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Abstract #3643

Association Between MR Imaging Measurements and Image-Guided Tissue Histopathology in Patients with Recurrent GBM

Qiuting Wen1, 2, Adam Elkhaled2, Emma Essock-Burns1, Annette Molinaro3, Joanna Phillips3, 4, Susan M. Chang5, Soonmee Cha6, Sarah J. Nelson1, 7

1Graduate Group in Bioengineering, UC Berkeley/UC San Francisco, San Francisco, CA, United States; 2Department of Radiology and Biomedical Imaging, UC San Francisco, San Francisco, CA, United States; 3Department of Neurological Surgery, UC San Francisco, San Francisco, CA, United States; 4Department of Pathology, UC San Francisco, UCSF San Francisco, CA, United States; 5Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, United States; 6Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States; 7Bioengineering and Therapeutic Science, UC San Francisco, San Francisco, CA, United States

Treatment with radiation and chemotherapy may result in gliosis, edema and necrosis, which can mimic tumor recurrence in standard MR images. Differentiating between these effects is a critical central challenge in neuro-oncology [1]. Acquisition of image guided tissue samples can enable the association of pathological properties of the tissue with pre-surgical MR parameters [2]. Ex vivo spectroscopy also offers direct association of pathology with a wide range of cellular metabolites [3]. The purpose of this study was to evaluate which in vivo and ex vivo MR parameters were able to distinguish between tumor and treatment effect in for patients with GBM. Our results showed the ability of PH, in vivo NAA, ex vivo NAA and Cr in differentiating tumor recurrence from treatment effect, which is consistent with the clinical findings that tumor recurrence has elevated angiogenesis and causes more neuronal disruption..It should be noted that there is overlap between the two groups for these parameters (see Figure 2), which suggests that future studies should consider using a multi-variate index to map out regions of recurrent tumor.

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Keywords

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