Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.
Biomed Phys Eng Express. 2020 Apr 27;6(3):035032. doi: 10.1088/2057-1976/ab81ad.
Rigid image registration (RIR) accuracy is crucial for image guided radiotherapy (IGRT). However, existing clinical image registration assessment methods cannot separate and quantify RIR error sources. Herein, we develop an extension of the 'full circle method' for RIR consistency. Paired registration circuits are used to isolate sources of RIR error caused by reference dataset substitution, from those inherent to the underlying RIR. This approach was demonstrated in the context of MRI-only IGRT, assessing substitution of MRI-derived synthetic-CT (sCT) for conventional CT, in a cohort of rectal cancer patients.
Planning CT, MRI-derived sCT, and two CBCTs from seven rectal cancer patients were retrospectively registered with global and soft tissue clipbox based RIR. Paired registration circuits were constructed using two moving (cone beam CT) images and two reference images (CT and sCT), per patient. Differences between inconsistencies in registration circuits containing CT and sCT were used to determine changes in registration accuracy due to substitution of sCT for CT.
sCT was found to be equivalent to CT under global RIR, with median differences of 0.05 mm and 0.01°. Soft tissue clipbox based RIR with sCT exhibited gross misregistration (>5 mm or 3°) for 3 patients. Registration consistency was degraded compared to CT across the cohort, with median differences of 0.54 mm and 0.15°.
A paired registration circuit methodology for assessing RIR accuracy without ground truth information was developed and demonstrated for MRI-only IGRT in rectal cancer. This highlighted a reduction in clipbox based RIR consistency when sCT was substituted for conventional CT. The developed method enabled separation of degraded registration accuracy, from other error sources within the overall registration inconsistency. This novel methodology is applicable to any RIR scenario and enables analysis of the change in RIR performance on modification of image data or process.
刚性图像配准（RIR）的准确性对于图像引导放疗（IGRT）至关重要。然而，现有的临床图像配准评估方法无法分离和量化 RIR 误差源。在此，我们为 RIR 一致性扩展了“全圆法”。配对注册电路用于分离由于参考数据集替换而导致的 RIR 误差源，以及固有于基础 RIR 的误差源。在仅 MRI 的 IGRT 中，评估了 MRI 衍生的合成 CT（sCT）代替常规 CT 的情况，在一组直肠癌患者中进行了演示。
回顾性地对 7 例直肠癌患者的计划 CT、MRI 衍生的 sCT 和 2 个 CBCT 进行了全局和软组织 clipbox 基于 RIR 的配准。为每位患者构建了两个移动（锥形束 CT）图像和两个参考图像（CT 和 sCT）的配对注册电路。使用包含 CT 和 sCT 的注册电路之间的不一致性差异来确定由于用 sCT 代替 CT 而导致的配准精度变化。
在全局 RIR 下，sCT 与 CT 等效，中位数差异为 0.05mm 和 0.01°。基于软组织 clipbox 的 RIR 使用 sCT 时，有 3 名患者出现严重配准错误（>5mm 或 3°）。与 CT 相比，整个队列的注册一致性都有所下降，中位数差异为 0.54mm 和 0.15°。
开发了一种无需真实信息即可评估 RIR 准确性的配对注册电路方法，并在直肠癌的仅 MRI IGRT 中进行了演示。这凸显了当用常规 CT 代替 sCT 时，clipbox 基于 RIR 的一致性降低。所开发的方法能够将注册精度的降低与整体注册不一致性中的其他误差源分开。该新方法适用于任何 RIR 情况，并能够分析在修改图像数据或过程时 RIR 性能的变化。
