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一种使用同时多层成像的二维/四维磁共振混合成像方法,用于放射治疗引导。

A hybrid 2D/4D-MRI methodology using simultaneous multislice imaging for radiotherapy guidance.

机构信息

Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.

Elekta AB, kungstensgatan 18, 113 57 Stockholm, Sweden.

出版信息

Med Phys. 2022 Sep;49(9):6068-6081. doi: 10.1002/mp.15802. Epub 2022 Jun 22.

DOI:10.1002/mp.15802
PMID:35694905
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9545880/
Abstract

PURPOSE

Respiratory motion management is important in abdominothoracic radiotherapy. Fast imaging of the tumor can facilitate multileaf collimator (MLC) tracking that allows for smaller treatment margins, while repeatedly imaging the full field-of-view is necessary for 4D dose accumulation. This study introduces a hybrid 2D/4D-MRI methodology that can be used for simultaneous MLC tracking and dose accumulation on a 1.5 T Unity MR-linac (Elekta AB, Stockholm, Sweden).

METHODS

We developed a hybrid 2D/4D-MRI methodology that uses a simultaneous multislice (SMS) accelerated MRI sequence, which acquires two coronal slices simultaneously and repeatedly cycles through slice positions over the image volume. As a result, the fast 2D imaging can be used prospectively for MLC tracking and the SMS slices can be sorted retrospectively into respiratory-correlated 4D-MRIs for dose accumulation. Data were acquired in five healthy volunteers with an SMS-bTFE and SMS-TSE MRI sequence. For each sequence, a prebeam dataset and a beam-on dataset were acquired simulating the two phases of MR-linac treatments. Prebeam data were used to generate a 4D-based motion model and a reference mid-position volume, while beam-on data were used for real-time motion extraction and reconstruction of beam-on 4D-MRIs. In addition, an in-silico computational phantom was used for validation of the hybrid 2D/4D-MRI methodology. MLC tracking experiments were performed with the developed methodology, for which real-time SMS data reconstruction was enabled on the scanner. A 15-beam 8× 7.5 Gy intensity-modulated radiotherapy plan for lung stereotactic body radiotherapy with isotropic 3 mm GTV-to-PTV margins was created. Dosimetry experiments were performed using a 4D motion phantom. The latency between target motion and updating the radiation beam was determined and compensated. Local gamma analyses were performed to quantify dose differences compared to a static reference delivery, and dose area histograms (DAHs) were used to quantify the GTV and PTV coverage.

RESULTS

In-vivo data acquisition and MLC tracking experiments were successfully performed with the developed hybrid 2D/4D-MRI methodology. Real-time liver-lung interface motion estimation had a Pearson's correlation of 0.996 (in-vivo) and 0.998 (in-silico). A median (5th-95th percentile) error of 0.0 (-0.9 to 0.7) mm and 0.0 (-0.2 to 0.2) mm was found for real-time motion estimation for in-vivo and in-silico, respectively. Target motion prediction beyond the liver-lung interface had a median root mean square error of 1.6 mm (in-vivo) and 0.5 mm (in-silico). Beam-on 4D MRI reconstruction required a median amount of data equal to an acquisition time of 2:21-3:17 min, which was 20% less data compared to the prebeam-derived 4D-MRI. System latency was reduced from 501 ± 12 ms to -1 ± 3 ms (SMS-TSE) and from 398 ± 10 ms to -10 ± 4 ms (SMS-bTFE) by a linear regression prediction filter. The local gamma analysis agreed within to 3.3% (SMS-bTFE) and to 10% (SMS-TSE) with a reference MRI sequence. The DAHs revealed a relative GTV coverage between 97% and 100% (SMS-bTFE) and 100% and 101% (SMS-TSE) compared to the static reference.

CONCLUSIONS

The presented 2D/4D-MRI methodology demonstrated the potential for accurately extracting real-time motion for MLC tracking in abdominothoracic radiotherapy, while simultaneously reconstructing contiguous respiratory-correlated 4D-MRIs for dose accumulation.

摘要

目的

在胸腹放射治疗中,呼吸运动管理很重要。肿瘤的快速成像可以促进多叶准直器(MLC)的跟踪,从而实现更小的治疗边缘,而对全视野的重复成像对于 4D 剂量积累是必要的。本研究介绍了一种混合 2D/4D-MRI 方法,可用于在 1.5T Unity MR-直线加速器(Elekta AB,斯德哥尔摩,瑞典)上同时进行 MLC 跟踪和剂量积累。

方法

我们开发了一种混合 2D/4D-MRI 方法,该方法使用同时多切片(SMS)加速 MRI 序列,该序列同时获取两个冠状切片,并在图像体积上重复循环切片位置。因此,快速的 2D 成像可以前瞻性地用于 MLC 跟踪,而 SMS 切片可以回溯性地分为与呼吸相关的 4D-MRI 以进行剂量积累。在五名健康志愿者中使用 SMS-bTFE 和 SMS-TSE MRI 序列采集数据。对于每个序列,采集了两个相位的预射束数据集和射束数据集,模拟了 MR-直线加速器治疗的两个阶段。预射束数据用于生成基于 4D 的运动模型和参考中位置体积,而射束数据集用于实时运动提取和射束数据集的重建。此外,使用计算仿真体模对混合 2D/4D-MRI 方法进行了验证。使用开发的方法进行了 MLC 跟踪实验,该方法可在扫描仪上实现实时 SMS 数据重建。创建了用于肺部立体定向体放射治疗的 15 束 8x7.5Gy 强度调制放射治疗计划,GTV 到 PTV 边界等方 3mm。使用 4D 运动体模进行了剂量实验。确定并补偿了靶区运动与更新辐射束之间的延迟。进行局部伽马分析,以量化与静态参考剂量的剂量差异,并使用剂量面积直方图(DAH)量化 GTV 和 PTV 覆盖。

结果

成功地使用开发的混合 2D/4D-MRI 方法进行了体内数据采集和 MLC 跟踪实验。实时肝肺界面运动估计的 Pearson 相关系数为 0.996(体内)和 0.998(计算仿真)。对于体内和计算仿真,实时运动估计的中位数(第 5 百分位-第 95 百分位)误差分别为 0.0(-0.9 到 0.7)mm 和 0.0(-0.2 到 0.2)mm。肝肺界面以外的靶区运动预测的中位数均方根误差为 1.6mm(体内)和 0.5mm(计算仿真)。进行 4D MRI 重建需要的中位数数据量相当于 2:21-3:17 分钟的采集时间,比基于预射束的 4D-MRI 减少了 20%的数据。通过线性回归预测滤波器,系统延迟从 501±12ms 降低至-1±3ms(SMS-TSE)和从 398±10ms 降低至-10±4ms(SMS-bTFE)。局部伽马分析与参考 MRI 序列的一致性在 (SMS-bTFE)和 (SMS-TSE)内为 到 3.3%和 到 10%。DAH 显示与静态参考相比,GTV 覆盖率相对为 97%至 100%(SMS-bTFE)和 100%至 101%(SMS-TSE)。

结论

所提出的 2D/4D-MRI 方法证明了在胸腹放射治疗中准确提取 MLC 跟踪实时运动的潜力,同时同时重建用于剂量积累的连续呼吸相关 4D-MRI。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/8e7731e9ab48/MP-49-6068-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/649c2da48ab8/MP-49-6068-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/12bf15c3e443/MP-49-6068-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/f404a3410612/MP-49-6068-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/555375f6145a/MP-49-6068-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/432d19c6ffd0/MP-49-6068-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/8e7731e9ab48/MP-49-6068-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/649c2da48ab8/MP-49-6068-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/12bf15c3e443/MP-49-6068-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/f404a3410612/MP-49-6068-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/555375f6145a/MP-49-6068-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/432d19c6ffd0/MP-49-6068-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4251/9545880/8e7731e9ab48/MP-49-6068-g006.jpg

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