Abstract #4182

Comparison of tumor microstructure derived NODDI and DTI metrics to histopathology in different grades of brain tumor

Prasanna Parvathaneni¹, Qiuting Wen², Joanna J Phillips ^3,4, Soonmee Cha^1,4, Susan M Chang⁴, Sarah J Nelson^1,5, and Janine M Lupo¹

¹Department of Radiology and Biomedical Imaging, University of California San Francisco (UCSF), San Fransisco, CA, United States, ²Indiana University, Indianapolis, IN, United States, ³Department of Pathology, University of California San Francisco (UCSF), San Fransisco, CA, United States, ⁴Department of Neurological Surgery, University of California San Francisco (UCSF), San Fransisco, CA, United States, ⁵Department of Bioengineering and Therapeutic Sciences, University of California San Francisco (UCSF), San Fransisco, CA, United States

New non-Gaussian measurement techniques like neurite orientation dispersion and density imaging (NODDI) that allow quantification of specific tissue microstructure features can provide meaningful biophysical indices to overcome the low specificity of DTI. In this study we applied three compartment model based NODDI and DTI to histopathology and explored the correlation with tumor cellularity between non-enhancing and contrast enhancing lesions. Unlike in normal brain where V_in represents the neurite density, it was positively correlated with tumor grade and tumor score in tissue samples from the tumor region, indicating the association of V_inwith tumor cellularity. Although NODDI is not directly built on tumor, it brings parameters that were sensitive to tumor cellularity, which may complement the conventional DTI model and adds specificity. Thus NODDI, when combined with DTI, could add value in understanding the heterogeneity of tissue microstructure in brain tumors.

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