Mechanically assisted non-invasive ventilation for liver SABR: Improve CBCT, treat more accurately.

Pierrard, Julien;Audag, Nicolas;Abdel Massih, Christel;Garcia, Maria Alvear;Van Ooteghem, Geneviève;et.al.
(2025) Clinical and Translational Radiation Oncology — Vol. 53, p. 100983 [1-8] (2025)

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Authors
  • Pierrard, Julienorcid-logoUCLouvain
    Author
  • Audag, NicolasUCLouvain
    Author
  • Abdel Massih, ChristelUCLouvain
    Author
  • Garcia, Maria AlvearUCLouvain
    Author
  • Moreno, Enrique AlvarezUCLouvain
    Author
  • Colot, AndréaUCLouvain
    Author
  • Jardinet, SimonUCLouvain
    Author
  • Mony, RomainUCLouvain
    Author
  • Nevez Marques, Ana FranciscaUCLouvain
    Author
  • Servaes, LolaUCLouvain
    Author
  • Tison, ThaïsUCLouvain
    Author
  • Van den Bossche, ValentinUCLouvain
    Author
  • Aniko Wale Etume, AnnieUCLouvain
    Author
  • Zouheir, LamyaeUCLouvain
    Author
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Abstract
BACKGROUND AND PURPOSE: Cone-beam computed tomography (CBCT) for image-guided radiotherapy (IGRT) during liver stereotactic ablative radiotherapy (SABR) is degraded by respiratory motion artefacts, potentially jeopardising treatment accuracy. Mechanically assisted non-invasive ventilation-induced breath-hold (MANIV-BH) can reduce these artefacts. This study compares MANIV-BH and free-breathing CBCTs regarding image quality, IGRT variability, automatic registration accuracy, and deep-learning auto-segmentation performance. MATERIALS AND METHODS: Liver SABR CBCTs were presented blindly to 14 operators: 25 patients with FB and 25 with MANIV-BH. They rated CBCT quality and IGRT ease (rigid registration with planning CT). Interoperator IGRT variability was compared between FB and MANIV-BH. Automatic gross tumour volume (GTV) mapping accuracy was compared using automatic rigid registration and image-guided deformable registration. Deep-learning organ-at-risk (OAR) auto-segmentation was rated by an operator, who recorded the time dedicated for manual correction of these volumes. RESULTS: MANIV-BH significantly improved CBCT image quality ("Excellent"/"Good": 83.4 % versus 25.4 % with FB, p < 0.001), facilitated IGRT ("Very easy"/"Easy": 68.0 % versus 38.9 % with FB, p < 0.001), and reduced IGRT variability, particularly for trained operators (overall variability of 3.2 mm versus 4.6 mm with FB, p = 0.010). MANIV-BH improved deep-learning auto-segmentation performance (80.0 % rated "Excellent"/"Good" versus 4.0 % with FB, p < 0.001), and reduced median manual correction time by 54.2 % compared to FB (p < 0.001). However, automatic GTV mapping accuracy was not significantly different between MANIV-BH and FB. CONCLUSION: In liver SABR, MANIV-BH significantly improves CBCT quality, reduces interoperator IGRT variability, and enhances OAR auto-segmentation. Beyond being safe and effective for respiratory motion mitigation, MANIV increases accuracy during treatment delivery, although its implementation requires resources.
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Citations

Pierrard, J., Audag, N., Abdel Massih, C., Garcia, M. A., Moreno, E. A., Colot, A., Jardinet, S., Mony, R., Nevez Marques, A. F., Servaes, L., Tison, T., Van den Bossche, V., Aniko Wale Etume, A., Zouheir, L., & Van Ooteghem, G. (2025). Mechanically assisted non-invasive ventilation for liver SABR: Improve CBCT, treat more accurately. Clinical and Translational Radiation Oncology, 53, 100983 [1-8]. https://doi.org/10.1016/j.ctro.2025.100983 (Original work published 2025)