采用光子计数测量的高灵敏度锥束XLCT
X-ray luminescence computed tomography (XLCT) technology uses X-ray excitation to stimulate specific luminescent materials at the nanoscale, termed phosphor nanoparticles (PNPs), to produce near-infrared light. Photodetectors then capture the emitted near-infrared light signals from these excited PNPs. Through suitable algorithms, the distribution of PNPs within biological tissues can be visualized. This method allows for structural and functional insights into biological tissues, showing great potential for advancement. There are two main types of XLCT systems: narrow-beam and cone-beam. The narrow-beam XLCT system exhibits higher spatial resolution, albeit at the cost of lower X-ray utilization efficiency. This inefficiency results in extended imaging times, limiting its potential for clinical use. Conversely, the cone-beam XLCT system improves X-ray efficiency and shortens detection time. However, the quality of the reconstructed images tends to be lower due to detection angle limitations. To overcome these challenges, there is a need for an innovative XLCT system that realizes rapid and highly sensitive data collection while also maximizing the use of X-ray technology. By addressing these issues, the clinical limitations of XLCT can be reduced to pave the way for its further development, thereby unlocking a plethora of possibilities.
This study introduces a new cone-beam XLCT system based on photon-counting measurements, complemented by an associated reconstruction method. Through the synergistic collaboration between the field-programmable gate array (FPGA) based sub-sampling unit and upper-level control unit, the system realizes automated multi-channel measurements. This integration shortens data acquisition time, boosts experimental efficiency, and mitigates the risks associated with X-ray exposure. After the completion of system implementation, we conduct experimental validation of the system and methodology. Specifically, a fabricated phantom is subjected to multi-angle projection measurements using the established system, and image reconstruction and evaluation are performed using the Tikhonov reconstruction algorithm.
The results of the dual target phantom experiment indicate that under the conditions of a cylindrical phantom radius of 40 mm, target radius of 6 mm, and distance of 14 mm from the dual target phantom (Fig.2), the similarity coefficient (DICE) of the reconstructed image of the dual target phantom exceeds 50% under six-angle cone-beam X-ray irradiation. Furthermore, the system fidelity (SF) exceeds 0.7 (Table 1). In the phantom experiment of dual targets with different concentrations, the system proposed in this study effectively distinguishes dual targets with a mass concentration difference of more than 3 mg/mL. The DICE of the reconstruction image maintains over 50%, SF remains over 0.7, and reconstruction concentration error (RCE) is also over 0.7 (Table 2). These phantom experiment results confirm the good fidelity and resolution capability of the proposed system. Nevertheless, numerous factors potentially degrade the experimental outcomes, such as the attenuation and scattering of X-ray beams in the XLCT system, the physical and chemical composition of the target body, or even uneven concentration distribution. Additionally, artifacts appear in the reconstructed images. In the future, our research will focus on optimizing algorithms and reducing noise to enhance the application of cone-beam XLCT for in vivo experiments.
This study comprehensively considers the advantages and disadvantages of two imaging methods in XLCT and proposes a photon-counting-based multi-channel cone-beam XLCT system. The system automation for multi-angle measurements is realized via FPGA and host computer interaction. Specifically, multi-angle cone-beam irradiation reduces data acquisition time, while photon-counting measurement enhances the system sensitivity. Furthermore, a phantom experiment is conducted to validate the effectiveness and practicality of the proposed system and algorithm. The results demonstrate a significant reduction in data acquisition time and an improvement in the utilization of X-rays.
1 引言
X射线激发发光断层成像(XLCT)是一种新兴的混合成像技术,该技术主要通过X射线特异性激发生物组织体内的纳米荧光物质发出近红外光信号,随后使用重建算法恢复测量组织中纳米磷光物质的空间分布,从而获得组织体内的功能信息,再结合传统计算机断层成像(CT)技术实现生物体结构信息和功能信息的双模态成像。与传统的光学分子成像技术相比,XLCT具有以下优点:1) 成像深度深,空间分辨率高。在XLCT中,X射线作为激励源,穿透生物组织体的能力强,可使XLCT具有更深的检测深度及更高的空间分辨率。尤其是对于深度大于几毫米的生物目标,如通常位于皮肤以下10 mm处的肿瘤,也可以实现高达数百微米的空间分辨率[1]。2) 无背景荧光以及自体荧光干扰。在成像过程中,XLCT可以消除传统荧光成像中的背景荧光和自体荧光的干扰,获得更高信噪比的测量信号[2]。3) 能够实现结构与功能双模态成像。一次X射线激发,可以同时获得结构成像和功能成像,减少了成像时间与成本[3]。近年来,纳米荧光技术的不断发展,为XLCT提供了更多可能,拓宽了其应用范围。
自XLCT被提出以来,国内外很多研究机构都对XLCT展开了研究。根据X射线的激发模式,把XLCT系统大体分为窄束成像系统和锥束成像系统,两种成像系统各有优缺点。2010年,Pratx等[4]第一次提出将XLCT系统用于分子成像,提出窄束XLCT(NB-XLCT)系统,验证了XLCT的可能性,为XLCT技术的发展奠定了基础。在窄束XLCT系统中,大多数探测器件选择具有高灵敏度、大动态范围的光电倍增管(PMT),PMT可将微弱的输入光转换为电脉冲序列[5],这能够提高系统测量的灵敏度。但是,在窄束XLCT系统的成像方式下,由于X射线被准直器遮挡,X射线的利用效率很低,并且系统需要通过平移旋转等操作依次扫描成像物体,故数据测量的时间较长。随着XLCT系统的进一步发展,2013年,Chen等[6]设计并实现了锥束XLCT(CB-XLCT)系统。基于锥束XLCT系统,一次X射线照射能够覆盖整个待测物体,系统无须进行平移操作,大幅缩短了数据采集时间并提高了X射线的利用率。然而,光在生物组织中具有高散射特性,且在一次扫描过程中,成像体内所有的纳米荧光物质都会被激励,这加剧了图像重建逆问题的不适定性[7]。此外,锥束XLCT系统大多以电子倍增电荷耦合器件(EMCCD)作为探测器,而EMCCD在一个角度下的探测范围有限,这直接影响了锥束XLCT的空间分辨率,同时EMCCD造价昂贵,性价比较低,导致实验成本较高。
为解决上述问题,提高X射线利用率和系统测量的灵敏度,本文提出了一种基于光子计数测量的锥束XLCT系统,通过光电倍增管(PMT)探测成像物体表面的光信号,提高了探测灵敏度,降低了实验成本,多角度锥束照射能够在提高X射线利用率的同时实现目标体的快速扫描。在系统调试完成后,我们进行了仿体实验,并通过图像重建进一步验证了所提系统的可行性,实验证明所提系统具有良好的保真度和系统分辨力。
2 系统设计
本文提出了一种基于光子计数测量的多通道锥束XLCT系统,如
图 1. XLCT系统图。(a)XLCT系统原理图;(b)XLCT系统实物图
Fig. 1. XLCT system diagrams. (a) Schematic of XLCT system; (b) physical image of XLCT system
本文所提系统基于单个PMT发展了多角度锥束照射策略,显著降低了系统研制成本,锥束X射线照射提高了X射线的利用率,缩短了数据采集时间;使用PMT进行信号采集,提高了系统测量灵敏度,有效降低了XLCT技术临床应用的壁垒。
3 XLCT理论模型
3.1 XLCT正向模型
锥束X射线激发纳米荧光物质发光的正向过程可以分为三个阶段。首先,X射线源发射锥束X射线并与成像物体相互作用。根据朗伯-比尔定律,此过程可建模[8-9]为
式中:
其次,成像物体内的纳米荧光物质经过X射线激发后产生可见光或近红外光,该发射光线性关系[4]可表示为
式中:
生物软组织对近红外光具有强散射、弱吸收特性,因此可以采用辐射传输方程(RTE)描述光子输运轨迹[8]。由于RTE求解复杂,通常以球谐近似方式简化RTE,即扩散方程(DE)[10]为
式中:
结合罗宾边界条件(RBC)耦合建模后,基于有限元方法,将成像区域离散成四面体网格[11],
式中:
式中:
式中:
3.2 XLCT逆向问题
XLCT逆向问题求解即利用光敏探测器捕获的待测物体表面的近红外光测量数据
由于方程(7)为非适定方程,直接求解
式中:
式中:
4 仿体实验
4.1 实验仿体设计
为更好验证所提系统的可行性,我们设计了仿体实验。在仿体实验中,我们设计的双目标圆柱形仿体模型如
4.2 图像重建评价指标
为了更好地研究本文所提系统在图像重建方面的效果,对重建结果进行了定量评估。本文采用的评估指标分别为位置误差(LE)、相似度系数(DICE)、均方误差(MSE)、系统保真度(SF)。
位置误差[16]用来评价图像内重建目标体的位置准确度。LE值越小,表明重建目标体的几何中心与真实目标体的差异越小。表达式为
式中:
相似度系数[17]用来评价重建图像中目标体的形状与位置的准确程度,其表达式为
式中:
均方误差[18]用来评价重建图像的精度。MSE越小,表明重建的图像与真实图像间的差异越小。表达式为
式中:
系统保真度[19]用来表示重建结果与真实结果的对应性。SF越接近1,表明系统保真度越高。表达式为
式中:
4.3 多角度锥束X射线照射实验
在仿体配置完成之后,我们通过差分测量方式[20],基于校正后的实验数据,使用Tikhonov正则化方法进行图像重建,获得双目标仿体的重建二维横截面图像(Z=40 mm)。
图 3. 双目标体仿体多角度锥束照射实验结果。(a)图像重建结果;(b)重建浓度曲线
Fig. 3. Dual target phantom experimental results under multi-angle cone-beam irradiation. (a) Reconstructed images; (b) reconstructed concentration curves
在多角度锥束X射线照射实验中,双目标体荧光物质的质量浓度均为5 mg·mL-1。从
表 1. 多角度锥束照射双目标仿体实验图像评价指标计算结果
Table 1. Calculation results of image evaluation indicators for dual target phantom experiments under multi-angle cone-beam irradiation
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4.4 系统分辨力评估实验
为验证本文所提系统的分辨能力,我们进行了不同荧光物质浓度双目标仿体实验以验证系统对不同浓度目标体的分辨能力,并引入重建浓度误差(RCE)评价指标。RCE反映了系统对不同浓度目标体的分辨能力,RCE越接近1,表示系统对不同浓度目标体的分辨能力越强,表达式为
式中:
从
图 4. 不同浓度双目标仿体实验结果。(a)图像重建结果;(b)重建浓度曲线
Fig. 4. Results of dual target phantom experiments with different concentrations. (a) Reconstructed images; (b) reconstructed concentration curves
表 2. 不同目标体浓度仿体实验图像评价指标计算结果
Table 2. Calculation results of image evaluation indicators for dual target phantom experiments with different target concentrations
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5 结论
综合考量XLCT两种成像方式的优缺点,提出了一种基于光子计数测量的多通道锥束XLCT系统,并且通过FPGA与上位机交互实现了系统的自动化测量,多角度锥束照射缩短了数据采集时间,光子计数技术提高了系统的灵敏度。经过调试,该系统能够达到预期目标,大幅缩短了数据采集时间并提高了X射线的利用率。为验证所提系统的可行性与重建算法的有效性,进行了仿体实验,并利用实验数据进行图像重建。
双目标仿体实验结果表明,当圆柱形仿体半径为40 mm,目标体半径为6 mm,双目标体间的距离为14 mm时,6个角度的锥束X射线照射下双目标体的重建图像的相似度系数DICE能达到50%以上,系统保真度SF达到0.7以上。在不同浓度的双目标仿体实验中,所提系统能有效分辨出质量浓度差距在3 mg·mL-1以上的双目标体,重建图像的相似度系数DICE仍然可以达到50%以上,系统保真度SF依然可以达到0.7以上,并且重建浓度误差RCE也达到了0.7以上。仿体实验结果验证了所提系统具有良好的系统保真度和分辨能力。但是在实验过程中,还存在许多其他因素导致结果恶化,例如XLCT系统中X射线束的衰减和散射、目标体的物理结构和化学组成甚至是浓度分布不均等都可能导致实验结果恶化,与此同时,在重建图像中有伪影的出现。算法的优化以及噪声的削弱上将会成为我们下一步关注的重点以及未来改进的方向,从而实现锥束XLCT在在体实验中的应用。
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Article Outline
韩景灏, 贾梦宇, 周仲兴, 高峰. 采用光子计数测量的高灵敏度锥束XLCT[J]. 中国激光, 2024, 51(3): 0307102. Jinghao Han, Mengyu Jia, Zhongxing Zhou, Feng Gao. High‑Sensitivity Cone‑Beam XLCT Using Photon Counting Measurements[J]. Chinese Journal of Lasers, 2024, 51(3): 0307102.