Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States of America.
Phys Med Biol. 2020 Dec 2;65(23):23TR02. doi: 10.1088/1361-6560/abb0f8.
Attenuation correction has been one of the main methodological challenges in the integrated positron emission tomography and magnetic resonance imaging (PET/MRI) field. As standard transmission or computed tomography approaches are not available in integrated PET/MRI scanners, MR-based attenuation correction approaches had to be developed. Aspects that have to be considered for implementing accurate methods include the need to account for attenuation in bone tissue, normal and pathological lung and the MR hardware present in the PET field-of-view, to reduce the impact of subject motion, to minimize truncation and susceptibility artifacts, and to address issues related to the data acquisition and processing both on the PET and MRI sides. The standard MR-based attenuation correction techniques implemented by the PET/MRI equipment manufacturers and their impact on clinical and research PET data interpretation and quantification are first discussed. Next, the more advanced methods, including the latest generation deep learning-based approaches that have been proposed for further minimizing the attenuation correction related bias are described. Finally, a future perspective focused on the needed developments in the field is given.
衰减校正一直是正电子发射断层成像和磁共振成像(PET/MRI)领域的主要方法学挑战之一。由于在集成的 PET/MRI 扫描仪中没有标准的透射或计算机断层扫描方法,因此必须开发基于磁共振的衰减校正方法。在实施准确方法时需要考虑的方面包括需要考虑骨组织、正常和病理性肺以及 PET 视野中存在的磁共振硬件的衰减,以减少受试者运动的影响,最小化截断和磁化率伪影,并解决与数据采集和处理相关的问题,包括 PET 和 MRI 两侧。首先讨论了由 PET/MRI 设备制造商实施的标准基于磁共振的衰减校正技术及其对临床和研究 PET 数据解释和定量的影响。接下来,描述了更先进的方法,包括为进一步最小化衰减校正相关偏差而提出的最新一代基于深度学习的方法。最后,着眼于该领域的未来发展,给出了未来展望。