A super‐resolution framework for the reconstruction of T2‐weighted (T2w) time‐resolved (TR) 4DMRI using T1w TR‐4DMRI as the guidance

Abstract

The purpose of this study was to develop T2-weighted (T2w) time-resolved (TR) four-dimensional magnetic resonance imaging (4DMRI) reconstruction technique with higher soft-tissue contrast for multiple breathing cycle motion assessment by building a super-resolution (SR) framework using the T1w TR-4DMRI reconstruction as guidance. Methods: The multi-breath T1w TR-4DMRI was reconstructed by deforming a high-resolution (HR: 2 9 2 9 2 mm 3 ) volumetric breath-hold (BH, 20s) three-dimensional magnetic resonance imaging (3DMRI) image to a series of low-resolution (LR: 5 9 5 9 5 mm 3 ) 3D cine images at a 2Hz frame rate in free-breathing (FB, 40 s) using an enhanced Demons algorithm, namely [T1 BH ? FB] reconstruction. Within the same imaging session, respiratory-correlated (RC) T2w 4DMRI (2 9 2 9 2 mm 3 ) was acquired based on an internal navigator to gain HR T2w (T2 HR ) in three states (full exhalation and mid and full inhalation) in~5 min. Minor binning artifacts in the RC-4DMRI were automatically identified based on voxel intensity correlation (VIC) between consecutive slices as outliers (VIC < VIC mean -r) and corrected by deforming the artifact slices to interpolated slices from the adjacent slices iteratively until no outliers were identified. A T2 HR image with minimal deformation (<1 cm at the diaphragm) from the T1 BH image was selected for multi-modal B-Spline deformable image registration (DIR) to establish the T2 HR -T1 BH voxel correspondence. Two approaches to reconstruct T2w TR-4DMRI were investigated: (A) T2 HR ?[T1 BH ?FB]: to deform T2w HR to T1w BH only as T1w TR-4DMRI was reconstructed, and combine the two displacement vector fields (DVFs) to reconstruct T2w TR-4DMRI, and (B) [T2 HR T1 BH ]?FB: to deform T1w BH to T2w HR first and apply the deformed T1w BH to reconstruct T2w TR-4DMRI. The reconstruction times were similar, 8-12 min per volume. To validate the two methods, T2w-and T1wmapped 4D XCAT digital phantoms were utilized with three synthetic spherical tumors (/ = 2.0, 3.0, and 4.0 cm) in the lower or mid lobes as the ground truth to evaluate the tumor location (the center of mass, COM), size (volume ratio, %V), and shape (Dice index). Six lung cancer patients were scanned under an IRB-approved protocol and the T2w TR-4DMRI images reconstructed from the two methods were compared based on the preservation of the three tumor characteristics. The local tumor-contained image quality was also characterized using the VIC and structure similarity (SSIM) indexes. Results: In the 4D digital phantom, excellent tumor alignment after T2 HR -T1 HR DIR is achieved: ΔCOM = 0.8 AE 0.5 mm, %V = 1.06 AE 0.02, and Dice = 0.91 AE 0.03, in both deformation directions using the DIR-target image as the reference. In patients, binning artifacts are corrected with improved image quality: average VIC increases from 0.92 AE 0.03 to 0.95 AE 0.01. Both T2w TR-4DMRI reconstruction methods produce similar tumor alignment errors ΔCOM = 2.9 AE 0.6 mm. However, method B ([T2 HR T1 BH ]?FB) produces superior results in preserv...

Stability and Reliability of Enhanced External-Internal Motion Correlation via Dynamic Phase-Shift Corrections Over 30-min Timeframe for Respiratory-Gated Radiotherapy

“…Specifically, it is possible to place a small navigator window on the tumor–lung interface to measure the motion of a sizable lung tumor, i.e., a tumor whose diameter exceeds 2 cm. Alternatively, the time-resolved 4DMRI with a 2 Hz frame rate 36 , 45 – 47 can be applied to investigate the correlation between the motions of an external structure and an internal tumor. Depending on the clinical needs, the dynamic MR imaging data can be used to build either a simple phase-shift-corrected respiratory model or a sophisticated physics-based perturbation model using surface-imaging-based spirometry as a surrogate.…”

Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula

“…Dracula could be applied on an MR-Linac, to reconstruct both 4D-MRI and MidP-MRI online in less than 1 minute, to support daily plan adaptation for lung and abdominal cancer patients [15][16][17]. Alternatively, 4D-Dracula MRI can provide MVFs, which could be used to transform a scan acquired with a separate contrast, to different respiratory phases [54,55]. This approach yields co-registered 4D-MRI of several contrasts, such as: T1-weighted, T2-weighted and synthetic-CT, without requiring multiple lengthy 4D acquisitions, which could facilitate MR-only radiotherapy treatment planning and delivery on an MR-Linac for lung and abdominal patients [40].…”

A Simulation Study of Tolerance of Breathing Amplitude Variations in Radiotherapy of Lung Cancer Using 4DCT and Time-Resolved 4DMRI

“…TR-4DMRI images were reconstructed using a super-resolution method via deformable image registration (DIR) [14,[22][23][24]. Using the displacement vector field (DVF) of DIR from the high-resolution BH image to the low-resolution FB images, the center of mass (COM) of the gross tumor volume (GTV) as a function of time (2 Hz) was used to create the tumor motion waveforms.…”