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--- planning:userguide:tutorials:finding_optimal_plan [2019/08/15 13:12] – dpatenaude
+++ planning:userguide:tutorials:finding_optimal_plan [2021/07/29 18:28] (current) – external edit 127.0.0.1
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-====== Astroid Optimization ======
+====== Astroid Optimization (PBS) ======
-With intensity modulated treatment plans the variety of possible dose distributions is quite large. Typically if a physician does not like a plan they will request it to be re-run. This requires the planner to input new constraints and objectives and a new plan to be run from the beginning of the optimization process. This is a time consuming process. Astroid eliminates this cycle using a Multi-Criteria Optimization (MCO) approach that allows planners and physicians to visualize the trade-offs of target volume coverage vs reduced dose to the OAR's in real time. MCO treatment planning is based on a set of Pareto optimized plans, where a plan is considered Pareto optimal if it satisfies all the constraints and none of the objectives can be improved without worsening at least one of the other objectives. So instead of creating just one plan, Astroid creates a set of optimal plans that satisfies the treatment plan constraints and puts an interactive exploration of the objectives at the planners and physicians fingertips via a unique, highly intuitive, solution navigation slider bar system.
+With intensity modulated PBS treatment plans the variety of possible dose distributions is quite large. Typically if a physician does not like a plan they will request it to be re-run. This requires the planner to input new constraints and objectives and a new plan to be run from the beginning of the optimization process. This is a time consuming process. Astroid eliminates this cycle using a Multi-Criteria Optimization (MCO) approach that allows planners and physicians to visualize the trade-offs of target volume coverage vs reduced dose to the OAR's in real time. MCO treatment planning is based on a set of Pareto optimized plans, where a plan is considered Pareto optimal if it satisfies all the constraints and none of the objectives can be improved without worsening at least one of the other objectives. So instead of creating just one plan, Astroid creates a set of optimal plans that satisfies the treatment plan constraints and puts an interactive exploration of the objectives at the planners and physicians fingertips via a unique, highly intuitive, solution navigation slider bar system.
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 {{ :planning:userguide:tutorials:mco_selection.png?400 |}}
+===== PBS Fraction Groups =====
+{{page>planning:userguide:tutorials:fraction_group&noheader}}
 ===== Optimization Constraints =====
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      * **Max Mean**: The maximum mean dose a structure may receive
       * This will limit the mean dose across the structure
-The user can choose to apply one or multiple of these constraints to any number of structure.
+     * **Overdose**: The maximum sum of the overdose that a structure may receive (//not available for ART3+O optimizer//)
+      * This will limit the total volume-weighted overdose (dose above a given threshold) that a structure receives, driving down hot spots
+     * **Underdose**: The maximum sum of the underdose that a structure may receive (//not available for ART3+O optimizer//)
+      * This will limit the total volume weighted underdose (dose below a given threshold) that a structures, driving up cold spots
+     * **Hot Spot Vol**: The maximum mean dose to the hottest portion of a structure (//not available for ART3+O optimizer//)
+      * This will keep the mean dose to the hottest portion of a structure below the given limit; portion is set as a % vol and the limit is the max mean dose allowed to that portion of the structure
+     * **Cold Spot Vol**: The minimum mean dose to the coldest portion of a structure (//not available for ART3+O optimizer//)
+      * This will keep the mean dose to the coldest portion of a structure above the given limit; portion is set as a % vol and the limit is the min mean allowed to that portion of the structure
+The user can choose to apply one or multiple of these constraints to any number of structures.
 ==== Working with Constraints ====
@@ Line 59: / Line 72: @@
 ===== Feasibility and Constraints =====
-After the //Constraints// have been entered, the user may start the //Feasibility// calculation by clicking //calculate// in the //Feasibility// block. The //Feasibility// calculation is based solely on the //constraints// and it should be used to ensure that is is possible to met the specified constraints. The //Feasibility// calculation may be an iterative processes in order to get appropriate constraints established for a particular plan. In other words, the user may need to enter one or more constraints, check the feasibility, then progressively tighten the constraints and re-check the feasibility until the plan is no longer feasible, then back-off to the last feasible values. It is recommended practice to start by obtaining a feasible plan utilizing only target //Constraints// then add OAR //Constraints// as desired. Remember, using a narrow range of constraints can improve the optimizer performance and improve the resolution of the solution navigation.
+After the //Constraints// have been entered, the user may start the //Feasibility// calculation by clicking //calculate// in the //Feasibility// block. The //Feasibility// calculation is based solely on the //constraints// and, it should be used to ensure that it is possible to meet the specified constraints. The //Feasibility// calculation may be an iterative processes in order to get appropriate constraints established for a particular plan. In other words, the user may need to enter one or more constraints, check the feasibility, then progressively tighten the constraints and re-check the feasibility until the plan is no longer feasible, then back-off to the last feasible values. It is recommended practice to start by obtaining a feasible plan utilizing only target //Constraints// then add OAR //Constraints// as desired. Remember, using a narrow range of constraints can improve the optimizer performance and improve the resolution of the solution navigation.
 The user also needs to be aware of the impact of //Constraints// being set at the //Fraction Group// level versus the //Plan// level. For example, it is possible to have a //Constraint// set in the //Plan// level so that the whole dose to an OAR is given on one day and none on the other day. This could happen when there are two //Fraction Groups// and the OAR dose is not split between the two by using Fraction Group level constraints.
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       * Dose will be driven up only until the specified limit is reached (this is often more relevant that max_min, since it may not be beneficial to continue maximizing beyond a certain dose level)
 <WRAP 920px center><WRAP left>[{{ :planning:userguide:tutorials:objectives_min_over.png?390 | min_overdose: Minimize the high dose}}]</WRAP><WRAP right>[{{ :planning:userguide:tutorials:objectives_min_under.png?390 | min_underdose: Minimize the low dose}}]</WRAP></WRAP><WRAP clear></WRAP>
+    * **min_hot_spot**: Minimize the mean dose to the hottest portion of a structure (//not available for ART3+O optimizer//)
+      * The mean dose to the hottest portion of a structure will be driven down (i.e. the tail dose on the DVH); portion is set as a % vol of the structure
+    * **min_cold_spot**: Maximize the mean dose to the coldest portion of a structure (//not available for ART3+O optimizer//)
+      * The mean dose to the coldest portion of a structure will be driven up (i.e. the shoulder dose on the DVH); portion is set as a % vol of the structure
 ==== Working with Objectives ====