HN-SIB-BPI: A single click, sub-site specific, dosimetric scorecard tuned RapidPlan model created from a foundation model for treating head and neck with bilateral neck.

To develop a Knowledge Based Planning (KBP) model for creating quantifiably high quality VMAT treatment plans in a single click for head and neck cases treated Simultaneous Integrated Boost (SIB) with bilateral parotid involvement (BPI) where both parotids are near, abutting or partially overlapping target volume. Eclipse RapidPlan and the publicly available PlanScorecard tool were used to assess existing Head and Neck RapidPlan models on two representative cases. The best performer was used as a foundation model to assist in creating new initial training set doses from previously treated cases. Those initial 27 cases were first replanned using only the selected foundation model, then further improved based on manual replanning, informed by dosimetric scorecard assessment. A new, initial model was trained from those 27 foundation model created cases that had been manually improved. Then, that initial model was used to replan those cases again, resulting in higher scores. Additional cases were also replanned using the initial model along with some manual changes to the optimization objectives to increase the score. This resulted in a total of 66 cases from which the final, released, HN-SIB-BPI was trained. A 27 case subset of the full training set was replanned and rescored at each phase of the process with a 260 total point 3-target scorecard. The average score increased: 210.5 foundation model; 226.96 manually improved plans; 230.1 initial model; 231.7 HN-SIB-BPI. On the same 27 case subset, mean ipsilateral and contralateral parotid dose decreased by 1.05Gy and 1.58Gy respectively from the foundation model to HN-SIB-BP. Eight external cases were created from HN-SIB-BPI with dosimetric scorecard validation on Halcyon (3-PTV:221.38/260; 2-PTV:196.1/228.5) and TrueBeam (3-PTV:222.01/260; 2-PTV:202.24/228.5). A specific clinical intent (ie: max parotid sparing) can be articulated in a comprehensive and precise manner by creating a dosimetric scorecard with individual metrics points assigned to each OAR and target metric reflecting their relative importance. This process improved the KBP model (HN-SIB-BPI) in several quantifiable ways including further sparing of parotid dose. All results and tools in this work are shared publicly.