Abstract
PURPOSE: To accelerate volumetric cine MRI (VC-MRI) using undersampled 2D-cine MRI to provide real-time 3D guidance for gating/target tracking in radiotherapy. METHODS: 4D-MRI is acquired during patient simulation. One phase of the prior 4D-MRI is selected as the prior images, designated as MRI(prior). The on-board VC-MRI at each time-step is considered a deformation of the MRI(prior). The deformation field map is represented as a linear combination of the motion components extracted by principal component analysis from the prior 4D-MRI. The weighting coefficients of the motion components are solved by matching the corresponding 2D-slice of the VC-MRI with the on-board undersampled 2D-cine MRI acquired. Undersampled Cartesian and radial k-space acquisition strategies were investigated. The effects of k-space sampling percentage (SP) and distribution, tumor sizes and noise on the VC-MRI estimation were studied. The VC-MRI estimation was evaluated using XCAT simulation of lung cancer patients and data from liver cancer patients. Volume percent difference (VPD) and Center of Mass Shift (COMS) of the tumor volumes and tumor tracking errors were calculated. RESULTS: For XCAT, VPD/COMS were 11.93 ± 2.37%/0.90 ± 0.27 mm and 11.53 ± 1.47%/0.85 ± 0.20 mm among all scenarios with Cartesian sampling (SP = 10%) and radial sampling (21 spokes, SP = 5.2%), respectively. When tumor size decreased, higher sampling rate achieved more accurate VC-MRI than lower sampling rate. VC-MRI was robust against noise levels up to SNR = 20. For patient data, the tumor tracking errors in superior-inferior, anterior-posterior and lateral (LAT) directions were 0.46 ± 0.20 mm, 0.56 ± 0.17 mm and 0.23 ± 0.16 mm, respectively, for Cartesian-based sampling with SP = 20% and 0.60 ± 0.19 mm, 0.56 ± 0.22 mm and 0.42 ± 0.15 mm, respectively, for radial-based sampling with SP = 8% (32 spokes). CONCLUSIONS: It is feasible to estimate VC-MRI from a single undersampled on-board 2D cine MRI. Phantom and patient studies showed that the temporal resolution of VC-MRI can potentially be improved by 5-10 times using a 2D cine image acquired with 10-20% k-space sampling.