Abstract
A rat glioblastoma model to mimic chemo-radiation treatment of human glioblastoma in the clinic was previously established. Similar to the clinical treatment, computed tomography (CT) and magnetic resonance imaging (MRI) were combined during the treatment-planning process. Positron emission tomography (PET) imaging was subsequently added to implement sub-volume boosting using a micro-irradiation system. However, combining three imaging modalities (CT, MRI, and PET) using a micro-irradiation system proved to be labor-intensive because multimodal imaging, treatment planning, and dose delivery have to be completed sequentially in the preclinical setting. This also results in a workflow that is more prone to human error. Therefore, a user-friendly algorithm to further optimize preclinical multimodal imaging-based radiation treatment planning was implemented. This software tool was used to evaluate the accuracy and efficiency of dose painting radiation therapy with micro-irradiation by using an in silico study design. The new methodology for dose painting radiation therapy is superior to the previously described method in terms of accuracy, time efficiency, and intra- and inter-user variability. It is also an important step towards the implementation of inverse treatment planning on micro-irradiators, where forward planning is still commonly used, in contrast to clinical systems.
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