Optimizing global liver function in radiation therapy treatment planning.

Liver stereotactic body radiation therapy (SBRT) patients differ in both pretreatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pretreatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (lEUD) (conventional 'lEUD model'), the so-called perfusion-weighted lEUD (fEUD) (proposed 'fEUD model'), and post-treatment global liver function (GLF) (proposed 'GLF model'), predicted by a new liver-perfusion-based dose-response model. The resulting lEUD, fEUD, and GLF plans delivering the same target lEUD are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6%(7.5%) more liver function than the fEUD (lEUD) plan does in 2D cases, and up to 4.5%(5.6%) in 3D cases. The GLF and fEUD plans worsen in lEUD of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and often achieves better GLF than lEUD model optimization does, the GLF model directly optimizes a more clinically relevant metric and can further improve fEUD plan quality.