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Updated: Jun 5, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Predicting glioblastoma progression using MR diffusion tensor imaging: A systematic review
Francesca M Cozzi1, Roxanne C Mayrand1, Yizhou Wan1
1Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK.
Background And Purpose:
Despite multimodal treatment of glioblastoma (GBM), recurrence beyond the initial tumor volume is inevitable. Moreover, conventional MRI has shortcomings that hinder the early detection of occult white matter tract infiltration by tumor, but diffusion tensor imaging (DTI) is a sensitive probe for assessing microstructural changes, facilitating the identification of progression before standard imaging. This sensitivity makes DTI a valuable tool for predicting recurrence. A systematic review was therefore conducted to investigate how DTI, in comparison to conventional MRI, can be used for predicting GBM progression.
Methods:
We queried three databases (PubMed, Web of Science, and Scopus) using the search terms: (diffusion tensor imaging OR DTI) AND (glioblastoma OR GBM) AND (recurrence OR progression). For included studies, data pertaining to the study type, number of GBM recurrence patients, treatment type(s), and DTI-related metrics of recurrence were extracted.
Results:
In all, 16 studies were included, from which there were 394 patients in total. Six studies reported decreased fractional anisotropy in recurrence regions, and 2 studies described the utility of connectomics/tractography for predicting tumor migratory pathways to a site of recurrence. Three studies reported evidence of tumor progression using DTI before recurrence was visible on conventional imaging.
Conclusions:
These findings suggest that DTI metrics may be useful for guiding surgical and radiotherapy planning for GBM patients, and for informing long-term surveillance. Understanding the current state of the literature pertaining to these metrics' trends is crucial, particularly as DTI is increasingly used as a treatment-guiding imaging modality.
Insights
Diffusion tensor imaging (DTI) shows promise for predicting glioblastoma (GBM) recurrence by detecting microstructural changes before conventional MRI. This advanced imaging can guide treatment and surveillance for GBM patients.
Area of Science:
- Neuroimaging
- Oncology
- Radiology
Background:
- Glioblastoma (GBM) inevitably recurs despite multimodal treatment.
- Conventional MRI has limitations in detecting early tumor infiltration in white matter tracts.
- Diffusion tensor imaging (DTI) offers enhanced sensitivity to microstructural changes.
Conclusions:
- DTI metrics show potential for guiding GBM treatment planning (surgery, radiotherapy).
- DTI can inform long-term surveillance strategies for GBM patients.
- Understanding DTI trends is vital as it becomes a standard treatment-guiding modality.
