Montgomery Maria Elkjær, Andersen Flemming Littrup, Mathiasen René, Borgwardt Lise, Andersen Kim Francis, Ladefoged Claes Nøhr
Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.
Department of Clinical Medicine, University of Copenhagen, 2200 Copenhagen, Denmark.
Diagnostics (Basel). 2024 Dec 12;14(24):2788. doi: 10.3390/diagnostics14242788.
: Paediatric PET/CT imaging is crucial in oncology but poses significant radiation risks due to children's higher radiosensitivity and longer post-exposure life expectancy. This study aims to minimize radiation exposure by generating synthetic CT (sCT) images from emission PET data, eliminating the need for attenuation correction (AC) CT scans in paediatric patients. : We utilized a cohort of 128 paediatric patients, resulting in 195 paired PET and CT images. Data were acquired using Siemens Biograph Vision 600 and Long Axial Field-of-View (LAFOV) Siemens Vision Quadra PET/CT scanners. A 3D parameter transferred conditional GAN (PT-cGAN) architecture, pre-trained on adult data, was adapted and trained on the paediatric cohort. The model's performance was evaluated qualitatively by a nuclear medicine specialist and quantitatively by comparing sCT-derived PET (sPET) with standard PET images. : The model demonstrated high qualitative and quantitative performance. Visual inspection showed no significant (19/23) or minor clinically insignificant (4/23) differences in image quality between PET and sPET. Quantitative analysis revealed a mean SUV relative difference of -2.6 ± 5.8% across organs, with a high agreement in lesion overlap (Dice coefficient of 0.92 ± 0.08). The model also performed robustly in low-count settings, maintaining performance with reduced acquisition times. : The proposed method effectively reduces radiation exposure in paediatric PET/CT imaging by eliminating the need for AC CT scans. It maintains high diagnostic accuracy and minimises motion-induced artifacts, making it a valuable alternative for clinical application. Further testing in clinical settings is warranted to confirm these findings and enhance patient safety.
儿科PET/CT成像在肿瘤学中至关重要,但由于儿童较高的放射敏感性和较长的暴露后预期寿命,存在重大辐射风险。本研究旨在通过从发射型PET数据生成合成CT(sCT)图像来尽量减少辐射暴露,从而无需对儿科患者进行衰减校正(AC)CT扫描。我们使用了128名儿科患者的队列,得到了195对PET和CT图像。数据使用西门子Biograph Vision 600和长轴视野(LAFOV)西门子Vision Quadra PET/CT扫描仪采集。一种在成人数据上预训练的3D参数转移条件生成对抗网络(PT-cGAN)架构,在儿科队列上进行了调整和训练。该模型的性能由核医学专家进行定性评估,并通过将sCT衍生的PET(sPET)与标准PET图像进行比较进行定量评估。该模型表现出较高的定性和定量性能。视觉检查显示PET和sPET之间的图像质量无显著差异(19/23)或轻微的临床无意义差异(4/23)。定量分析显示,各器官的平均SUV相对差异为-2.6±5.8%,病变重叠度高度一致(Dice系数为0.92±0.08)。该模型在低计数设置下也表现稳健,在采集时间减少的情况下保持性能。所提出的方法通过无需AC CT扫描有效地减少了儿科PET/CT成像中的辐射暴露。它保持了较高的诊断准确性,并最大限度地减少了运动伪影,使其成为临床应用中有价值的替代方法。有必要在临床环境中进行进一步测试以证实这些发现并提高患者安全性。