Predicting brain tumour growth patterns using a novel MRI-based tumour spread map: application to radiotherapy...

Area of Science:

• Neuro-oncology
• Radiotherapy Physics
• Medical Imaging Analysis

Background:

• Glioblastoma (GBM) treatment is challenging due to invasive growth and high recurrence rates within normal brain tissue.
• Current radiotherapy approaches struggle to effectively target diffuse tumour spread.

Purpose of the Study:

• To introduce a new metric, the tumour spread (TS) map, utilizing diffusion tensor imaging (DTI).
• To hypothesize that the TS map can predict GBM recurrence patterns and guide radiation therapy modifications.
• To pre-emptively target regions at high risk of tumour spread for improved treatment outcomes.

Main Methods:

• Diffusion tensor tractography was used to visualize white matter fiber tracts.
• A novel algorithm generated a TS map calculating voxel-wise probability of tumour spread.
• Radiotherapy target volumes were modified based on TS map predictions for Volumetric Modulated Arc Therapy (VMAT) planning.

Main Results:

• A TS map successfully predicted tumour spread along fiber tracts in a GBM patient.
• The modified target volume improved coverage of high-risk areas with a 21% reduction in overall volume.
• The modified VMAT plan delivered a higher dose (80% vs. 63%) to identified recurrences, preserving more normal tissue.

Conclusions:

• Tractography-based TS maps show promise for predicting GBM recurrence and optimizing radiotherapy.
• Further validation in larger patient cohorts is necessary.
• TS maps may enable personalized treatment strategies for glioblastoma.