Adaptive Deformable Registration And Fusion For Fractionated Stereotactic Radiosurgery Using A Small Animal Irradiator

To implement software-based image fusion and adaptive deformable registration to enable treatment planning for preclinical murine models of fractionated stereotactic radiosurgery (fSRS) using the Small Animal Radiation Research Platform (SARRP). C57BL6 mice underwent three unique cone-beam computed tomography (CBCT) scans: two in the prone position and a third supine. A single T1-weighted post-contrast Magnetic Resonance Imaging (MRI) series of a metastatic brain tumor was selected for MRI-to-CBCT registration and gross tumor volume (GTV) identification. Two arms were compared: Arm 1, where we performed three individual MRI-to-CBCT fusions using rigid registration, contouring GTVs on each, and Arm 2, where we performed MRI-to-CBCT fusion and contoured GTV on the first CBCT followed by software-based adaptive registration. The first CBCT and associated GTV were exported from dose planning software intoan imaging registration platform. The second and third CBCTs were exported similarly, along with associated GTVs (Arm 1). In Arm 2, the first (prone) CBCT was fused separately to the second (prone) and third (supine) CBCTs. Deformable registrations were performed on initial CBCTs, applying resulting matrices to the contoured GTV. Consistency of GTVs were compared between Arms 1 and 2. Comparing GTV overlays using repeated MRI fusion and GTV delineation (Arm 1) versus those of software-based CBCT and GTV adaptive fusion (Arm 2), mean deviations ± standard deviation in the axial, sagittal, and coronal planes were 0.46±0.16, 0.46±0.22, and 0.37±0.22 mm for prone-to-prone and 0.52±0.27, 0.52±0.36, and 0.68±0.31 mm for proneto-supine adaptive fusions, respectively. Adaptive fusion of CBCTs and contoured volumes allows for efficient fSRS planning using a single MRI-to-CBCT fusion. This technique can be immediately implemented on current SARRP systems, facilitating advanced preclinical treatment paradigms using existing clinical treatment planning software.