Meeting Banner
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 Cha1,4, Susan M Chang4, Sarah J Nelson1,5, 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 Vin 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 Vin with 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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here