Toward atlas-assisted automatic interpretation of MRI morphological brain scans in the presence of tumor.

Rationale and Objectives: Determination of distorted brain anatomy surrounding a tumor causing a mass effect is much more difficult than interpretation of normal brain scans, particularly because this distortion is not easily predictable a tumor may be located in any place and vary substantially in size, shape, and radiological appearance. The objective of our work is to provide a qualitative means for rapid estimation of brain anatomy distorted by tumor.
Materials and Methods: Toward achieving this objective, we use an electronic and deformable brain atlas of gross anatomy along with a fast atlas-to-data warping technique. The deformed atlas determines the distorted anatomy surrounding a tumor and can be used for structure labeling (naming). The warping algorithm uses the Talairach transformation followed by three-dimensional nonlinear tumor deformation based on a geometric assumption that the tumor, delineated on radiological images, compresses its surrounding tissues radially.
Results: The approach is implemented and a dedicated application is developed. It processes the data automatically in five steps: (1) load data, (2) set the Talairach landmarks and perform the Talairach transformation, (3) segment the tumor, (4) warp the scan nonlinearly in three dimensions, and (5) explore the scan. The approach is very fast, and a magnetic resonance imaging scan is processed in 10-15 seconds on a standard personal computer. It is fully automatic and gives the user control over the entire process.
Conclusion: Despite its limitations in modeling and validation, this practical solution provides a rapid and potentially useful qualitative assessment of anatomy deformed by a mass effect tumor.