首页> 外文期刊>The Journal of Nuclear Medicine >Multi-Atlas-Based Attenuation Correction for Brain F-18-FDG PET Imaging Using a Time-of-Flight PET/MR Scanner: Comparison with Clinical Single-Atlas- and CT-Based Attenuation Correction
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Multi-Atlas-Based Attenuation Correction for Brain F-18-FDG PET Imaging Using a Time-of-Flight PET/MR Scanner: Comparison with Clinical Single-Atlas- and CT-Based Attenuation Correction

机译:基于飞行时间PET / MR扫描仪的脑F-18-FDG PET成像多图谱衰减校正:与基于临床单图谱和CT的衰减校正的比较

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In this work, we assessed the feasibility of attenuation correction (AC) based on a multi-atlas-based method (m-Atlas) by comparing it with a clinical AC method (single-atlas-based method [s-Atlas]), on a time-of-flight (TOF) PET/MRI scanner. Methods: We enrolled 15 patients. The median patient age was 59 y (age range, 31-80). All patients underwent clinically indicated whole-body F-18-FDG PET/CT for staging, restaging, or follow-up of malignant disease. All patients volunteered for an additional PET/MRI scan of the head (no additional tracer being injected). For each patient, 3 AC maps were generated. Both s-Atlas and m-Atlas AC maps were generated from the same patient-specific LAVA-Flex T1-weighted images being acquired by default on the PET/MRI scanner during the first 18 s of the PET scan. An s-Atlas AC map was extracted by the PET/MRI scanner, and an m-Atlas AC map was created using a Web service tool that automatically generates m-Atlas pseudo-CT images. For comparison, the AC map generated by PET/CT was registered and used as a gold standard. PET images were reconstructed from raw data on the TOF PET/MRI scanner using each AC map. All PET images were normalized to the SPM5 PET template, and F-18-FDG accumulation was quantified in 67 volumes of interest (VOIs; automated anatomic labeling atlas). Relative (%diff) and absolute differences (vertical bar%diff vertical bar) between images based on each atlas AC and CT-AC were calculated. F-18-FDG uptake in all VOIs and generalized merged VOIs were compared using the paired t test and Bland-Altman test. Results: The range of error on m-Atlas in all 1,005 VOIs was -4.99% to 4.09%. The vertical bar%diff vertical bar on the m-Atlas was improved by about 20% compared with s-Atlas (s-Atlas vs. m-Atlas: 1.49% +/- 1.06% vs. 1.21% +/- 0.89%, P < 0.01). In generalized VOIs, %diff on m-Atlas in the temporal lobe and cerebellum was significantly smaller (s-Atlas vs. m-Atlas: temporal lobe, 1.49% +/- 1.37% vs. -0.37% +/- 1.41%, P < 0.01; cerebellum, 1.55% +/- 1.97% vs. -1.15% +/- 1.72%, P < 0.01). Conclusion: The errors introduced using either s-Atlas orm-Atlas did not exceed 5% in any brain region investigated. When compared with the clinical s-Atlas, m-Atlas is more accurate, especially in regions close to the skull base.
机译:在这项工作中,我们通过将其与临床AC方法(基于单图集的方法[s-Atlas])进行比较,评估了基于多图集的方法(m-Atlas)进行衰减校正(AC)的可行性,在飞行时间(TOF)PET / MRI扫描仪上方法:我们招募了15名患者。患者的中位年龄为59岁(年龄范围:31-80岁)。所有患者均接受临床指征的全身F-18-FDG PET / CT进行分期,重新分期或恶性疾病的随访。所有患者都自愿进行头部的其他PET / MRI扫描(未注射其他示踪剂)。对于每个患者,生成了3个AC图。 s-Atlas和m-Atlas AC图都是从相同的患者特定LAVA-Flex T1加权图像生成的,这些图像是在PET扫描的前18秒内默认在PET / MRI扫描仪上获取的。通过PET / MRI扫描仪提取了s-Atlas AC图,并使用可自动生成m-Atlas伪CT图像的Web服务工具创建了m-Atlas AC图。为了进行比较,将PET / CT生成的AC图注册并用作黄金标准。使用每个AC图从TOF PET / MRI扫描仪上的原始数据重建PET图像。将所有PET图像均标准化为SPM5 PET模板,并在67个感兴趣的体积(VOI;自动解剖标记图集)中对F-18-FDG积累进行定量。计算基于每个图集AC和CT-AC的图像之间的相对(%diff)和绝对差异(垂直条%diff垂直条)。使用配对t检验和Bland-Altman检验比较所有VOI和广义合并VOI中的F-18-FDG摄取。结果:在所有1,005个VOI中,m-Atlas的误差范围为-4.99%至4.09%。与s-Atlas相比,m-Atlas上的竖线%diff竖线提高了约20%(s-Atlas与m-Atlas:1.49%+/- 1.06%与1.21%+/- 0.89%, P <0.01)。在广义VOI中,颞叶和小脑m-Atlas的%diff显着较小(s-Atlas与m-Atlas:颞叶,分别为1.49%+/- 1.37%和-0.37%+/- 1.41%, P <0.01;小脑为1.55%+/- 1.97%,而-1.15%+/- 1.72%,P <0.01)。结论:在所研究的任何大脑区域中,使用s-Atlas或orm-Atlas引入的误差均不超过5%。与临床s-Atlas相比,m-Atlas更为准确,尤其是在靠近颅底的区域。

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