机械辅助无创通气治疗肝脏SABR：提高CBCT，治疗更准确

IF 2.7 3区医学 Q3 ONCOLOGY

Clinical and Translational Radiation Oncology Pub Date : 2025-05-22 DOI:10.1016/j.ctro.2025.100983

Julien Pierrard , Nicolas Audag , Christel Abdel Massih , Maria Alvear Garcia , Enrique Alvarez Moreno , Andrea Colot , Simon Jardinet , Romain Mony , Ana Francisca Nevez Marques , Lola Servaes , Thaïs Tison , Valentin Van den Bossche , Aniko Wale Etume , Lamyae Zouheir , Geneviève Van Ooteghem

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引用次数: 0

摘要

背景与目的在肝脏立体定向消融放疗（SABR）过程中，用于图像引导放疗（IGRT）的二束计算机断层扫描（CBCT）会受到呼吸运动伪影的影响，可能危及治疗的准确性。机械辅助无创通气诱导屏气（MANIV-BH）可以减少这些伪影。本研究比较了MANIV-BH和自由呼吸cbct在图像质量、IGRT可变性、自动配准精度和深度学习自动分割性能方面的差异。材料和方法对14例患者进行盲测，其中25例为FB患者，25例为MANIV-BH患者。他们评估了CBCT的质量和IGRT的易用性（与计划CT的严格注册）。比较FB和MANIV-BH之间的操作员间IGRT变异性。使用自动刚性配准和图像引导的可变形配准比较自动总肿瘤体积（GTV）映射精度。操作员对深度学习风险器官（OAR）自动分割进行了评分，并记录了用于手动校正这些体积的时间。结果maniv - bh显著改善了CBCT图像质量(“优”/“好”：83.4%，而FB， p <；0.001)，促进IGRT(“非常容易”/“容易”：68.0%，而FB为38.9%,p <；0.001)，并降低了IGRT变异性，特别是对于训练有素的操作员（总体变异性为3.2 mm，而FB为4.6 mm, p = 0.010）。MANIV-BH提高了深度学习的自动分割性能(80.0%的评分为“优秀”/“良好”，而FB的评分为4.0%,p <；0.001)，与FB相比，中位人工校正时间减少了54.2% (p <；0.001)。MANIV-BH与FB的自动GTV成图精度差异不显著。结论在肝脏SABR中，MANIV-BH可显著提高CBCT质量，降低操作员间IGRT差异，增强OAR自动分割。除了安全有效地缓解呼吸运动外，MANIV还提高了治疗过程中的准确性，尽管其实施需要资源。

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

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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