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从双源能量积分CT和光子计数CT数据重建的虚拟单能图像中碘对比噪声比的评估

Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data.

作者信息

Booij Ronald, van der Werf Niels R, Dijkshoorn Marcel L, van der Lugt Aad, van Straten Marcel

机构信息

Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands.

出版信息

Diagnostics (Basel). 2022 Jun 14;12(6):1467. doi: 10.3390/diagnostics12061467.

DOI:10.3390/diagnostics12061467
PMID:35741277
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9222007/
Abstract

To evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two anthropomorphic phantoms in three different sizes (thorax and abdomen, QRM GmbH), in combination with a custom-built insert containing cavities filled with water, and water with 15 mg iodine/mL, were scanned on an EID-based scanner (Siemens SOMATOM Force) and on a PCD-based scanner (Siemens, NAEOTOM Alpha). VMI (range 40−100 keV) were reconstructed without an iterative reconstruction (IR) technique and with an IR strength of 60% for the EID technique (ADMIRE) and closest matching IR strengths of 50% and 75% for the PCD technique (QIR). CNR was defined as the difference in mean CT numbers of water, and water with iodine, divided by the root mean square value of the measured noise in water, and water with iodine. A two-sample t-test was performed to evaluate differences in CNR between images. A p-value < 0.05 was considered statistically significant. For VMI without IR and below 60 keV, the CNR of the PCD-based images at 120 and 90 kVp was up to 55% and 75% higher than the CNR of the EID-based images, respectively (p < 0.05). For VMI above 60 keV, CNRs of PCD-based images at both 120 and 90 kVp were up to 20% lower than the CNRs of EID-based images. Similar or improved performance of PCD-based images in comparison with EID-based images were observed for VMIs reconstructed with IR techniques. In conclusion, with PCD-CT, iodine CNR on low energy VMI (<60 keV) is better than with EID-CT.

摘要

为了评估首款临床光子计数探测器(PCD)CT扫描仪生成的虚拟单能图像(VMI)中碘化造影剂的对比噪声比(CNR)是否优于具有能量积分探测器(EID)的双源双能CT扫描仪的VMI CNR,将三个不同尺寸的仿真人体模型(胸部和腹部,QRM GmbH)与一个定制插件相结合进行扫描,该插件包含充满水以及含有15 mg碘/ mL碘的水的腔室,分别在基于EID的扫描仪(西门子SOMATOM Force)和基于PCD的扫描仪(西门子,NAEOTOM Alpha)上进行扫描。VMI(范围40 - 100 keV)在未使用迭代重建(IR)技术的情况下进行重建,对于EID技术(ADMIRE)使用60%的IR强度,对于PCD技术(QIR)使用最接近匹配的50%和75%的IR强度。CNR定义为水和含碘水的平均CT值之差除以水和含碘水中测量噪声的均方根值。进行双样本t检验以评估图像之间CNR的差异。p值<0.05被认为具有统计学意义。对于未使用IR且低于60 keV的VMI,基于PCD的图像在120和90 kVp时的CNR分别比基于EID的图像的CNR高55%和75%(p < 0.05)。对于高于60 keV的VMI,基于PCD的图像在120和90 kVp时的CNR比基于EID的图像的CNR低达20%。对于使用IR技术重建的VMI,观察到基于PCD的图像与基于EID的图像相比具有相似或更好的性能。总之,使用PCD - CT时,低能量VMI(<60 keV)上的碘CNR优于EID - CT。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/290f307c3df6/diagnostics-12-01467-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/d8099db489b3/diagnostics-12-01467-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/ddedb96c029c/diagnostics-12-01467-g0A2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/9783eb7a8a86/diagnostics-12-01467-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/4783b305a7f6/diagnostics-12-01467-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/652c8f7005ad/diagnostics-12-01467-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/290f307c3df6/diagnostics-12-01467-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/d8099db489b3/diagnostics-12-01467-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/ddedb96c029c/diagnostics-12-01467-g0A2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/9783eb7a8a86/diagnostics-12-01467-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/4783b305a7f6/diagnostics-12-01467-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/652c8f7005ad/diagnostics-12-01467-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ceb/9222007/290f307c3df6/diagnostics-12-01467-g004.jpg

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