusion weighted imaging
Medical Imaging Research Center July 2010
“ Distinction between high-grade gliomas and solitary metastases using peritumoral 3T magnetic resonance spectroscopy, diffusion and perfusion imagings ”, Chan Chiang I. et al., Neuroradiology 2004
CSI, TE: 270 TR: 1500ms
rCBV map
ADC maps, TE: 100 ms TR: 12000ms, b-value: 1000 mm/s²
2. Review of the literature 2.1 Advanced MRI in diagnosing gliomas
Conclusion:
Perfusion-weighted MRI, diffusion weighted MRI and MR spectroscopy (Cho/Cr) in the peritumoural region can be used to demonstrate differences in solitary metastases and high-grade
gliomas. The intratumoural rCBV, Cho/Cr, NAA/Cr and peritumoural NAA/Cr do not differ statistically from those seen with metastases
Medical Imaging Research Center July 2010
“ Distinction between high-grade gliomas and solitary metastases using peritumoral 3T magnetic resonance spectroscopy, diffusion and perfusion imagings ”, Chan Chiang I. et al., Neuroradiology 2004
2. Review of the literature 2.2 Advanced MRI in grading gliomas
“ 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 grading gliomas
Subjects 5 grade II astrocytomas13 grade III astroctyomas16 grade IV glioblastoma multiforme
Methodology - Prospective study / surgery within three weeks histopathological confirmation- 3T 6 b-values (0, 500, 1000, 1500, 2000 and 2500 sec /mm²), 30 directions each- segmentation of the most solid part of the tumour on T2w-images- average MK, average FA, average ADC for every region of interest; normalized MK, FA and ADC
Results - Average MK and normalized MK values increased with higher tumour grades significant between gr II, III and IV
- Average and normalized ADC values decreased with higher tumour grades significant between gr III and IV, NOT between gr II and III
- Average FA values: no difference between gr II and III; slightly increase in GBM without statistical significance
Medical Imaging Research Center July 2010
“ Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences”, Raab P. et al.; Neuroradiology 2010
2. Review of the literature 2.2 Advanced MRI in grading gliomas
“The data demonstrate significantdifferences in MK values among gliomas of different WHO grades”
Medical Imaging Research Center July 2010
“ Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences”, Raab P. et al.; Neuroradiology 2010
2. Review of the literature 2.2 Advanced MRI in grading gliomas
Conclusion:
There are significant differences in mean DK between glioma grades II through IV, thereby showing a better separation between
tumour grades by mean DK than by conventional DTI measurements.
This new technique potentially can be used as another non-invasive biomarker for tumour grading.
Medical Imaging Research Center July 2010
“ Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences”, Raab P. et al.; Neuroradiology 2010
2. Review of the literature 2.2 Advanced MRI in grading gliomas
“ Nosological imaging of the brain: segmentation and classification using 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 grading gliomas
Subjects 24 patients (diffuse astrocytoma, oligoastrocytoma, oligodendroglioma, glioblastoma and meningioma) and 4 healthy volunteers selected from a database histopathological confirmed
Methodology - 1.5T short echo time spectra 2D STEAM
- Training data set for pattern recognition: several voxels from the tumor area (HP confirmed) and normal appearing tissue
- Segmentation of parenchym tissue (tumour, edema, NAP) on anatomical images.
- Coregistration with MRSI data.
- Classification based on pattern recognition in order to provide information on the tissue type TWO STEP SEGMENTATION-CLASSIFICATION METHOD
Results - The method proposed in the paper is flexible: any classifier can be integrated.
- Probability maps
Medical Imaging Research Center July 2010
“ Nosological imaging of the brain: segmentation and classification using MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008
2. Review of the literature 2.2 Advanced MRI in grading gliomas
Medical Imaging Research Center July 2010
“ Nosological imaging of the brain: segmentation and classification using MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008
NAP CSF
Gr II Gr III
Gr IVmeningiomaGlioblastoma multiforme
LEGEND: Light blue: WM; dark blue: GM; green: CSF; yellow gr II; orange: gr III glioma; dark red: GBM
T1 T2 FLAIR T1 +
NOS IM
2. Review of the literature 2.2 Advanced MRI in grading gliomas
Medical Imaging Research Center July 2010
“ Nosological imaging of the brain: segmentation and classification using MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008
Glioma grade II
LEGEND: Light blue: WM; dark blue: GM; green: CSF; yellow gr II; orange: gr III glioma; dark red: GBM
Glioma grade II/III
T1 T1 T2T2 PDPD T1 +T1 +
NOS IMNOS IM
2. Review of the literature 2.2 Advanced MRI in grading gliomas
Medical Imaging Research Center July 2010
“ Nosological imaging of the brain: segmentation and classification using MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008
Probability maps and contour plots
LEGEND: • the lighter the probability map, the higher the probability for a
certain tissue type.• the blue contour lines show higher gr III probabilities, as opposed by
the red lines.
2. Review of the literature 2.2 Advanced MRI in grading gliomas
Medical Imaging Research Center July 2010
“ Nosological imaging of the brain: segmentation and classification using MRI and MRSI” Luts J. et al., NMR in Biomedicine 2008
Conclusion:
A new method to generate nosologic images of the brain by combining MRI and MRSI in a two-step approach. First, abnormal tissue is segmented. Next, the abnormal tissue is classified using
pattern recognition. Class probabilities are generated for the diverse tissue types.
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis
Medical Imaging Research Center July 2010
“ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma””
Tsien C et al.J Clin Onc 2010
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis
Medical Imaging Research Center July 2010
Subjects - 27 patients with HGG receiving concurrent chemoradiotherapy (20 pts previous surgery)
Methodology - prospective study- MRI prior to R/, week 1 and week 3. (DCE-MRI)- normalized rCBV and rCBF maps- segmentation of GTV- the differences between serial rCBV/rCBF maps calculated for each voxel within the GTV pre and on week 3.-T on Δ rCBV > 1.2 or < -1.2 (PRM: parametric response mapping)- 1 m post-treatment, anatomical MR to determine response treatment.
Results - No significant results when looking at rCBV or rCBF.
- No significant results when looking at baseline mean rCBF and mean rCBV in PD and PP. Statistically significant results when looking at baseline mean rCBV between pts with SD and PD.
- Significant differences in change of rCBV between PD en PP
“ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma”, Tsien C et al., J Clin Onc 2010
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis
Medical Imaging Research Center July 2010
“ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma”, Tsien C et al., J Clin Onc 2010
Pseudoprogression: transient increase in contrast enhancement without evidence for tumour recurrence (hypothesis: inflammatory response to treatment)
LEGEND: red: significant increase in rCBV, blue: significant decrease; green: unchanged
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
PD
PP
2. Review of the literature 2.3 Advanced MRI in treatment FU/prognosis
Medical Imaging Research Center July 2010
“ Parametric response map as an imaging biomarker to distinguish progression from pseudoprogression in high-grade glioma”, Tsien C et al., J Clin Onc 2010
Conclusion:
“Parametric response maps applied to parameters determined by perfusion-weighted MRI are a potentially important biomarker in
distinguishing pseudoprogression and progressive disease in patients with high grade glioma receiving concurrent
chemoradiation.”
2. Review of the literature 2.4 Advanced MRI in detecting recurrence
“ Predicting patterns of glioma recurrence using diffusion tensor imaging”
Price SJ et al.Eur Radiol 2007
Medical Imaging Research Center July 2010
2. Review of the literature 2.4 Advanced MRI in detecting recurrence
Subjects 8 grade II astrocytomas5 grade III astroctyomas12 grade IV glioblastoma multiforme
Methodology - Restrospective study , DTI + follow-up imaging (6 in WW, 19 in R/)- 3T, 12 directions with 6 b-values each (0-1570 mm/s²)- eigenvalues isotropic component p, anisotropic component q maps- delineate areas with reduced q and abnormalities in p
--> Compare with images at the time of recurrence on conventional imaging
Results - DIFFUSE PATTERN OF DTI ABNORMALITY: The p abnormality exceeded diffusely beyond the q abnormality. Tumour recurrence showed a generalized increase in the size of the tumour
- LOCALISED PATTERN OF DTI ABNORMALITY: Tumour regrowth occured in the direction where the isotropic abnormality p exceeded the anisotropic abnormality q
- MINIMAL PATTERN OF DTI ABNORMALITY: no evidence of tumour regrowth (one exception)
Medical Imaging Research Center July 2010
“ Predicting patterns of glioma recurrence using diffusion tensor imaging”, Price SJ et al., Eur Radiol 2007
2. Review of the literature 2.4 Advanced MRI in detecting recurrence
P isotropic abnormalityQ anisotropic abnormality
DIFFUSE PATTERN OF DTI ABNORMALITY
LOCALISED PATTERN OF DTI ABNORMALITY
MINIMAL PATTERN OF DTI ABNORMALITY
Medical Imaging Research Center July 2010
“ Predicting patterns of glioma recurrence using diffusion tensor imaging”, Price SJ et al., Eur Radiol 2007
T2 T2
T2
T2
T2
T2
T2
b0
b0
b0
2. Review of the literature 2.4 Advanced MRI in detecting recurrence
Conclusion:
Diffusion tensor imaging can predict patterns of tumour recurrence. Looking at patterns from either tumour infiltration or occult tumour, not seen on conventional images may be helpful in
directing surgical treatments, guiding biospies and directing local chemotherapy and radiotherapy treatments.
Medical Imaging Research Center July 2010
“ Predicting patterns of glioma recurrence using diffusion tensor imaging”, Price SJ et al., Eur Radiol 2007
Advanced multimodal MRI in gliomas
1. Introduction
2. Review of the literature
3. Scope of our research
Medical Imaging Research Center July 2010
3. Scope of our research
To monitor treatment effects in immune therapy for high grade gliomas
APPLICATION OF ADVANCED MR TECHNIQUES
- To differentiate antitumour immune respons from tumour relapse/progression tool to assess vaccine efficacy
- To propose criteria to distinguish responders from non-responders in an early stage.
Immune Response Tumour Relapse
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 murine
orthotopic glioma mouse model
phase I/II clinical trials for relapsing patients 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
pre-clinical in vivo experiments in a murine
orthotopic glioma mouse model
phase I/II clinical trials for relapsing patients as
solitary treatment and a phase II trial for patients
with newly diagnosed GBM for whom immunotherapy is integrated in the current
multimodal treatment
Macrophage labeling with USPIO
MR spectroscopy and DTI in the mouse model
MR spectroscopy and DKI/DTI in a longitudinal patient study
NEUROIMAGING
MoSAIC KUL
Department of radiology UZL
Medical Imaging Research Center July 2010
3. Scope of our research
CURRENT STATUS
MR spectroscopy and DKI/DTI in a longitudinal patient study10 à 15 patients with GBM treated with immune therapy
monthly follow-upanatomical imaging: (T2, FLAIR, T1 +/- contrast)
advanced techniques : PWI, DKI, CSI
PILOT EXPERIMENT 1: reproducibility of an optimized CSI protocol
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
Medical Imaging Research Center July 2010
Acknowledgments
MIRC:Caroline SageSilvia KovacsJudith VerhoevenSabine DeprezThijs DhollanderJanaki RangarajanRon PeetersWim Van HeckeStefan Sunaert
MoSAIC:Cindy LetenAshwini AtreJesse TrekkerGreetje VandeveldeTom DresselaersUwe Himmelreich
ESAT:Anca Croitor
Maria Isabel OsorioJan Luts
Diana SimaSabine Van Huffel
Department of radiology UZL:Guido Wilms
Philippe DemaerelRaymond Oyen
Guy Marchal
Thank you for the attention ! Questions?