Abstract

Purpose:To develop a technique generating ultrafast on‐board VC‐MRI using prior 4D‐MRI and on‐board phase‐skipped encoding k‐space acquisition for real‐time 3D target tracking of liver and lung radiotherapy.Methods:The end‐of‐expiration (EOE) volume in 4D‐MRI acquired during the simulation was selected as the prior volume. 3 major respiratory deformation patterns were extracted through the principal component analysis of the deformation field maps (DFMs) generated between EOE and all other phases. The on‐board VC‐MRI at each instant was considered as a deformation of the prior volume, and the deformation was modeled as a linear combination of the extracted 3 major deformation patterns. To solve the weighting coefficients of the 3 major patterns, a 2D slice was extracted from VC‐MRI volume to match with the 2D on‐board sampling data, which was generated by 8‐fold phase skipped‐encoding k‐space acquisition (i.e., sample 1 phase‐encoding line out of every 8 lines) to achieve an ultrafast 16–24 volumes/s frame rate. The method was evaluated using XCAT digital phantom to simulate lung cancer patients. The 3D volume of end‐ofinhalation (EOI) phase at the treatment day was used as ground‐truth onboard VC‐MRI with simulated changes in 1) breathing amplitude and 2) breathing amplitude/phase change from the simulation day. A liver cancer patient case was evaluated for in‐vivo feasibility demonstration.Results:The comparison between ground truth and estimated on‐board VC‐MRI shows good agreements. In XCAT study with changed breathing amplitude, the volume‐percent‐difference(VPD) between ground‐truth and estimated tumor volumes at EOI was 6.28% and the Center‐of‐Mass‐Shift(COMS) was 0.82mm; with changed breathing amplitude and phase, the VPD was 8.50% and the COMS was 0.54mm. The study of liver patient case also demonstrated a promising in vivo feasibility of the proposed methodConclusion:Preliminary results suggest the feasibility to estimate ultrafast VC‐MRI for on‐board target localization with phase skipped‐encoding k‐space acquisition.Research grant from NIH R01‐184173

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