Institute of Medical Physics, University of Erlangen-Nürnberg, Henkestr. 91, 91052 Erlangen, Germany.
Med Phys. 2013 Aug;40(8):082301. doi: 10.1118/1.4812685.
Flexible radiofrequency (RF) surface coils used in simultaneous PET/MR imaging are currently disregarded in PET attenuation correction (AC) since their position and individual geometry are unknown in whole-body patient scans. The attenuation of PET emission data due to the presence of RF surface coils has been investigated by several research groups but so far no automatic approach for the incorporation of RF surface coils into PET AC has been described. In this work, an algorithm is presented and evaluated which automatically determines the position of multiple RF surface coils and corrects for their attenuation of the PET emission data.
The presented algorithm nonrigidly registers pre-acquired CT-based three-dimensional attenuation templates of RF surface coils into attenuation maps used for PET AC. Transformation parameters are obtained by nonrigid B-spline landmark registration of marker positions in the CT-based attenuation templates of the RF surface coils to marker positions in the current MR images of the patient. The use of different marker patterns enables the registration algorithm to distinguish multiple partly overlapping RF surface coils. To evaluate the registration algorithm, two different PET emission scans of a NEMA standard body phantom with six active lesions and of a large rectangular body phantom were performed on an integrated whole-body PET/MR scanner. The phantoms were scanned with and without one (NEMA phantom scan) or three (large body phantom scan) flexible six-channel RF surface coils placed on top. Additionally, the accuracy and performance of the algorithm were evaluated on volunteer scans (n=5) and on a patient scan using a typical clinical setup of three RF surface coils.
Overall loss of true counts due to the presence of the RF surface coils was 5.1% for the NEMA phantom, 3.6% for the large body phantom, and 2.1% for the patient scan. Considerable local underestimation of measured activity concentration up to 15.4% in the top part of the phantoms and 15.5% for a lesion near the body surface of the patient was measured close to the high attenuating hardware components of the RF coils. The attenuation maps generated by the registration algorithm reduced the quantification errors due to the RF surface coils to values ranging from -3.9% to 4.3%. Concerning the volunteer examinations, the attenuation templates of the three RF surface coils were registered to their correct positions with an overall accuracy of about 3 mm.
The presence of flexible RF surface coils leads to considerable local errors in the simultaneously measured PET activity concentration up to 15.5% especially in regions close to the coils. The presented automatic algorithm accurately and reliably reduces the PET quantification errors caused by multiple partly overlapping flexible RF surface coils to values of 4.3% or better.
在全身患者扫描中，由于无法获知射频（RF）表面线圈的位置和个体几何形状，因此当前在正电子发射断层扫描/磁共振成像（PET/MR）的同时成像中忽略了灵活的 RF 表面线圈。已经有几个研究小组研究了由于存在 RF 表面线圈而导致的 PET 发射数据衰减，但迄今为止，尚未描述将 RF 表面线圈纳入 PET 衰减校正（AC）的自动方法。在这项工作中，提出并评估了一种算法，该算法可自动确定多个 RF 表面线圈的位置，并对其对 PET 发射数据的衰减进行校正。
所提出的算法通过将预先采集的基于 CT 的 RF 表面线圈三维衰减模板非刚性地配准到用于 PET AC 的衰减图中，从而实现了这一点。通过在 RF 表面线圈的基于 CT 的衰减模板中的标记位置和患者当前 MR 图像中的标记位置之间使用非刚性 B-样条标志点配准，获得转换参数。使用不同的标记模式可使配准算法区分多个部分重叠的 RF 表面线圈。为了评估配准算法，在集成的全身 PET/MR 扫描仪上对具有六个活动病变的 NEMA 标准体模和具有大矩形体模的两个不同的 PET 发射扫描进行了评估。在顶部放置一个（NEMA 体模扫描）或三个（大体模扫描）灵活的六通道 RF 表面线圈的情况下对体模进行了扫描。此外，还在志愿者扫描（n=5）和使用三个 RF 表面线圈的典型临床设置的患者扫描上评估了算法的准确性和性能。
对于 NEMA 体模，由于存在 RF 表面线圈，真实计数的总损失为 5.1％，对于大体模，总损失为 3.6％，对于患者扫描，总损失为 2.1％。在体模的顶部附近以及患者体表面附近的病变处，测量到的局部活性浓度明显低估，高达 15.4％，这与 RF 线圈的高衰减硬件组件有关。配准算法生成的衰减图将由于 RF 表面线圈引起的定量误差降低至-3.9％至 4.3％的范围内。就志愿者检查而言，三个 RF 表面线圈的衰减模板以约 3mm 的整体精度配准到其正确位置。
灵活的 RF 表面线圈的存在会导致同时测量的 PET 活性浓度在 15.5％左右产生明显的局部误差，尤其是在靠近线圈的区域。所提出的自动算法可准确可靠地将由多个部分重叠的灵活 RF 表面线圈引起的 PET 定量误差降低至 4.3％或更好的值。
