  With many variables to adjust, conventional manual forward planning for Gamma
Knife (GK) radiosurgery is very complicated and cumbersome. The resulting plan
quality heavily depends on planners skills, experiences and devoted efforts,
and varies significantly among cases, planners, and institutions. Quality
control for GK planning is desired to consistently provide high-quality plan to
each patient. In this study, we proposed a quality control method for GK
planning by building a database of high-quality GK plans. Patient anatomy was
described by target volume, target shape complexity, and spatial relationship
between target and nearby organs, which determine GK planning difficulty level.
Plan quality was evaluated using target coverage, selectivity, intermediate
dose spillage, maximum dose to 0.1 cc of brainstem, mean dose of ipsilateral
cochlea, and beam-on time. When a new plan is created, a high-quality plan that
has the most similar target volume size and shape complexity will be identified
from the database. A model has also been built to predict the dose to brainstem
and cochlea based on their overlap volume histograms. The identified reference
plan and the predicted organ dose will help planners to make quality control
decisions accordingly. To validate this method, we have built a database for
vestibular schwannoma, which are considered to be challenging for GK planning
due to the irregularly-shaped target and its proximity to brainstem and
cochlea. Five cases were tested, among which one case was considered to be of
high quality and four cases had a lower plan quality than prediction. These
four cases were replanned and got substantially improved. Our results have
demonstrated the efficacy of our proposed quality control method. This method
may also be used as a plan quality prediction method to facilitate the
development of automatic treatment planning for GK radiosurgery.
