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Updated: Jul 3, 2026
DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
Published on: August 26, 2014
Mapping brain tumor microstructure: A multimodal study of diffusion MRI, intraoperative fluorescence, and
Elisabeth Klint1, Johan Richter2, Teresa Nordin1
1Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
Abstract:
High-grade glioma characteristics such as heterogeneity and diffuse growth present a major diagnostic and therapeutic challenge, making accurate imaging essential for diagnosis and surgical planning. Diffusion MRI (dMRI) shows promise in tissue identification through a negative correlation between the dMRI apparent diffusion coefficient and tumor cellularity. Further, tissue disorganization due to tumor growth is correlated with decreased fractional anisotropy (FA) from diffusion tensor imaging (DTI). Q-space trajectory imaging (QTI) through free gradient waveform encoding during dMRI acquisition has been suggested as a framework for dMRI scalar map generation, enabling disentangled measures of shape, size, and orientation. We aimed to extend a clinically integrated workflow for optical guidance in frameless navigated brain tumor biopsies to include DTI and QTI scalars for multimodal analysis. Diffusion scalars were compared to tumor indications on tissue fluorescence, conventional imaging, and neuropathology in navigated brain tumor biopsy procedures. In seven high-grade glioma patients, the biopsied tissue volume was associated with decreased dMRI features (anisotropy, kurtosis, and order parameters) and increased diffusivity in DTI when compared with contralateral white matter. Principal components of diffusion scalars depend on microstructural (QTI) and diffusivity (DTI) parameters, respectively. Redundancy analysis between the dMRI scalars revealed scalar pairs that offer novel information for tissue separation that could be of interest for fine-tuning of the MRI protocol before further evaluation of QTI for tumor tissue identification in the clinical setting.
Insights
This study integrates advanced diffusion MRI (dMRI) techniques, including diffusion tensor imaging (DTI) and Q-space trajectory imaging (QTI), into brain tumor biopsies. Findings reveal dMRI scalars can differentiate high-grade gliomas from healthy tissue, aiding diagnosis and surgical planning.
Area of Science:
- Neuroimaging
- Oncology
- Biophysics
Background:
- High-grade gliomas present diagnostic and therapeutic challenges due to heterogeneity and diffuse growth.
- Accurate imaging is crucial for diagnosis and surgical planning in neuro-oncology.
- Diffusion MRI (dMRI) shows potential for tissue characterization by correlating diffusion coefficients with tumor cellularity.
Purpose of the Study:
- To integrate Diffusion Tensor Imaging (DTI) and Q-space Trajectory Imaging (QTI) scalars into a clinical workflow for navigated brain tumor biopsies.
- To compare diffusion scalars with tissue fluorescence, conventional imaging, and neuropathology in high-grade glioma patients.
- To explore the utility of dMRI scalars for multimodal analysis and tissue differentiation.
Main Methods:
- Extended a clinical workflow for frameless navigated brain tumor biopsies to incorporate DTI and QTI.
- Acquired dMRI data using free gradient waveform encoding for QTI.
- Compared diffusion scalars (anisotropy, kurtosis, order parameters, diffusivity) with contralateral white matter and neuropathological findings in seven high-grade glioma patients.
Main Results:
- Biopsied high-grade glioma tissue showed decreased dMRI features (anisotropy, kurtosis, order parameters) and increased diffusivity compared to contralateral white matter.
- Principal components of diffusion scalars were dependent on microstructural (QTI) and diffusivity (DTI) parameters.
- Redundancy analysis identified scalar pairs offering novel information for tissue separation.
Conclusions:
- Integrated DTI and QTI provide valuable microstructural and diffusivity information for differentiating high-grade gliomas.
- Specific dMRI scalar pairs show promise for enhancing tissue separation and could inform MRI protocol optimization.
- Further evaluation of QTI is warranted for clinical application in tumor tissue identification.
