Physics and imaging in radiation oncology · 2025
Automated target misalignment correction for cone beam computed tomography-based online adaptive radiotherapy of locally advanced lung cancer patients.
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Seller-Oria Carmen, van Beek Suzanne, Gerrets Suzan, van Weerdenburg Sanne, Bos Paula, van Kranen Simon, Frantzen-Steneker Marloes, Gouw Zeno, Sonke Jan-Jakob, Remeijer Peter
Аннотация
BACKGROUND AND PURPOSE: Locally advanced lung cancer patients are commonly treated with daily cone beam CT (CBCT) guided radiotherapy using one treatment isocenter. Due to differential motion between primary tumor (GTVprim) and affected lymph nodes, a compromise needs to be made during daily patient alignment, requiring enlarged treatment margins. In this work, an online adaptive (OART) strategy was proposed to correct for residual target misalignments and enable treatment margin reduction.
MATERIAL AND METHODS: We developed in-house an application that produced a synthetic CT (sCT) and delineations to correct for residual target misalignments. A deformation vector field (DVF) was created by using conventional CBCT-to-CT rigid target registrations. The DVF was applied to the planning CT (pCT) and delineations to generate a sCT where GTVprim was loco-rigidly shifted into the correct position. Twenty CBCTs of eight patients were selected to assess sCTs in terms of GTVprim position (via CBCT-to-sCT and CBCT-to-pCT registration vector lengths), pixel-wise sCT-pCT Hounsfield unit (HU) errors inside GTVprim, and sCT-pCT GTVprim volume differences.
RESULTS: Median vector lengths were 5.1 mm relative to pCTs, and 0.7 mm relative to sCTs, demonstrating the ability of the proposed tool to correct residual misalignments. Median HU errors across all scans were within 1 HU, and the median GTVprim volume difference was -3.7 %.
CONCLUSIONS: A correction method for residual target misalignments in locally advanced lung cancer patients was proposed. It automatically produces sCTs and delineations, enabling OART implementation without the need for manual delineation corrections, and with potentially smaller treatment margins.
MATERIAL AND METHODS: We developed in-house an application that produced a synthetic CT (sCT) and delineations to correct for residual target misalignments. A deformation vector field (DVF) was created by using conventional CBCT-to-CT rigid target registrations. The DVF was applied to the planning CT (pCT) and delineations to generate a sCT where GTVprim was loco-rigidly shifted into the correct position. Twenty CBCTs of eight patients were selected to assess sCTs in terms of GTVprim position (via CBCT-to-sCT and CBCT-to-pCT registration vector lengths), pixel-wise sCT-pCT Hounsfield unit (HU) errors inside GTVprim, and sCT-pCT GTVprim volume differences.
RESULTS: Median vector lengths were 5.1 mm relative to pCTs, and 0.7 mm relative to sCTs, demonstrating the ability of the proposed tool to correct residual misalignments. Median HU errors across all scans were within 1 HU, and the median GTVprim volume difference was -3.7 %.
CONCLUSIONS: A correction method for residual target misalignments in locally advanced lung cancer patients was proposed. It automatically produces sCTs and delineations, enabling OART implementation without the need for manual delineation corrections, and with potentially smaller treatment margins.