Velocity-based Adaptive Registration and Fusion for Fractionated Stereotactic Radiosurgery Using the Small Animal...

Area of Science:

• Medical Physics
• Radiotherapy
• Preclinical Research

Background:

• Fractionated stereotactic radiosurgery (fSRS) requires precise image guidance for preclinical murine models.
• Current methods for image fusion and registration in small animal radiation research platforms (SARRP) can be complex.
• Accurate delineation of gross tumor volume (GTV) is critical for effective radiation treatment planning.

Purpose of the Study:

• To implement Velocity-based image fusion and adaptive deformable registration for fSRS treatment planning in preclinical murine models.
• To evaluate the efficiency and accuracy of this technique using the SARRP system.

Main Methods:

• Three cone beam computed tomography (CBCT) scans were acquired from C57BL6 mice (two prone, one supine).
• T1-weighted post-contrast MRI was used for MRI-to-CBCT registration and GTV identification.
• Two arms were compared: Arm 1 (rigid registration, multiple fusions) and Arm 2 (Velocity-based adaptive registration on a single fusion).

Main Results:

• Mean deviations for GTV overlays were minimal in both prone-to-prone (0.46 ± 0.16 mm axial) and prone-to-supine (0.52 ± 0.27 mm axial) adaptive fusions.
• Velocity-based adaptive fusion demonstrated comparable accuracy to repeated rigid fusions.
• The adaptive approach simplifies the workflow for GTV delineation and fusion.

Conclusions:

• Velocity-based adaptive fusion of CBCTs and contoured volumes enables efficient fSRS planning with a single MRI-to-CBCT fusion.
• This technique is readily implementable on existing SARRP systems.
• Facilitates advanced preclinical treatment paradigms using established clinical treatment planning software.