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Updated: Sep 22, 2025
Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
Published on: November 23, 2019
A novel bone suppression algorithm in intensity-based 2D/3D image registration for real-time tumor motion monitoring:
Ingo Gulyas1, Petra Trnkova1, Barbara Knäusl1,2
1Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria.
Background:
Real-time tumor motion monitoring (TMM) is a crucial process for intra-fractional respiration management in lung cancer radiotherapy. Since the tumor can be partly or fully located behind the ribs, the TMM is challenging.
Purpose:
The aim of this work was to develop a bone suppression (BS) algorithm designed for real-time 2D/3D marker-less TMM to increase the visibility of the tumor when overlapping with bony structures and consequently to improve the accuracy of TMM.
Method:
A BS method was implemented in the in-house developed software for ultrafast intensity-based 2D/3D tumor registration (Fast Image-based Registration [FIRE]). The method operates on both, digitally reconstructed radiograph (DRR) and intra-fractional X-ray images. The bony structures are derived from computed tomography data by thresholding during ray-casting, and the resulting bone DRR is subtracted from intra-fractional X-ray images to obtain a soft-tissue-only image for subsequent tumor registration. The accuracy of TMM utilizing BS was evaluated within a retrospective phantom study with nine different 3D-printed tumor phantoms placed in the in-house developed Advanced Radiation DOSimetry (ARDOS) breathing phantom. A 24 mm craniocaudal tumor motion, including rib eclipses, was simulated, and X-ray images were acquired on the Elekta Versa HD Linac in the lateral and posterior-anterior directions. An error assessment for BS images was evaluated with respect to the ground truth tumor position.
Results:
A total error (root mean square error) of 0.87 ± 0.23 mm and 1.03 ± 0.26 mm was found for posterior-anterior and lateral imaging; the mean time for BS was 8.03 ± 1.54 ms. Without utilizing BS, TMM failed in all X-ray images since the registration algorithm focused on the rib position due to the predominant intensity of this tissue within DRR and X-ray images.
Conclusion:
The BS algorithm developed and implemented improved the accuracy, robustness, and stability of real-time TMM in lung cancer in a phantom study, even in the case of rib interlude where normal tumor registration fails.
