Enhanced super-resolution reconstruction of T1w time-resolved 4DMRI in low-contrast tissue using 2-step hybrid deformable image registration.

PURPOSE: Deformable image registration (DIR) in low-contrast tissues is often suboptimal because of low visibility of landmarks, low driving-force to deform, and low penalty for misalignment. We aim to overcome the shortcomings for improved reconstruction of time-resolved four-dimensional magnetic resonance imaging (TR-4DMRI). METHODS AND MATERIALS: Super-resolution TR-4DMRI reconstruction utilizes DIR to combine high-resolution (highR:2x2x2mm3 ) breath-hold (BH) and low-resolution (lowR:5x5x5mm3 ) free-breathing (FB) 3D cine (2Hz) images to achieve clinically acceptable spatiotemporal resolution. A 2-step hybrid DIR approach was developed to segment low-dynamic-range (LDR) regions: low-intensity lungs and high-intensity "bodyshell" (=body-lungs) for DIR refinement after conventional DIR. The intensity in LDR regions was renormalized to the full dynamic range (FDR) to enhance local tissue contrast. A T1-mapped 4D XCAT digital phantom was created, and seven volunteers and five lung cancer patients were scanned with two BH and one 3D cine series per subject to compare the 1-step conventional and 2-step hybrid DIR using: (a) the ground truth in the phantom, (b) highR-BH references, which were used to simulate 3D cine images by down-sampling and Rayleigh-noise-adding, and (c) cross-verification between two TR-4DMRI images reconstructed from two BHs. To assess DIR improvement, 8-17 blood vessel bifurcations were used in volunteers, and lung tumor position, size, and shape were used in phantom and patients, together with the voxel intensity correlation (VIC), structural similarity (SSIM), and cross-consistency check (CCC). RESULTS: The 2-step hybrid DIR improves contrast and DIR accuracy. In volunteers, it improves low-contrast alignment from 6.5 ± 1.8 mm to 3.3 ± 1.0 mm. In phantom, it improves tumor center of mass alignment (COM = 1.3 ± 0.2 mm) and minimizes DIR directional difference. In patients, it produces almost-identical tumor COM, size, and shape (dice> 0.85) as the reference. The VIC and SSIM are significantly increased and the number of CCC outliers are reduced by half. CONCLUSION: The 2-step hybrid DIR improves low-contrast-tissue alignment and increases lung tumor fidelity. It is recommended to adopt the 2-step hybrid DIR for TR-4DMRI reconstruction.

Introduction of a pseudo demons force to enhance deformation range for robust reconstruction of super-resolution time-resolved 4DMRI.

PURPOSE: The purpose of this study was to enhance the deformation range of demons-based deformable image registration (DIR) for large respiration-induced organ motion in the reconstruction of time-resolved four-dimensional magnetic resonance imaging (TR-4DMRI) for multi-breath motion simulation. METHODS: A demons-based DIR algorithm was modified to enhance the deformation range for TR-4DMRI reconstruction using the super-resolution approach. A pseudo demons force was introduced to accelerate the coarse deformation in a multi-resolution (n = 3) DIR approach. The intensity gradient of a voxel was applied to its neighboring (5 × 5 × 5) voxels with a weight of Gaussian probability profile (σ = 1 voxel) to extend the demons force, especially on those voxels that have little intensity gradience but high-intensity difference. A digital 4DMRI phantom with 3-8 cm diaphragmatic motions was used for DIR comparison. Six volunteers were scanned with two high-resolution (highR: 2 × 2 × 2 mm3 ) breath-hold (BH) 3DMR images at full inhalation (BHI) and full exhalation (BHE) and low-resolution (lowR: 5 × 5 × 5 mm3 ) free-breathing (FB) 3DMR cine images (2 Hz) under an IRB-approved protocol. A cross-consistency check (CCC) (BHI→FB←BHE), with voxel intensity correlation (VIC) and inverse consistency error (ICE), was introduced for cross-verification of TR-4DMRI reconstruction. RESULTS: Using the digital phantom, the maximum deformable magnitude is doubled using the modified DIR from 3 to 6 cm at the diaphragm. In six human subjects, the first 15-iteration DIR using the pseudo force deforms 200 ± 150% more than the original force, and succeeds in all 12 cases, whereas the original demons-based DIR failed in 67% of tested cases. Using the pseudo force, high VIC (>0.9) and small ICE (1.6 ± 0.6 mm) values are observed for DIR of BHI&BHE, BHI→FB, and BHE→FB. The CCC identifies four questionable cases, in which two cases need further DIR refinement, without missing true negative. CONCLUSIONS: The introduction of a pseudo demons force enhances the largest deformation magnitude up to 6 cm. The cross-consistency check ensures the quality of TR-4DMRI reconstruction. Further investigation is ongoing to fully characterize TR-4DMRI for potential multi-breathing-cycle radiotherapy simulation.

Evaluation of automatic contour propagation in T2-weighted 4DMRI for normal-tissue motion assessment using internal organ-at-risk volume (IRV).

PURPOSE: The purpose of this study was to evaluate the quality of automatically propagated contours of organs at risk (OARs) based on respiratory-correlated navigator-triggered four-dimensional magnetic resonance imaging (RC-4DMRI) for calculation of internal organ-at-risk volume (IRV) to account for intra-fractional OAR motion. METHODS AND MATERIALS: T2-weighted RC-4DMRI images were of 10 volunteers acquired and reconstructed using an internal navigator-echo surrogate and concurrent external bellows under an IRB-approved protocol. Four major OARs (lungs, heart, liver, and stomach) were delineated in the 10-phase 4DMRI. Two manual-contour sets were delineated by two clinical personnel and two automatic-contour sets were propagated using free-form deformable image registration. The OAR volume variation within the 10-phase cycle was assessed and the IRV was calculated as the union of all OAR contours. The OAR contour similarity between the navigator-triggered and bellows-rebinned 4DMRI was compared. A total of 2400 contours were compared to the most probable ground truth with a 95% confidence level (S95) in similarity, sensitivity, and specificity using the simultaneous truth and performance level estimation (STAPLE) algorithm. RESULTS: Visual inspection of automatically propagated contours finds that approximately 5-10% require manual correction. The similarity, sensitivity, and specificity between manual and automatic contours are indistinguishable (P > 0.05). The Jaccard similarity indexes are 0.92 ± 0.02 (lungs), 0.89 ± 0.03 (heart), 0.92 ± 0.02 (liver), and 0.83 ± 0.04 (stomach). Volume variations within the breathing cycle are small for the heart (2.6 ± 1.5%), liver (1.2 ± 0.6%), and stomach (2.6 ± 0.8%), whereas the IRV is much larger than the OAR volume by: 20.3 ± 8.6% (heart), 24.0 ± 8.6% (liver), and 47.6 ± 20.2% (stomach). The Jaccard index is higher in navigator-triggered than bellows-rebinned 4DMRI by 4% (P < 0.05), due to the higher image quality of navigator-based 4DMRI. CONCLUSION: Automatic and manual OAR contours from Navigator-triggered 4DMRI are not statistically distinguishable. The navigator-triggered 4DMRI image provides higher contour quality than bellows-rebinned 4DMRI. The IRVs are 20-50% larger than OAR volumes and should be considered in dose estimation.