Assessment of 3D motion modeling performance for dose accumulation mapping on the MR-linac by simultaneous multislice MRI

• Published in: Physics in medicine & biology Vol. 64; no. 9; pp. 095004 - 95012
• Main Authors: Borman, P T S, Bos, C, Stemkens, B, Moonen, C T W, Raaymakers, B W, Tijssen, R H N
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 23.04.2019
• Subjects: 4D-MRI; Dose Fractionation, Radiation; Healthy Volunteers; Humans; Liver - diagnostic imaging; Liver - radiation effects; Magnetic Resonance Imaging - instrumentation; Models, Biological; Movement; MR-guided radiotherapy; Particle Accelerators; Phantoms, Imaging; Radiation Dosage; Radiotherapy, Image-Guided - methods; respiratory motion model; robustness; simultaneous multislice
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/1361-6560/ab13e3

Hybrid MR-linac systems enable intrafraction motion monitoring during radiation therapy. Since time-resolved 3D MRI is still challenging, various motion models have been developed that rely on time-resolved 2D imaging. Continuous validation of these models is important for accurate dose accumulation mapping. In this study we used 2D simultaneous multislice (SMS) imaging to improve the PCA-based motion modeling method developed previously (Stemkens et al 2016 Phys. Med. Biol. 61 5335-55). From the additional simultaneously acquired slices, several independent motion models could be generated, which allowed for an assessment of the sensitivity of the motion model to the location of the time-resolved 2D slices. Additionally, the best model could be chosen at every time-point, increasing the method's robustness. Imaging experiments were performed in six healthy volunteers using three simultaneous slices, which generated three independent models per volunteer. For each model the motion traces of the liver tip and both kidneys were estimated. We found that the location of the 2D slices influenced the model's error in five volunteers significantly with a p -value  <0.05, and that selecting the best model at every time-point can improve the method. This allows for more accurate and robust motion characterization in MR-guided radiotherapy.