Adaptive Re-planning for Lung RT with Multi-targets

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1 Adaptive Re-planning for Lung RT with Multi-targets Feng Liu, An Tai, Ergun Ahunbay, Elizabeth Gore, Candice Johnstone, X. Allen Li Medical College of Wisconsin NCC AAMP, Madison, Oct. 11, 2013

2 Motivation: Lung RT w/ multi-targets Lung cancer: 2 nd morbidity(14%)/1 st mortality (27%) for cancer patients Inter-fractional variations affect accuracy of RT delivery Patient setup & anatomic variations (organ motion & deformation) IGRT repositioning to manage setup, intra-, and interfractional translation variations Disadvantage of IGRT: not fully take into account: organ deformation, rotation, relative motions between organs Leading to suboptimal target coverage and OAR sparing even for one target 2

3 Lung RT with Multi-targets Anatomy: 3D GTV contours in plan(red) and daily(brown) CTs Independent motion between different targets Target response to RT might vary: relative target volume variations More complex Online adaptive re-planning to account for interfractional variations 3

4 Online Adaptive Re-planning A full re-optimization ( >30 min) for daily treatment is too slow to be practical/qa requires intensive labor Fast re-planning methods: online adaptive to daily anatomy Workflow: min Approval MCW Image Acquisition via CT-on-Rails Contour generation (auto segmentation w/ manual editing) Dose/DVH evaluation and comparison 1 min 4 min Segment Aperture Morphing & Segment Weight Optimization 2 min New MLC transferred for treatment 1 min Medical College of Wisconsin Feng Liu 4

5 Method and Materials 7 lung cancer patients with two targets (either primary and nodes, or two independent lesions) treated with imageguided RT (CT-on-rail) 75 Daily CTs (randomly selected every consecutive few fractions) populated from the planning contours based on deformable registration (ABAS, Elekta) w/ manual editing Targets and OARs: GTV, CTV, PTV, lungs, heart, cord, and esophagus Quantities (daily and plan contours): Deviation of daily target displacement of the centers of masses (DCOM between two targets) from the plan: relative motion (non-zero Δ) 5

6 Method and Materials Dosimetry Original IMRT plan w/ Prowess panther General constraints: Three daily plans: PTV V100>95% cord Dmax<45 Gy V40Gy<100% Heart V45Gy<60% V60Gy<30% lung w/o GTV V20Gy<35% V5Gy<65% V35Gy<50% Esophagus V50Gy<40% V70Gy<20% 1. IGRT repositioning: copy of original plan unchanged (soft tissue) 2. Adaptive plan: tailoring the original plan to conform the anatomy of the daily CT 3. Re-optimization plan: new plan re-optimized based on the daily anatomy Same constraints as original IMRT plan applied for adaptive and re-opt plans. 6

7 Independent Target Motion Deviation of daily target DCOM from the plan 14 Range: (-10, 8) mm, mean: -0.7±4.5mm (SD), 30% fxw/ deviation >5mm Frequency Daily target DCOM deviation from the plans (cm) 7

8 Dosimetry: Adaptive vsrepositioning Adaptive: pt#1 (LT), better OAR sparing; pt#5 (RT) better target coverage & OAR sparing. 8

9 Dosimetry: Adaptive vsrepositioning Adaptive: better target coverage 9

10 Dosimetry: Adaptive vsrepositioning Adaptive: better OAR sparing 10

11 Summary There exist considerable independent motion between targets for lung RT w/ multi-targets. Online ART w/ organ and target deformation and relative independent motion taken into account maintains the Rx target coverage and provides better OAR sparing. Acknowledgements Partially supported by the MCW Cancer Center Fotsch Foundation Medical College of Wisconsin Feng Liu 11

12 Dosimetry: results Average dose-volume quantities quantity orignal plan repositioning adaptive reoptimization total PTV V100 (%) 95.2± ± ± ±0.7 larger PTV V100 (%) 94.9± ± ± ±0.9 smaller PTV V100 (%) 96.3± ± ± ±3.1 total CTV V100(%) 99.0± ± ± ±0.6 D99 (Rx) 1.007± ± ± ±0.018 larger CTV V100(%) 99.2± ± ± ±0.7 D99 (Rx) 1.005± ± ± ±0.015 smaller CTV V100(%) 100.0± ± ± ±1.3 D99 (Rx) 1.027± ± ± ±0.023 heart V45(cc) 28.3± ± ± ±30.4 esophagus V40(cc) 7.7± ± ± ±6.7 Lung V20(cc) 958.7± ± ± ±329.1 cord Dmax(Rx) 0.607± ± ± ±

13 Backup: ART QA procedure A multistep QA process: a thorough phantom measurement for the original plan an in-house software to double check monitor unit calculation, beam data transfer from the planning system to the delivery unit, and the delivered beam parameters Medical College of Wisconsin Feng Liu 13