Nie Xingyu, Huang Kirk, Deasy Joseph, Rimner Andreas, Li Guang
Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
J Appl Clin Med Phys. 2020 Oct;21(10):25-39. doi: 10.1002/acm2.12988. Epub 2020 Sep 22.
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).
Super-resolution TR-4DMRI reconstruction utilizes DIR to combine high-resolution (highR:2x2x2mm ) breath-hold (BH) and low-resolution (lowR:5x5x5mm ) 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).
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.
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.
由于地标可见性低、变形驱动力小以及对齐误差惩罚低，低对比度组织中的可变形图像配准（DIR）往往不够理想。我们旨在克服这些缺点，以改进时间分辨四维磁共振成像（TR-4DMRI）的重建。
超分辨率TR-4DMRI重建利用DIR将高分辨率（highR：2×2×2mm）屏气（BH）和低分辨率（lowR：5×5×5mm）自由呼吸（FB）3D电影（2Hz）图像相结合，以实现临床上可接受的时空分辨率。开发了一种两步混合DIR方法来分割低动态范围（LDR）区域：低强度的肺部和高强度的“身体外壳”（=身体-肺部），以便在传统DIR之后进行DIR细化。将LDR区域的强度重新归一化到全动态范围（FDR），以增强局部组织对比度。创建了一个T1映射的4D XCAT数字体模，对7名志愿者和5名肺癌患者进行扫描，每位受试者扫描两个BH和一个3D电影序列，以使用以下方法比较一步传统DIR和两步混合DIR：（a）体模中的真实情况，（b）高分辨率BH参考图像，通过下采样和添加瑞利噪声来模拟3D电影图像，以及（c）从两个BH重建的两个TR-4DMRI图像之间的交叉验证。为了评估DIR的改进，在志愿者中使用8-17个血管分支，在体模和患者中使用肺肿瘤的位置、大小和形状，同时使用体素强度相关性（VIC）、结构相似性（SSIM）和交叉一致性检查（CCC）。
两步混合DIR提高了对比度和DIR准确性。在志愿者中，它将低对比度对齐从6.5±1.8mm提高到3.3±1.0mm。在体模中，它改善了肿瘤质心对齐（COM = 1.3±0.2mm），并最小化了DIR方向差异。在患者中，它产生的肿瘤COM、大小和形状（骰子系数>0.85）与参考几乎相同。VIC和SSIM显著增加，CCC异常值数量减少一半。
两步混合DIR改善了低对比度组织对齐，并提高了肺肿瘤保真度。建议在TR-
