Department of Radiation Oncology, Columbia University, New York, NY, USA.
Department of Radiation Oncology, Columbia University, New York, NY, USA.
Phys Med. 2024 Sep;125:104504. doi: 10.1016/j.ejmp.2024.104504. Epub 2024 Aug 27.
To determine if MRI-based synthetic CTs (sCT), generated with no predefined pulse sequence, can be used for inhomogeneity correction in routine gamma knife radiosurgery (GKRS) treatment planning dose calculation.
Two sets of sCTs were generated from T1post and T2 images using cycleGAN. Twenty-eight patients (18 training, 10 validation) were retrospectively selected. The image quality of the generated sCTs was compared with the original CT (oCT) regarding the HU value preservation using histogram comparison, RMSE and MAE, and structural integrity. Dosimetric comparisons were also made among GKRS plans from 3 calculation approaches: TMR10 (oCT), and convolution (oCT and sCT), at four locations: original disease site, bone/tissue interface, air/tissue interface, and mid-brain.
The study showed that sCTs and oCTs' HU were similar, with T2-sCT performing better. TMR10 significantly underdosed the target by a mean of 5.4% compared to the convolution algorithm. There was no significant difference in convolution algorithm shot time between the oCT and sCT generated with T2. The highest and lowest dosimetric differences between the two CTs were observed in the bone and air interface, respectively. Dosimetric differences of 3.3% were observed in sCT predicted from MRI with stereotactic frames, which was not included in the training sets.
MRI-based sCT can be utilized for GKRS convolution dose calculation without the unnecessary radiation dose, and sCT without metal artifacts could be generated in framed cases. Larger datasets inclusive of all pulse sequences can improve the training set. Further investigation and validation studies are needed before clinical implementation.
确定是否可以使用基于 MRI 的合成 CT(sCT)(无预设脉冲序列生成)对常规伽玛刀放射外科(GKRS)治疗计划剂量计算中的不均匀性进行校正。
使用 cycleGAN 从 T1 后和 T2 图像生成两组 sCT。回顾性选择了 28 名患者(18 名训练,10 名验证)。使用直方图比较、RMSE 和 MAE 以及结构完整性来比较生成的 sCT 与原始 CT(oCT)的图像质量,以评估其 CT 值的保留情况。还在四个位置(原始疾病部位、骨/组织界面、空气/组织界面和中脑)对三种计算方法(oCT、TMR10 和卷积)的 GKRS 计划进行了剂量比较:TMR10(oCT)和卷积(oCT 和 sCT)。
研究表明,sCT 和 oCT 的 CT 值相似,T2-sCT 的效果更好。与卷积算法相比,TMR10 使靶区的剂量显著低估了 5.4%。使用 T2 生成的 oCT 和 sCT 之间的卷积算法拍摄时间没有显著差异。两种 CT 在骨和空气界面处观察到的剂量差异最大和最小。在使用立体定向框架从 MRI 预测的 sCT 中观察到 3.3%的剂量差异,而该差异并未包含在训练集中。
可以在不增加不必要辐射剂量的情况下,使用基于 MRI 的 sCT 进行 GKRS 卷积剂量计算,并且可以在有框架的情况下生成无金属伪影的 sCT。包含所有脉冲序列的更大数据集可以改善训练集。在临床实施之前,需要进行进一步的研究和验证。