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对比增强胸部CT上的肺实变:光谱探测器计算机断层扫描参数在区分肺不张和肺炎中的应用

Consolidated lung on contrast-enhanced chest CT: the use of spectral-detector computed tomography parameters in differentiating atelectasis and pneumonia.

作者信息

Konietzke Philip, Steentoft Hauke H, Wagner Willi L, Albers Jonas, Dullin Christian, Skornitzke Stephan, Stiller Wolfram, Weber Tim F, Kauczor Hans-Ulrich, Wielpütz Mark O

机构信息

Diagnostic and Interventional Radiology (DiR), Heidelberg University Hospital, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany.

Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Im Neuenheimer Feld 156, 69120 Heidelberg, Germany.

出版信息

Heliyon. 2021 May 26;7(5):e07066. doi: 10.1016/j.heliyon.2021.e07066. eCollection 2021 May.

Abstract

OBJECTIVES

To investigate the value of spectral-detector computed tomography (SDCT) parameters for the quantitative differentiation between atelectasis and pneumonia on contrast-enhanced chest CT.

MATERIAL AND METHODS

Sixty-three patients, 22 clinically diagnosed with pneumonia and 41 with atelectasis, underwent contrast-enhanced SDCT scans during the venous phase. CT numbers (Hounsfield Units [HU]) were measured on conventional reconstructions (CON) and the iodine concentration (C, [mg/ml]), and effective atomic number (Z) on spectral reconstructions, using region-of-interest (ROI) analysis. Receiver operating characteristics (ROC) and contrast-to-noise ratios (CNRs) were calculated to assess each reconstruction's potential to differentiate between atelectasis and pneumonia.

RESULTS

On contrast-enhanced SDCT, the difference between atelectasis and pneumonia was significant on CON, C, and Z images (p < 0.001). On CON images, a threshold of 81 HU achieved a sensitivity of 93 % and a specificity of 95 % for identifying pneumonia, while C and Z images reached the same sensitivity but lower specificities of 85 % and 83 %. CON images showed significantly higher CNRs between normal lung and atelectasis or pneumonia with 30.63 and 27.69 compared to C images with 3.54 and 1.27 and Z images with 4.22 and 7.63 (p < 0.001). None of the parameters could differentiate atelectasis and pneumonia without contrast media.

CONCLUSIONS

Contrast-enhanced SDCT can differentiate atelectasis and pneumonia based on the spectral parameters C, and Z However, they had no added value compared to CT number measurement on CON images. Furthermore, contrast media is still needed for a differentiation based on quantitative SDCT parameters.

摘要

目的

探讨光谱探测器计算机断层扫描(SDCT)参数在增强胸部CT上对肺不张和肺炎进行定量鉴别的价值。

材料与方法

63例患者,其中22例临床诊断为肺炎,41例为肺不张,在静脉期进行增强SDCT扫描。使用感兴趣区(ROI)分析,在常规重建(CON)图像上测量CT值(亨氏单位[HU]),在光谱重建图像上测量碘浓度(C,[mg/ml])和有效原子序数(Z)。计算受试者工作特征(ROC)曲线和对比噪声比(CNR),以评估每种重建方式区分肺不张和肺炎的潜力。

结果

在增强SDCT上,肺不张和肺炎在CON、C和Z图像上的差异具有统计学意义(p < 0.001)。在CON图像上,81 HU的阈值对肺炎的识别灵敏度为93%,特异性为95%,而C和Z图像达到相同的灵敏度,但特异性较低,分别为85%和83%。CON图像显示正常肺与肺不张或肺炎之间的CNR显著高于C图像(分别为30.63和27.69,C图像为3.54和1.27,Z图像为4.22和7.63,p < 0.001)。在无对比剂的情况下,没有参数能够区分肺不张和肺炎。

结论

增强SDCT可根据光谱参数C和Z区分肺不张和肺炎。然而,与CON图像上的CT值测量相比,它们没有额外价值。此外,基于定量SDCT参数进行鉴别仍需要使用对比剂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bd4/8170158/17136e9f112f/gr1.jpg

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本文引用的文献

1
Quantitative distribution of iodinated contrast media in body computed tomography: data from a large reference cohort.
Eur Radiol. 2021 Apr;31(4):2340-2348. doi: 10.1007/s00330-020-07298-3. Epub 2020 Sep 30.
2
Technical background of a novel detector-based approach to dual-energy computed tomography.
Diagn Interv Radiol. 2020 Jan;26(1):68-71. doi: 10.5152/dir.2019.19136.
3
Computed tomography scan contribution to the diagnosis of community-acquired pneumonia.
Curr Opin Pulm Med. 2019 May;25(3):242-248. doi: 10.1097/MCP.0000000000000567.
4
Dual-Energy CT-derived Iodine Maps: Use in Assessing Pleural Carcinomatosis.
Radiology. 2019 Mar;290(3):796-804. doi: 10.1148/radiol.2018181567. Epub 2019 Jan 15.
8
Analysis of contrast time-enhancement curves to optimise CT pulmonary angiography.
Clin Radiol. 2017 Apr;72(4):340.e9-340.e16. doi: 10.1016/j.crad.2016.11.018. Epub 2016 Dec 24.
9
A Quantitative Approach to Distinguish Pneumonia From Atelectasis Using Computed Tomography Attenuation.
J Comput Assist Tomogr. 2016 Sep-Oct;40(5):746-51. doi: 10.1097/RCT.0000000000000438.
10
Principal component analysis: a review and recent developments.
Philos Trans A Math Phys Eng Sci. 2016 Apr 13;374(2065):20150202. doi: 10.1098/rsta.2015.0202.

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