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Updated: May 12, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and
Daniel Rodriguez Gutierrez1, Muftah Manita, Tim Jaspan
1Division of Radiological and Imaging Sciences, University of Nottingham, Nottingham, United Kingdom.
Background:
Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response.
Methods:
Eighteen patients (age range, 1.9-20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1-16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM).
Results:
Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η(2) = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis.
Conclusions:
We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols.
Insights
Diffusion MRI metrics effectively predict treatment response in pediatric high-grade brain tumors. The functional diffusion map slope method showed the highest accuracy for early assessment.
Area of Science:
- Pediatric oncology
- Neuroimaging
- Biomedical engineering
Background:
- Tumor size is a late indicator of treatment response.
- Diffusion MRI offers earlier response assessment in adults, but data in pediatric brain tumors is limited.
- This study evaluates diffusion MRI metrics for predicting treatment response in children with high-grade brain tumors.
Purpose of the Study:
- To assess and compare the predictive value of diffusion change metrics for treatment response in pediatric high-grade brain tumors.
- To determine the most accurate diffusion MRI metric for early response prediction.
- To validate these metrics despite variable imaging protocols.
Main Methods:
- Retrospective study of 18 pediatric patients with high-grade brain tumors.
- Serial diffusion MRI data analyzed pre- and posttreatment (1-16 weeks).
- Compared regional apparent diffusivity coefficient (ADC) change, fractional volume of increased/decreased ADC (fiADC/fdADC), and functional diffusion map (fDM) slope with 6-month clinical response.
Main Results:
- All diffusion change metrics significantly differentiated responders from non-responders (P < .05).
- The fDM slope metric provided the best prediction accuracy (83%) with high statistical significance (P < .01, η(2) = 0.78).
- The optimal prediction threshold for the fDM slope was 58° via ROC analysis.
Conclusions:
- Diffusion change metrics are reliable predictors of treatment response in high-grade pediatric brain tumors.
- The fDM slope metric shows particular promise for early and accurate response assessment.
- These findings hold true even with variations in clinical diffusion imaging protocols.
