Using organ similarity metric to determine optimization strategy in adaptive radiation therapy

A method for adapting a preliminary radiation treatment plan for a current treatment session of an adaptive radiation therapy session, comprising:

• obtaining a set of directives including plan quality values of a preliminary treatment plan for the patient;
• using the set of directives to perform a series of automated steps to generate a current treatment session patient model;
• determine a similarity metric between target structures of the current treatment session patient model and corresponding target structures of a plurality of previously obtained treatment session patient models;
• determine the previously obtained treatment session patient model that has the highest similarity metric value;
• and
• generate an adapted treatment plan for the current treatment session patient model by:
• using the preliminary treatment plan as input to a treatment plan generation algorithm to generate a current plan,
• the treatment plan generation algorithm including optimization parameters generated based on control points automatically selected based on the determined similarity metrics;
• and
• generating the adapted treatment plan by optimizing the current plan based on the plan quality values of the preliminary treatment plan,
• wherein the control points include MLC leaf configurations, and
• wherein a standard MLC leaf configuration is selected when the highest similarity metric value is below a predetermined threshold, and
• an MLC leaf configuration of a treatment plan of the previous treatment session patient model having the highest similarity metric value is selected when the highest similarity metric value is above the predetermined threshold.

A system for implementing an automated workflow for an adaptive radiation therapy session of a patient, comprising:

• a computer processing system configured to:
• obtaining a set of directives including plan quality values of a preliminary treatment plan for the patient;
• and
• using the set of directives, perform a series of automated steps to:
• generate a current treatment session patient model;
• and
• generate an adapted treatment plan for the treatment session patient model by:
• using the preliminary treatment plan as input to a treatment plan generation algorithm to generate a current plan,
• optimizing the current plan based on optimization parameters generated based on control points selected based on a similarity metrics determined between target structures of the current treatment session patient model and corresponding target structures of either a planned patient model or one or more previously obtained treatment session patient models,
• wherein the control points include MLC leaf configurations, and
• wherein a standard MLC leaf configuration is selected when the highest similarity metric value is below a predetermined threshold, and
• an MLC leaf configuration of a treatment plan of the previous treatment session patient model having the highest similarity metric value is selected when the highest similarity metric value is above the predetermined threshold.