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使用对比增强和非对比增强计算机断层扫描图像评估肝脏再照射患者的可变形图像配准准确性。

Evaluation of deformable image registration accuracy for liver re-irradiation patients using contrast and non-contrast computed tomography images.

作者信息

Allen Caitlin, Yeo Adam, Franich Rick, Chander Sarat, Hardcastle Nicholas

机构信息

Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.

RMIT University, Melbourne, Victoria, Australia.

出版信息

Med Phys. 2025 Jul;52(7):e17942. doi: 10.1002/mp.17942.

Abstract

BACKGROUND

Re-irradiation of liver tumors is increasing in frequency, requiring clinicians to account for previous radiation dose to prevent unacceptable toxicity. Given the heterogeneity of liver morphological changes between treatments, deformable image registration (DIR) is required to accumulate dose from previous treatments onto the latest planning images for radiotherapy.

PURPOSE

The increase in re-irradiation of patients with liver cancer has led to the need to account for previous radiotherapy treatments. This feasibility study used contemporaneous intravenous contrast computed tomography images (CTs) to evaluate the accuracy of DIR dose accumulation in the re-irradiation of liver patients, via the use of structural landmarks.

METHODS

We used nine liver patients who received repeat stereotactic body radiation therapy (SBRT) liver radiotherapy, with contrast and non-contrast planning CTs, to evaluate the accuracy of dose accumulation in the liver. The initial planning CT was deformed to the second planning CT, and the deformation vector field was used to deform the initial dose map. The dose could then be accumulated by adding the deformed initial dose map to the second dose map. Three methods of performing DIR were compared, including with and without corresponding anatomical landmarks. Target registration error (TRE), dice similarity coefficient, and Hausdorff distance were used to assess the accuracy of the dose accumulation.

RESULTS

The lowest TRE was achieved with the structure guided algorithm using all of the available anatomical landmarks, with a mean + standard deviation of 1.7 mm (SD = 0.9 mm) for non-contrast (p < 0.0005) and 1.6 mm (SD = 0.9 mm) for contrast CTs (p < 0.0005). DIR based on contrast CTs reduced the TREs, the distance between the location of a given landmark on the second image, and the location of where that landmark is deformed to from the first image, with all DIR algorithms (p < 0.0005 for each contrast non-contrast pair). There were also statistically significant differences between dose accumulation errors for Contrast CTs with a mean of 0.92 Gy (SD = 3.08 Gy) and Non-Contrast CTs of 1.07 Gy (SD = 3.36 Gy) (p < 0.05), and the differences between each of the algorithms were also statistically significant, with p-values < 0.05.

CONCLUSIONS

DIR improves the dose accumulation accuracy in re-irradiation in liver SBRT. DIR accuracy can be improved using contrast CTs and corresponding anatomical landmarks. Providing additional information into the DIR in the form of corresponding anatomical landmarks dramatically improved image registration accuracy and thus reduced dose accumulation errors. Dose accumulation accuracy was dependent on the TRE, and on the dose-gradient of the mapped dose.

摘要

背景

肝脏肿瘤再程放疗的频率日益增加,这要求临床医生考虑既往放疗剂量,以防止出现不可接受的毒性反应。鉴于不同治疗之间肝脏形态变化的异质性,需要采用可变形图像配准(DIR)将既往治疗的剂量累积到最新的放疗计划图像上。

目的

肝癌患者再程放疗的增加导致有必要考虑既往的放射治疗。这项可行性研究使用同期静脉注射对比剂的计算机断层扫描图像(CT),通过使用结构标志点来评估DIR剂量累积在肝脏再程放疗中的准确性。

方法

我们选取了9例接受肝脏立体定向体部放射治疗(SBRT)重复放疗的患者,利用有对比剂和无对比剂的计划CT来评估肝脏中剂量累积的准确性。将初始计划CT变形到第二次计划CT,变形矢量场用于使初始剂量分布图变形。然后,通过将变形后的初始剂量分布图与第二次剂量分布图相加来累积剂量。比较了三种执行DIR的方法,包括有无相应的解剖标志点。使用靶区配准误差(TRE)、骰子相似系数和豪斯多夫距离来评估剂量累积的准确性。

结果

使用所有可用解剖标志点的结构引导算法实现了最低的TRE,无对比剂CT时的平均值±标准差为1.7毫米(标准差=0.9毫米)(p<0.0005),有对比剂CT时为1.6毫米(标准差=0.9毫米)(p<0.0005)。基于有对比剂CT的DIR降低了TRE,即第二次图像上给定标志点的位置与该标志点从第一张图像变形到的位置之间的距离,所有DIR算法均如此(每组有对比剂与无对比剂配对的p<0.0005)。有对比剂CT的剂量累积误差(平均值为0.92 Gy,标准差=3.08 Gy)与无对比剂CT的剂量累积误差(平均值为1.07 Gy,标准差=3.36 Gy)之间也存在统计学显著差异(p<0.05),并且各算法之间的差异也具有统计学显著性,p值<0.05。

结论

DIR提高了肝脏SBRT再程放疗中剂量累积的准确性。使用有对比剂CT和相应的解剖标志点可提高DIR的准确性。以相应解剖标志点的形式向DIR提供额外信息可显著提高图像配准准确性,从而减少剂量累积误差。剂量累积准确性取决于TRE以及映射剂量的剂量梯度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01da/12260772/53b048194d5c/MP-52-0-g003.jpg

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