Finite Element Method-Based Hybrid MRI/CBCT Generation to Improve Liver Stereotactic Body Radiation Therapy Targets Localization Accuracy

Abstract

Cone-beam CT (CBCT) is commonly used in treatment imaging, but its limited soft tissue contrast presents challenges for liver tumor localization. As a result, indirect localization methods relying on the liver’s boundary are commonly utilized, which have limited accuracy for tumor localization. On-board MRI offers superior soft tissue contrast but is limited by the cost. To address this, we devised a method to generate onboard virtual MRI by integrating pretreatment MRI with onboard CBCT, enhancing liver stereotactic body radiation therapy (SBRT) tumor localization accuracy. We employed a finite element method (FEM) for deformable mapping, deforming prior liver MR images onto CBCT geometry to create a virtual MRI. This hybrid virtual-MRI/CBCT (hMRI-CBCT) approach was evaluated in a pilot study involving 48 patients. The hMRI-CBCT demonstrated superb soft-tissue contrast with clear tumor visualization. Registration accuracy of hMRI-CBCT to planning CT significantly surpasses the onboard CBCT to planning CT registration, particularly for tumors not near the liver boundary, with an average error reduction of $1.53~\pm ~2$ .16 mm. Our study demonstrated that hybrid MRI/CBCT can apparently reduce localization errors in liver SBRT, potentially improving tumor control and reducing toxicities, and opening avenues for further margin reduction and dose escalation.