The influence of anisotropy on the clinical target volume of brain tumor patients

Abstract

Objective. Current radiotherapy guidelines for glioma target volume definition recommend a uniform margin expansion from the gross tumor volume (GTV) to the clinical target volume (CTV), assuming uniform infiltration in the invaded brain tissue. However, glioma cells migrate preferentially along white matter tracts, suggesting that white matter directionality should be considered in anisotropic CTV expansion. We investigate two models of anisotropic CTV expansion and evaluate their clinical feasibility.
Approach. To incorporate white matter directionality into the CTV, a diffusion tensor imaging (DTI) atlas is used. The DTI atlas consists of water diffusion tensors that are first spatially transformed into local tumor resistance tensors, also known as metric tensors, and secondly fed to a CTV expansion algorithm to generate anisotropic CTVs. Two models of spatial transformation are considered in the first step. The first model assumes that tumor cells experience reduced resistance parallel to the white matter fibers. The second model assumes that the anisotropy of tumor cell resistance is proportional to the anisotropy observed in DTI, with an "anisotropy weighting parameter" controlling the proportionality. The models are evaluated in a cohort of ten brain tumor patients.
Main results. To evaluate the sensitivity of the model, a library of model-generated CTVs was computed by varying the resistance and anisotropy parameters. Our results indicate that the resistance coefficient had the most significant effect on the global shape of the CTV expansion by redistributing the target volume from potentially less involved gray matter to white matter tissue. In addition, the anisotropy weighting parameter proved useful in locally increasing CTV expansion in regions characterized by strong tissue directionality, such as near the corpus callosum.
Significance. By incorporating anisotropy into the CTV expansion, this study is a step toward an interactive CTV definition that can assist physicians in incorporating neuroanatomy into a clinically optimized CTV.

Integrating muscle fiber orientation from visible human data into radiotherapy target volumes

“…showing that the structure tensor transforms according to the same rule as the Riemann metric tensor under a change in coordinate basis (Buti et al 2024).…”

“…In our framework, a relationship between metric and structure tensors can be established by noting that small intensity gradients in image space correspond to reduced resistance to tumor infiltration. Accordingly, the structure tensor T (or T ) can be transformed into G by replacing Λ in (2) by a parameterized diagonal matrix diag(ρ, 1, 1) in muscle tissue and defining (Shusharina et al 2022, Buti et al 2024:…”

“…Accordingly, VHM CTVs and VHF CTVs were generated by setting the ρ parameter to 0.44, 0.25, and 0.11, respectively. To facilitate CTV comparison, the VHF CTV and VHM CTV were normalized to the Standard CTV by selecting the iso-geodesic distance contours that surround the same volume as the Standard CTV for each patient (Unkelbach et al 2012, 2014, Buti et al 2024. The Dice similarity coefficient (DSC) and the Hausdorff 95% percentile index (HD95) are used to quantify the volume overlap and surface distance, respectively.…”