THE DOSIMETRIC EFFECTS OF OPTIMIZATION TECHNIQUES IN IMRT/IGRT PLANNING 1 Multiple PTV Head and Neck Treatment Planning, Contouring, Data, Tips, Optimization Techniques, and algorithms AAMD 2013, San Antonio, TX
OUTLINE Overview of contouring techniques for IMRT Description of Head and Neck (H&N) cases Scanning Contouring Common prescriptions Treatment planning Conclusions 2
CONCERNS WITH MULTIPLE PTV H&N PLANNING Multiple PTV with different prescriptions but the same isocenter and very close to each other Dose to critical structures Part of parotids included in the PTV Brainstem Spinal cord Mandible Placement of beams very important Skin reactions Artifacts Lips 3
WELLINGTON REGIONAL CANCER CENTER H&N TREATMENT PLANNING Larynx Floor of mouth Base of tongue Tonsils Base of tongue Glottis 4
WELLINGTON REGIONAL CANCER CENTER SIMULATION PROCEDURES Supine Head mask Big bore CT 2 mm thickness One per each PTV Scan top of head and 3 cm below the shoulders PET registered with CT 5
CONTOURING STRATEGY CTV high risk: tumor + microscopic CTV intermediate risk: active nodes on PET CTV low risk: non active nodes in the same area PTV: high risk, intermediate risk, low risk, 5 mm margin to CTV PTV optimization (PTV-opt) Expand the PTV 1-2 slices sup-inf and make it type PTV One per each PTV Using the crop function move the PTV-opt 0.5 cm away from the skin inside the body PTV total optimization (PTV-tot-opt) Union of the three just for generating the ring or R90 Artifacts 6
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CONTOURING HELPFUL STRUCTURES Ring Expand the PTV-tot-opt with 1-1.2 cm (depending on the distance to the skin) Again crop away from the skin with 0.3 cm No dose zone (Nodose) Area surrounding the Ring a few cm sup and inf Crop away from the skin 0.2 cm inside the body Impose restriction on not exceeding 50% of the prescribed dose 8
CONTOURING HELPFUL STRUCTURES Subtract the Ring from Nodose structure Crop the PTV-tot-opt from Ring leaving a 2 mm space between them Organs at risk (OAR) If highly important (Parotids) and in proximal location to PTV add 2 mm margins to a OAR making a planning OAR. Make a new structure from Planning OAR subtracting the part that overlaps with the PTV (Parotid-PTV) Subtract the new structure of OAR from the Ring 9
PLACING THE BEAMS Dose prescribed to the PTV high Use only 6 MV For a very large and toll PTV use 9 fields Avoid an AP field to minimize the dose to the lips Use a PA field to help protecting the cord If the PTV is symmetrical in the head-neck area distribute the beams symmetrically. If the PTV is placed on one side of the head-neck region choose an area in the middle of the PTV and place one beam then distribute the rest of the 1 0 beams at equal angles every 25 0-30 0.
PLACING THE BEAMS Dose prescribed to the PTV high Use only 6 MV Use 7-9 fields Place isocenter in the PTV-tot center Watch the shoulders Kick couch if needed 1 1
NINE BEAMS WITH AP EIGHT BEAMS NO AP 12
OPTIMIZATION GOALS No hot spot over 108% of the PTV high risk dose Minimal large areas of 105% Proper PTV high risk, PTV intermediate risk, and PTV low risk coverage Minimize parotids, brainstem, and spinal cord dose Reduce hotspots near the skin Minimize skin and mandible dose 13
WRCC PRACTICE GUIDELINES PLANNING MINIMUM DVH REQUIREMENTS Head & Neck radiation therapy 100 of the PTV high risk receives 95% of prescribed dose Similar for the PTV intermediate and low risk Normal structures (Quantec) Parotids Bilateral: mean dose < 25 Gy Unilateral: mean dose < 20 Gy Brainstem Maximum dose < 54 Gy D10cc < 59 Gy Larynx Mean dose < 50 Gy V50 < 27% 14
Trilogy machine 6 & 18 MV photons EQUIPMENT Multi-leaf collimators with 0.5 cm and 1 cm leaves Eclipse 8.6 IMRT Planning AAA algorithm for dose calculation Optimization (not used for beam placement) Fluence editing 15
Start by excluding all the structures that will not need constraints Change the Body s resolution to a 10 Use normal tissue objectives OPTIMIZATION 1 6
OPTIMIZATION Each of the PTV-opt will receive 2 upper and 2 lower constraints Ring will receive one upper constraint: 0.1% of the volume to receive maximum 90% of the PTV intermed risk dose Nodose will receive one upper constraint: 0.1% of the volume to receive a maximum of 50% of the prescribed dose 1 7
DOSE DISTRIBUTION 18
RESULTS 1 9
DVH ANALYSIS 2 0
IMRT planning CONCLUSIONS Is as good as the segmentation is As good as the beam placement As good as the dosimetrist talents in optimization Can take a long time for complex treatments Fluence editing is required in the majority of the plans It will be great if we could find the perfect algorithm to place the beams according to the constraints and to optimize the plan such that no fluence editing is needed 21
TUMOR CONTROL OR TISSUE COMPLICATIONS? Tissue Control Probability (TCP) increases with dose, while Normal Tissue Complication Probability (NTCP) also increases with dose. 2
ALGORITHMS CURRENTLY USED IN ECLIPSE Anisotropic Analytical Algorithm (AAA) 3D pencil beam that calculates dose from primary and scattered photons Plan Geometry Optimization (PGO) Selects the best beams to use for Beam Angle Optimization (BAO) using the same algorithm as the Dose Volume Optimization (DVO) DVO is an iterative process to shape the beam based on constraints 23
ANISOTROPIC ANALYTICAL ALGORITHM (AAA) Calculate the dose at a point Uses pencil beams of the energy spectrum to determine primary and scatter dose Can use heterogeneity corrections 24 Source: Varian Eclipse Algorithm Reference Guide
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CONSTRAINTS Dose constraints PTV constraints Penalize if dose is above or below 100% of the prescription OAR constraints Penalize if dose is above tissue toxicity levels Normal tissue constraints Minimize dose to normal tissue Minimize scoring function 27
SCORING FUNCTION 28
SCORING FUNCTION 2
SCORING FUNCTION Advantage of this: Easy to implement Simple parameter S to evaluate a plan Disadvantages: Does not try to do better than constraints Optimization may not be biologically effective
MODIFICATION TO SCORING FUNCTION Exponentially decaying
MODIFICATION TO SCORING FUNCTION The exponential decay gives the plan the ability to do better than what is set Decay can be adjusted to have a sharp or slow drop Has not been implemented yet 3
BEAM ANGLE OPTIMIZATION Beam Angle Optimization is currently employed in Eclipse, although the feature is rarely used at our center due to poor results. The method places between 71 and 400 beams uniformly around the patient. The beams are selectively chosen based an iterative process known as Plan Geometry Optimization (PGO) that evaluates the plan and deletes the lowest weighted beam. The plan is then evaluated again and the process continues until a minimum of beams is reached. 3
BEAM ANGLE OPTIMIZATION 34
FACTORS TO CONSIDER Gantry angle separation should be >25 0 Collimator angle Increases treatment time for more angles used Monitor Units (MU) Dose to OAR, PTV and normal tissue Number of beams Couch angles 3
SIMULATED ANNEALING Ability to minimize a function Can escape a local minimum and search for absolute minimum. Each iteration is evaluated against the previous. If it is lower, it is accepted with probability 1. If it is higher, it is accepted with an exponential probability. Source: Institut fur Angewandte Stochastik und Operations Research
MONTE CARLO At least 2000 points are placed in each ROI A monte carlo simulation of the beams is run and dose at each point is calculated A change in a beam will affect every voxel Leakage is taken into consideration 3
BEAM ANGLES Automatic Manual 38
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DOSE VOLUME HISTOGRAM End result will be a Dose Volume Histogram that can be evaluated by the dosimetrist, physicist and physician. The DVH shows the corresponding dose to the structures that were contoured. An ideal case will have the tumor site receive a uniform prescribed dose (100% of the dose to 100% of the volume) while the dose to organs and normal tissue be minimized. 4
AUTOMATED PLANNING WITH BAO AND DVO 4
MANUAL PLANNING 4
COMPARISON 4
CONCLUSIONS Optimization algorithms hold the key to improved dosimetry Faster planning times Better coverage Less dose to organs at risk Using existing plans can be implemented to algorithms to look for solutions 44
REFERENCES Advance Radiation Physics Inc. FL, Boca Raton. Performance. Varian. Eclipse Algorithms Refence Guide. N.p.: n.p., July-Aug. 2008. PDF. Mills, Albert. "Algorithm for Correcting Optimization Convergence Errors in Eclipse." Journal of Applied Clinical Medical Physics 10.4 (2009): 281-85. 45