The plan quality scoring builds upon the previously established formalism (5) which is based on defining a collection of specific metrics (which can be DVH points, conformality indices, etc.) and corresponding score functions for each. Each metric's score function translates the achieved value to a numerical score. The sum over all metric scores divided by the combined maximum possible constitutes a composite PQM (%), used as a proxy for the overall achieved plan quality. The individual score functions are generally designed to define a failure region (where the score is zero), a transition region between the minimally acceptable and the ideal achievements (where the score increases from zero to the maximum), and the region exceeding the ideal (where the maximum score is awarded). Once the quality algorithm is defined, the analysis is automated and devoid of observer bias. However, it is important to understand that the metric scores inevitably carry a degree of subjectivity when used in aggregate, for a composite PQM. It is fundamentally unavoidable when attempting to quantify the relative importance of different clinical priorities. On the other hand, an individual metric score (rendered as percentage of the maximum possible) is used to compare only that specific achievement for the single ROI across the plans, and thus is devoid of “relative importance” subjectivity.