Lee Jiyeon, Ha Seunggyun, Kim Regina E Y, Lee Minho, Kim Donghyeon, Lim Hyun Kook
Research Institute, Neurophet Inc., Seoul 06234, Korea.
Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Diagnostics (Basel). 2022 Mar 2;12(3):623. doi: 10.3390/diagnostics12030623.
Amyloid positron emission tomography (PET) scan is clinically essential for the non-invasive assessment of the presence and spatial distribution of amyloid-beta deposition in subjects with cognitive impairment suspected to have been a result of Alzheimer's disease. Quantitative assessment can enhance the interpretation reliability of PET scan; however, its clinical application has been limited due to the complexity of preprocessing. This study introduces a novel deep-learning-based approach for SUVR quantification that simplifies the preprocessing step and significantly reduces the analysis time. Using two heterogeneous amyloid ligands, our proposed method successfully distinguished standardized uptake value ratio (SUVR) between amyloidosis-positive and negative groups. The proposed method's intra-class correlation coefficients were 0.97 and 0.99 against PETSurfer and PMOD, respectively. The difference of global SUVRs between the proposed method and PETSurfer or PMOD were 0.04 and -0.02, which are clinically acceptable. The AUC-ROC exceeded 0.95 for three tools in the amyloid positive assessment. Moreover, the proposed method had the fastest processing time and had a low registration failure rate (1%). In conclusion, our proposed method calculates SUVR that is consistent with PETSurfer and PMOD, and has advantages of fast processing time and low registration failure rate. Therefore, PET quantification provided by our proposed method can be used in clinical practice.
淀粉样蛋白正电子发射断层扫描（PET）对于无创评估疑似患有阿尔茨海默病导致认知障碍的受试者中β淀粉样蛋白沉积的存在和空间分布具有临床重要性。定量评估可提高PET扫描的解读可靠性；然而，由于预处理的复杂性，其临床应用受到限制。本研究引入了一种基于深度学习的新型标准化摄取值比（SUVR）量化方法，该方法简化了预处理步骤并显著减少了分析时间。使用两种不同的淀粉样蛋白配体，我们提出的方法成功区分了淀粉样变性阳性和阴性组之间的标准化摄取值比（SUVR）。所提方法与PETSurfer和PMOD相比，类内相关系数分别为0.97和0.99。所提方法与PETSurfer或PMOD之间的全局SUVR差异分别为0.04和 -0.02，在临床上是可接受的。在淀粉样蛋白阳性评估中，三种工具的曲线下面积（AUC-ROC）均超过0.95。此外，所提方法处理时间最快且配准失败率低（1%）。总之，我们提出的方法计算出的SUVR与PETSurfer和PMOD一致，具有处理时间快和配准失败率低的优点。因此，我们提出的方法提供的PET定量可用于临床实践。
