MR-Based Attenuation Correction Using Ultrashort-Echo-Time Pulse Sequences in Dementia Patients
MR-Based Attenuation Correction Using Ultrashort-Echo-Time Pulse Sequences in Dementia Patients
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DOI：
10.2967/jnumed.114.146308
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发表时间：
2015-03-01
影响因子：
9.3
通讯作者：
Ziegler, Sibylle I.
中科院分区：
文献类型：
--
作者：
Cabello, Jorge;Lukas, Mathias;Ziegler, Sibylle I.
衰减校正（AC）是定量PET重建的关键要求。考虑衰减图（mu图）中的骨信息对于准确的脑PET定量至关重要。然而，测量骨结构的信号是MR中一项具有挑战性的任务。最近的F-18-FDG PET/MR研究表明，当骨被忽略时，放射性示踪剂浓度的评估存在定量偏倚。这项工作的重点是F-18-FDG PET/MR神经退行性痴呆症。已知这些会导致特定模式的F-18-FDG代谢低下，主要发生在大脑浅表结构中，可能会出现衰减伪影，因此具有直接诊断结果。一个全自动的方法来估计亩地图，包括骨组织仅使用MR信息，提出。方法：该算法基于双回波超短回波时间MR成像序列计算R-2图，并由此导出mu图。对基于R-2的mu图进行后处理，以计算骨组织的估计分布。通过确定混淆矩阵，将从9名患者的数据集计算的mu图与基于CT的mu图（mu图（CT））进行比较。此外，使用不同的mu图校正重建的PET数据之间的感兴趣区域进行比较。PET数据使用基于Dixon的mu图（mu图（DX））和基于双回波超短回波时间的mu图（mu图（UTE））进行重建，这两个图都是由扫描仪计算的，并且将本工作中提出的基于R-2的mu图与使用mu图（CT）作为参考的重建PET数据进行比较。结果如下：与使用参考mu图（CT）重建的PET数据相比，使用AC的mu图（DX）和mu图（UTE）的误差约高20%。然而，对于所有患者和所有分析的感兴趣区域，使用基于R-2的mu图的PET AC导致显著改善，将误差降低至-5.8%至2.5%。结论：与mu图（DX）和mu图（UTE）相比，所提出的方法成功地显示出显著减少的量化误差，因此提供了更准确的PET图像量化，以改善痴呆患者的诊断检查。
Attenuation correction (AC) is a critical requirement for quantitative PET reconstruction. Accounting for bone information in the attenuation map (mu map) is of paramount importance for accurate brain PET quantification. However, to measure the signal from bone structures represents a challenging task in MR. Recent F-18-FDG PET/MR studies showed quantitative bias for the assessment of radiotracer concentration when bone was ignored. This work is focused on F-18-FDG PET/MR neurodegenerative dementing disorders. These are known to lead to specific patterns of F-18-FDG hypometabolism, mainly in superficial brain structures, which might suffer from attenuation artifacts and thus have immediate diagnostic consequences. A fully automatic method to estimate the mu map, including bone tissue using only MR information, is presented. Methods: The algorithm was based on a dual-echo ultrashort-echo-time MR imaging sequence to calculate the R-2 map, from which the mu map was derived. The R-2-based mu map was postprocessed to calculate an estimated distribution of the bone tissue. mu maps calculated from datasets of 9 patients were compared with their CT-based mu maps (mu map(CT)) by determining the confusion matrix. Additionally, a regionof- interest comparison between reconstructed PET data, corrected using different mu maps, was performed. PET data were reconstructed using a Dixon-based mu map (mu map(DX)) and a dual-echo ultrashort-echotime- based mu map (mu map(UTE)), which are both calculated by the scanner, and the R-2-based mu map presented in this work was compared with reconstructed PET data using the mu map(CT) as a reference. Results: Errors were approximately 20% higher using the mu map(DX) and mu map(UTE) for AC, compared with reconstructed PET data using the reference mu map(CT). However, PET AC using the R-2-based mu map resulted, for all the patients and all the analyzed regions of interest, in a significant improvement, reducing the error to -5.8% to 2.5%. Conclusion: The proposed method successfully showed significantly reduced errors in quantification, compared with the mu map(DX) and mu map(UTE), and therefore delivered more accurate PET image quantification for an improved diagnostic workup in dementia patients.