Simultaneous optimization of non-coplanar beam orientations and cumulative EQD2 distribution for high-dose reirradiation of locoregionally recurrent non-small cell lung cancer
Nathan Torelli, Jonas Willmann, Katja Daehler, Madalyne Day, Nicolaus Andratschke, Jan Unkelbach

TL;DR
This study introduces a novel beam orientation optimization algorithm for reirradiation of recurrent NSCLC, enabling better sparing of critical organs by selecting favorable non-coplanar beam angles, compared to traditional coplanar plans.
Contribution
The paper presents a new algorithm for simultaneous optimization of non-coplanar beam orientations and cumulative EQD2 distribution in reirradiation planning for NSCLC, improving organ-at-risk sparing.
Findings
Non-coplanar plans reduced maximum EQD2 to critical OARs by at least 5 Gy2 in 6 of 15 cases.
Target coverage and lung EQD2 metrics were comparable between non-coplanar and coplanar plans.
Automated non-coplanar beam selection can potentially improve reirradiation safety and efficacy.
Abstract
Background and Purpose: Reirradiation for non-small cell lung cancer (NSCLC) is commonly delivered using coplanar techniques. In this study, we developed a beam orientation optimization algorithm for reirradiation planning to investigate whether the selection of favorable non-coplanar beam orientations may limit cumulative doses to critical organs-at-risk (OARs) and thus improve the therapeutic window. Materials and Methods: Fifteen cases of challenging high-dose reirradiation for locoregionally recurrent NSCLC were included in this in-silico study. For each patient, the dose distribution from the previous treatment was first mapped to the reirradiation planning CT using rigid dose registration, and subsequently converted to equivalent dose in 2 Gy fractions (EQD2). A 2-arc non-coplanar reirradiation plan, combining dynamic gantry and couch rotation, was then generated using an…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
