Real-time non-rigid 3D respiratory motion estimation for MR-guided radiotherapy using MR-MOTUS
Niek R.F. Huttinga, Tom Bruijnen, Cornelis A.T. van den Berg and, Alessandro Sbrizzi

TL;DR
This paper introduces a real-time 3D respiratory motion estimation method for MR-guided radiotherapy that achieves low latency by directly reconstructing motion-fields from k-space data using low-rank decomposition, enabling precise motion monitoring during treatment.
Contribution
The novel real-time MR-MOTUS method significantly reduces latency to 170 ms by combining offline preparation with online inference, improving motion estimation for MR-guided radiotherapy.
Findings
Reconstructed motion-fields are anatomically plausible.
High correlation with motion surrogate (R ≈ 0.975).
Achieved 170 ms latency suitable for real-time application.
Abstract
The MR-Linac is a combination of an MR-scanner and radiotherapy linear accelerator (Linac) which holds the promise to increase the precision of radiotherapy treatments with MR-guided radiotherapy by monitoring motion during radiotherapy with MRI, and adjusting the radiotherapy plan accordingly. Optimal MR-guidance for respiratory motion during radiotherapy requires MR-based 3D motion estimation with a latency of 200-500 ms. Currently this is still challenging since typical methods rely on MR-images, and are therefore limited by the 3D MR-imaging latency. In this work, we present a method to perform non-rigid 3D respiratory motion estimation with 170 ms latency, including both acquisition and reconstruction. The proposed method called real-time low-rank MR-MOTUS reconstructs motion-fields directly from k-space data, and leverages an explicit low-rank decomposition of motion-fields to…
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