Methodology for Imaging Genomics of Gliomas Rivka R. Colen, M.D. 1, Bhanu Mahajan, M.B.B.S. 1, Arpad...

Methodology for Imaging Genomics of Gliomas

Rivka R. Colen, M.D.1, Bhanu Mahajan, M.B.B.S.1, Arpad Kovacs, M.D.1, Pascal O. Zinn, M.D.2, Ferenc A. Jolesz, M.D.1

1 Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.2 M.D. Anderson Cancer Center, Houston, TX, USA.

ASNR 2012ASNR 2012

© NlH National Center for Image Guided Therapy, 2012

No Disclosures.

R25 CA089017(RRC) P41 RR019703 (FAJ)

Disclosures


• Imaging Genomics has emerged as a new field which links gene expression profiles with MRI phenotypes.

• MRI (radio) phenotypes( necrosis, edema/tumor infiltration, contrast enhancement, perfusion, diffusion) correlated with underlying genomic composition (genes, microRNAs, etc)

Imaging Genomics


• Quantitative image analysis results in more precise and reproducible results and can then be correlated with genomics.

• In imaging genomics, tumor volumetrics has the potential to uncover genomic targets for subsequent development into cancer therapeutics.

• This was first described by Zinn et al in 2011 where an invasive gene and microRNA was uncovered using the FLAIR volume as an MRI biomarker (radiophenotype).

Imaging Genomics


Zinn PO, Majadan B, Sathyan P, Singh SK, Majumder S, Jolesz FA, Colen RR. Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme. PLoS One. 2011;6(10):e25451

• In this study, we seek demonstrate the methodology for imaging genomic brain tumor volumetric analysis and its feasibility.

Purpose


• Here, we demonstrate the methodology and feasibility for the first comprehensive radiogenomic analysis using quantitative MRI volumetrics and large-scale gene- and microRNA expression profiling in Glioblastoma Multiforme (GBM).

Imaging Genomics


• Retrospective study of 78 treatment naïve GBM patients

• Image data used in this research were obtained from The Cancer Imaging Archive (http://cancerimagingarchive.net/) sponsored by the Cancer Imaging Program, DCTD/NCI/NIH.

• Imaging was correlated with Gene- and micoRNA- expression profiles obtained from The Cancer Genome Atlas (TCGA)

Methods and Materials


http://cancergenome.nih.gov

http://cancerimagingarchive.net/

T2/FLAIR was rigidly aligned and registered to the post- contrast T1WI.



Segmentation Slicer 3.6 (slicer.org)Volumes were obtained using the segmentation module of Slicer

Segmentation Slicer 3.6 (slicer.org)Volumes were obtained using the segmentation module of Slicer



Volumetric segmentation was performed in a simple hierarchical model of anatomy, proceeding from peripheral to central.

Volumetric segmentation was performed in a simple hierarchical model of anatomy, proceeding from peripheral to central.




Edema NecrosisContrast Enhancement

- This results in 3 distinct structures being segmented:• Edema/invasion• Enhancing tumor• Necrosis

- This results in 3 distinct structures being segmented:• Edema/invasion• Enhancing tumor• Necrosis



Tumor Segmentation. 65 year old male patient with a right temporal GBM. Segmentation of tumor edema (blue), enhancement (yellow) and necrosis (red) was performed and edema volume was obtained.

Fluid-attenuated inversion recovery (FLAIR) was used for segmentation of the edema



Ede

ma

Post contrast T1-weighted imaging (T1W1) for segmentation of enhancement(tumor) and necrosis



Contrast enhancement

Necrosis



• Slicer Model Making Module for Volume calculations

• Models (Volumes) of Edema, Tumor and Necrosis were generated from previously performed segmentations.



Volumes of each radiophenotype ( edema/tumor infiltration, enhancing tumor, and necrosis) were then

correlated with the genomic findings.


• In most scans, image registration was almost 100%

• Scans where complex rotational modifications and registration were required, registration was deemed adequate when error was 2mm or less.

Results


• Quantitative volumes of edema/invasion, enhancement and necrosis were in high correlation with biologically concordant functional genomic targets.

Results



MRI-FLAIR radiophenotype readily and noninvasively detected key cancer genomic components responsible for cellular migration and invasion in GBM.

• Quantitative imaging genomic analysis is simple.

• Imaging surrogates/ biomarkers using conventional MRI radiophenotypes of necrosis, enhancing tumor and edema/tumor infiltration reflect specific genomic composition in GBM.

• Quantitative imaging genomic analysis allow for predictions of key genetic events.

• Quantitative imaging genomic analysis can screen for novel genomic targets for possible subsequent development of targeted therapeutics.

• Stratify patients based on their genetic/molecular makeup into responders versus non-responders to a particular treatment.

• The ability to determine uncover genomic targets from routine clinical MRI examinations and thus subsequently determine if a patient is a candidate for that genomic therapy is a major step towards personalized medicine.

Conclusion


Thank you for your interest!

Acknowledgements: This work was supported by NIH grant R25 CA089017-06A2 (RRC).

Any questions please email: [email protected].

Conclusion


Methodology for Imaging Genomics of Gliomas Rivka R. Colen, M.D. 1, Bhanu Mahajan, M.B.B.S. 1, Arpad...

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