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

## TL;DR

Using mechanical ventilation during liver radiotherapy improves image quality and treatment accuracy by reducing motion artifacts.

## Contribution

MANIV-BH improves CBCT image quality, reduces IGRT variability, and enhances auto-segmentation accuracy in liver SABR.

## Key findings

- MANIV-BH significantly improves CBCT image quality compared to free-breathing.
- MANIV-BH reduces interoperator variability in IGRT and manual correction time for auto-segmented OARs.
- Deep-learning auto-segmentation performance is significantly better with MANIV-BH CBCTs.

## Abstract

•Mechanically assisted non-invasive ventilation is used for CBCT-guided liver SABR.•CBCT image quality is better with MANIV compared to free-breathing.•MANIV facilitates IGRT and reduces its interobserver variability.•OARs auto-segmentation is more accurate on MANIV CBCTs.•Time dedicated to correction of auto-segmented OARs is reduced with MANIV CBCTs.

Mechanically assisted non-invasive ventilation is used for CBCT-guided liver SABR.

CBCT image quality is better with MANIV compared to free-breathing.

MANIV facilitates IGRT and reduces its interobserver variability.

OARs auto-segmentation is more accurate on MANIV CBCTs.

Time dedicated to correction of auto-segmented OARs is reduced with MANIV CBCTs.

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.

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.

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.

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.