基于PE-CycleGAN网络的鼻咽癌适应性放疗CBCT-sCT生成。

Q3 Medicine
Yadi He, Xuanru Zhou, Jinhui Jin, Ting Song
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引用次数: 0

摘要

目的:探讨PE-CycleGAN在鼻咽癌适应性放疗(ART)中应用锥形束CT (CBCT)合成高质量CT (sCT)。方法:提出了一种感知增强的CycleGAN模型“PE-CycleGAN”,该模型引入了双对比度鉴别器损失、多感知生成器损失和改进的U-Net结构。80例鼻咽癌患者的CBCT和CT数据作为训练集,其中7例作为测试集。通过量化sCT与参考CT之间的平均绝对误差(MAE)、峰值信噪比(PSNR)、结构相似指数(SSIM)以及剂量γ及通率和靶区及危险器官的相对剂量偏差(OAR),评价sCT的图像质量和剂量计算精度。结果:与参考CT相比,PE-CycleGAN生成的sCT MAE为(56.89±13.84)HU,比CBCT的(81.06±15.86)HU低约30% (PPPPPPP=0.09)。PTVnx HI、PTVnd HI、PTVnd CI、PTV1 HI、PRV_SC、PRV_BS、腮腺、喉部、口腔、下颌骨和PRV_ON的平均相对剂量偏差均小于±1% (P < 0.05)。结论:PE-CycleGAN显示了从CBCT快速合成高质量sCT的能力,为CBCT引导的鼻咽癌适应性放疗提供了一种有希望的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PE-CycleGAN network based CBCT-sCT generation for nasopharyngeal carsinoma adaptive radiotherapy.

Objectives: To explore the synthesis of high-quality CT (sCT) from cone-beam CT (CBCT) using PE-CycleGAN for adaptive radiotherapy (ART) for nasopharyngeal carcinoma.

Methods: A perception-enhanced CycleGAN model "PE-CycleGAN" was proposed, introducing dual-contrast discriminator loss, multi-perceptual generator loss, and improved U-Net structure. CBCT and CT data from 80 nasopharyngeal carcinoma patients were used as the training set, with 7 cases as the test set. By quantifying the mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), as well as the dose gamma pass rate and the relative dose deviations of the target area and organs at risk (OAR) between sCT and reference CT, the image quality and dose calculation accuracy of sCT were evaluated.

Results: The MAE of sCT generated by PE-CycleGAN compared to the reference CT was (56.89±13.84) HU, approximately 30% lower than CBCT's (81.06±15.86) HU (P<0.001). PE-CycleGAN's PSNR and SSIM were 26.69±2.41dB and 0.92±0.02 respectively, significantly higher than CBCT's 21.54±2.37dB and 0.86±0.05 (P<0.001), indicating substantial improvements in image quality and structural similarity. In gamma analysis, under the 2 mm/2% criterion, PE-CycleGAN's sCT achieved a pass rate of (90.13±3.75)%, significantly higher than CBCT's (81.65±3.92)% (P<0.001) and CycleGAN's (87.69±3.50)% (P<0.05). Under the 3 mm/3% criterion, PE-CycleGAN's sCT pass rate of (90.13±3.75)% was also significantly superior to CBCT's (86.92±3.51)% (P<0.001) and CycleGAN's (94.58±2.23)% (P<0.01). The mean relative dose deviation of the target area and OAR between sCT and planned CT was within ±3% for all regions, except for the Lens Dmax (Gy), which had a deviation of 3.38% (P=0.09). The mean relative dose deviations for PTVnx HI, PTVnd HI, PTVnd CI, PTV1 HI, PRV_SC, PRV_BS, Parotid, Larynx, Oral, Mandible, and PRV_ON were all less than ±1% (P>0.05).

Conclusions: PE-CycleGAN demonstrates the ability to rapidly synthesize high-quality sCT from CBCT, offering a promising approach for CBCT-guided adaptive radiotherapy in nasopharyngeal carcinoma.

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南方医科大学学报杂志
南方医科大学学报杂志 Medicine-Medicine (all)
CiteScore
1.50
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0.00%
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208
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