Contrast-to-noise ratio comparison between X-ray fluorescence emission tomography and computed tomography.

IF 1.9 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Journal of Medical Imaging Pub Date : 2024-12-01 Epub Date: 2024-10-15 DOI:10.1117/1.JMI.11.S1.S12808

Hadley DeBrosse, Giavanna Jadick, Ling Jian Meng, Patrick La Rivière

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引用次数: 0

Abstract

Purpose: We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT).

Approach: We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs.

Results: For the mouse phantom, XFET produced superior CNR values ( $CNRs = 24.5$ , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( $CNR = 4.4$ , 4.6, and 1.5) and photon-counting ( $CNR = 6.5$ , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( $< 28.75 mm$ ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16 mGy compatible with in vivo imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of $\sim 81.6 cGy$ to a localized region of interest.

Conclusions: We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for in vivo metal mapping in preclinical imaging tasks.

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X 射线荧光发射断层扫描与计算机断层扫描的对比度与噪声比。

目的：我们对 X 射线荧光发射断层成像（XFET）和计算机断层扫描（CT）检测软组织中低浓度金纳米粒子（GNPs）的方法进行了比较，并确定了 XFET 优于能量积分 CT（EICT）和光子计数 CT（PCCT）的条件：方法：我们将剂量匹配的蒙特卡罗 XFET 模拟与分析扇形光束 EICT 和 PCCT 模拟进行了比较。每种模式都用于对一个数值小鼠模型和对比度深度模型进行成像，模型中的软组织含有按重量计从 0.05% 到 4% 不等的 GNP。比较了三种模式下金区域的对比度-噪声比（CNR），并根据罗斯标准量化了 XFET 的检测极限。对含有 0.05% GNPs 的模型区域采集了部分视场（FOV）图像：对于小鼠模型，XFET 产生的 CNR 值（CNR = 24.5、21.6 和 3.4）优于使用能量积分（CNR = 4.4、4.6 和 1.5）和光子计数（CNR = 6.5、7.7 和 2.0）检测系统获得的 CT 图像。总体而言，对于金浓度在 0.5% 及以上的浅层成像深度（28.75 毫米），XFET 的性能优于 CT。XFET 的表面检测极限被量化为 0.44%，平均模型剂量为 16 mGy，符合体内成像。XFET 对部分 FOV 的成像能力得到了证明，在局部感兴趣区域的估计剂量为 ∼ 81.6 cGy 时，0.05% 的金很容易被检测到：结论：我们证明了 XFET 在浅层低浓度金成像方面的优势，以及 XFET 在临床前成像任务中用于体内金属绘图的可行性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-

CiteScore

4.10

自引率

4.20%

发文量

期刊介绍： JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.