Program Information
Auto-Adaptive Margin Generation for MLC-Tracked Radiotherapy
M Glitzner1*, M Fast2 , B Denis de Senneville1,3 , S Nill2 , U Oelfke2 , J Lagendijk1 , B Raaymakers1 , S Crijns1 , (1) University Medical Center Utrecht, Utrecht, The Netherlands, (2) The Institute of Cancer Research, London, UK, (3) IMB, UMR 5251 CNRS/University of Bordeaux, Talence, France
Presentations
TH-AB-202-4 (Thursday, August 4, 2016) 7:30 AM - 9:30 AM Room: 202
Purpose: To develop an auto-adaptive margin generator for MLC tracking. The generator is able to estimate errors arising in image guided radiotherapy, particularly on an MR-Linac, which depend on the latencies of machine and image processing, as well as on patient motion characteristics. From the estimated error distribution, a segment margin is generated, able to compensate errors up to a user-defined confidence.
Method: In every tracking control cycle (TCC, 40ms), the desired aperture D(t) is compared to the actual aperture A(t), a delayed and imperfect representation of D(t). Thus an error e(t)=A(T)-D(T) is measured every TCC. Applying kernel-density-estimation (KDE), the cumulative distribution (CDF) of e(t) is estimated. With CDF-confidence limits, upper and lower error limits are extracted for motion axes along and perpendicular leaf-travel direction and applied as margins. To test the dosimetric impact, two representative motion traces were extracted from fast liver-MRI (10Hz). The traces were applied onto a 4D-motion platform and continuously tracked by an Elekta Agility 160 MLC using an artificially imposed tracking delay. Gafchromic film was used to detect dose exposition for static, tracked, and error-compensated tracking cases. The margin generator was parameterized to cover 90% of all tracking errors. Dosimetric impact was rated by calculating the ratio between underexposed points (>5% underdosage) to the total number of points inside FWHM of static exposure.
Results: Without imposing adaptive margins, tracking experiments showed a ratio of underexposed points of 17.5% and 14.3% for two motion cases with imaging delays of 200ms and 300ms, respectively. Activating the margin generated yielded total suppression (<1%) of underdosed points.
Conclusion: We showed that auto-adaptive error compensation using machine error statistics is possible for MLC tracking. The error compensation margins are calculated on-line, without the need of assuming motion or machine models. Further strategies to reduce consequential overdosages are currently under investigation.
Funding Support, Disclosures, and Conflict of Interest: This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution
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