Author Name 2 , Author Name 5 1 Dept. of Neurology, 2 Dept. of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA To demonstrate the utility of whole brain graded functional diffusion maps (fDMs) as an biomarker for monitoring brain tumor growth and invasion PURPOSE REFERENCES 1 Sugahara, JMRI, 1999; 2 Lyng, MRM, 2000; 3 Chenevert, JNCI, 2000; 4 Hayashida, AJNR, 2006; 5 Manenti, Radiol Med, 2008; 6 Gauvain, AJR, 2001; 7 Chenevert, Clin Cancer Res, 1997; 8 Moffat, Proc Nat Acad Sci, 2005; 9 Moffat, Neoplasia, 2006; 10 Hamstra, JCO, 2008; 11 Hamstra, Proc Nat Acad Sci, 2005. 12 Ellingson, JMRI, 2010. 13 Stupp, NEJM, 2005. Acknowledgements: In neoplasms, a decrease in apparent diffusion coefficient (ADC is believed to reflect an increase in tumor cellularity 1-6 , and an increase in ADC is believed to reflect necrosis or decreases in cellularity as a result of successful cytotoxic treatment 2,7 . Functional diffusion maps (fDMs) were developed to exploit these principles on a voxel-wise basis and may be useful for predicting response to chemotherapy and radiotherapy 8-11 . Currently, traditional fDMs rely on a single threshold for classifying voxels as significantly increasing or decreasing. We hypothesize that a graded fDM technique that stratifies voxels into varying degrees of change, applied to the whole brain may be useful for visualizing growing and invading tumor with high sensitivity and specificity. This is a Study About Some Sort of Glioblastoma Treatments This is a Study About Some Sort of Glioblastoma Treatments or Imaging of Brain Tumors or Imaging of Brain Tumors INTRODUCTION In neoplasms, a decrease in apparent diffusion coefficient (ADC is believed to reflect an increase in tumor cellularity 1-6 , and an increase in ADC is believed to reflect necrosis or decreases in cellularity as a result of successful cytotoxic treatment 2,7 . Functional diffusion maps (fDMs) were developed to exploit these principles on a voxel-wise basis and may be useful for predicting response to chemotherapy and radiotherapy 8-11 . Currently, traditional fDMs rely on a single threshold for classifying voxels as significantly increasing or decreasing. We hypothesize that a graded fDM technique that stratifies voxels into varying degrees of change, applied to the whole brain may be useful for visualizing growing and invading tumor with high sensitivity and specificity. In neoplasms, a decrease in apparent diffusion coefficient (ADC is believed to reflect an increase in tumor cellularity 1-6 , and an increase in ADC is believed to reflect necrosis or decreases in cellularity as a result of successful cytotoxic treatment 2,7 . Functional diffusion maps (fDMs) were developed to exploit these principles on a voxel-wise basis and may be useful for predicting response to chemotherapy and radiotherapy 8-11 . Currently, traditional fDMs rely on a single threshold for classifying voxels as significantly increasing or decreasing. We hypothesize that a graded fDM technique that stratifies voxels into varying degrees of change, applied to the whole brain may be useful for visualizing growing and invading tumor with high sensitivity and specificity. RESULTS METHODS

Author Name 2, Author Name 5 1 Dept. of Neurology, 2 Dept. of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA To demonstrate

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Page 1: Author Name 2, Author Name 5 1 Dept. of Neurology, 2 Dept. of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA To demonstrate

Author Name2, Author Name5Author Name2, Author Name5

1Dept. of Neurology, 2Dept. of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA1Dept. of Neurology, 2Dept. of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA

To demonstrate the utility of whole brain graded functional diffusion maps (fDMs) as an biomarker for monitoring brain tumor growth and invasion

PURPOSEPURPOSE

REFERENCESREFERENCES1 Sugahara, JMRI, 1999; 2 Lyng, MRM, 2000; 3 Chenevert, JNCI, 2000; 4 Hayashida, AJNR, 2006; 5 Manenti, Radiol Med, 2008; 6 Gauvain, AJR, 2001; 7 Chenevert, Clin Cancer Res, 1997; 8 Moffat, Proc Nat Acad Sci, 2005; 9 Moffat, Neoplasia, 2006; 10 Hamstra, JCO, 2008; 11 Hamstra, Proc Nat Acad Sci, 2005. 12 Ellingson, JMRI, 2010. 13 Stupp, NEJM, 2005.

Acknowledgements:Acknowledgements:

In neoplasms, a decrease in apparent diffusion coefficient (ADC is believed to reflect an increase in tumor cellularity 1-6, and an increase in ADC is believed to reflect necrosis or decreases in cellularity as a result of successful cytotoxic treatment 2,7. Functional diffusion maps (fDMs) were developed to exploit these principles on a voxel-wise basis and may be useful for predicting response to chemotherapy and radiotherapy 8-11. Currently, traditional fDMs rely on a single threshold for classifying voxels as significantly increasing or decreasing. We hypothesize that a graded fDM technique that stratifies voxels into varying degrees of change, applied to the whole brain may be useful for visualizing growing and invading tumor with high sensitivity and specificity.

This is a Study About Some Sort of Glioblastoma Treatments or Imaging of This is a Study About Some Sort of Glioblastoma Treatments or Imaging of Brain TumorsBrain Tumors

INTRODUCTIONINTRODUCTION In neoplasms, a decrease in apparent diffusion coefficient (ADC is believed to reflect an increase in tumor cellularity 1-6, and an increase in ADC is believed to reflect necrosis or decreases in cellularity as a result of successful cytotoxic treatment 2,7. Functional diffusion maps (fDMs) were developed to exploit these principles on a voxel-wise basis and may be useful for predicting response to chemotherapy and radiotherapy 8-11. Currently, traditional fDMs rely on a single threshold for classifying voxels as significantly increasing or decreasing. We hypothesize that a graded fDM technique that stratifies voxels into varying degrees of change, applied to the whole brain may be useful for visualizing growing and invading tumor with high sensitivity and specificity.

RESULTSRESULTSMETHODSMETHODS