Citation: | JIANG N, YANG Y, LI G F, et al. Advances in Dual-energy CT for the Diagnosis of Solitary Pulmonary Nodules[J]. CT Theory and Applications, 2024, 33(6): 733-739. DOI: 10.15953/j.ctta.2024.066. (in Chinese). |
With the popularization of high-resolution thin-layer CT, the detection rate of early asymptomatic lung cancer that manifests as solitary pulmonary nodules has significantly increased. The differentiation of benign from malignant nodules and histopathological classification are the keys to and challenges of clinical diagnoses, the accuracy of which is of great significance for treatment decision-making. Traditional CT evaluates nodules based on their size, density, and morphological characteristics with single modal imaging. Dual-energy CT achieves material separation based on attenuation differences in the same tissue at two different energy levels, which allows CT imaging to evolve from a single-parameter to multi-parameter measurements. This not only provides more valuable information for the early and accurate diagnosis of nodules but also facilitates measurements of tumor progression and heterogeneity. In addition, the combination of radiomics based on artificial intelligence and multi-parameter images by dual-energy CT has shown great potential in diagnosis, and the related investigations are in exploratory stages. This review will cover the application of dual-energy CT in the diagnosis of solitary pulmonary nodules, with a focus on the meaning of multi-parameter images for the ccurate diagnosis of pulmonary nodules. Further, the future directions of this diagnostic imaging technique are discussed as well.
[1] |
ZHENG R S, CHEN R, HAN B F, et al. Cancer incidence and mortality in China, 2022[J]. Chinese Journal of Oncology, 2024, 46(3): 221−231. DOI: 10.3760/cma.j.cn112152-20240119-00035.
|
[2] |
ZENG H, CHEN W Q, ZHENG R S, et al. Changing cancer survival in China during 2003-15: A pooled analysis of 17 population-based cancer registries[J]. Lancet Global Health, 2018, 6(5): e555−e567. DOI: 10.1016/S2214-109X(18)30127-X.
|
[3] |
LI N, TAN F W, CHEN W Q, et al. One-off low-dose CT for lung cancer screening in China: A multicentre, population-based, prospective cohort study[J]. Lancet Respiratory Medicine, 2022, 10(4): 378−391. DOI: 10.1016/S2213-2600(21)00560-9.
|
[4] |
HENSCHKE C I, YIP R, SHAHAM D, et al. A 20-year follow-up of the international early lung cancer action program (I-ELCAP)[J]. Radiology, 2023, 309(2): e231988. DOI: 10.1148/radiol.231988.
|
[5] |
TER-POGOSSIAN M M. Basic principles of computed axial tomography[J]. Seminars in Nuclear Medicine, 1977, 7(2): 109−127. DOI: 10.1016/s0001-2998(77)80013-5.
|
[6] |
MCCOLLOUGH C H, LENG S, YU L, et al. Dual- and multi-energy CT: Principles, technical approaches, and clinical applications[J]. Radiology, 2015, 276(3): 637−653. DOI: 10.1148/radiol.2015142631.
|
[7] |
LENGA L, LEITHNER D, PETERKE J L, et al. Comparison of radiation dose and image quality of contrast-enhanced dual-source CT of the chest: Single-versus dual-energy and second-versus third-generation technology[J]. American Journal of Roentgenology, 2019, 212(4): 741−747. DOI: 10.2214/AJR.18.20065.
|
[8] |
AGOSTINI A, BORGHERESI A, MARI A, et al. Dual-energy CT: Theoretical principles and clinical applications[J]. Radiologia Medica, 2019, 124(12): 1281−1295. DOI: 10.1007/s11547-019-01107-8.
|
[9] |
HENSCHKE C I, YANKELEVITZ D F, YIP R, et al. Lung cancers diagnosed at annual CT screening: Volume doubling times[J]. Radiology, 2012, 263(2): 578−583. DOI: 10.1148/radiol.12102489.
|
[10] |
HENSCHKE C I, YANKELEVITZ D F, MIRTCHEVA R, et al. CT screening for lung cancer: Frequency and significance of part-solid and nonsolid nodules[J]. American Journal of Roentgenology, 2002, 178(5): 1053−1057. DOI: 10.2214/ajr.178.5.1781053.
|
[11] |
朱丽娟, 朱晓明, 宋冬冬, 等. AI在双源CT不同管电压下对肺结节的检测效能[J]. CT理论与应用研究, 2021, 30(4): 495−502. DOI: 10.15953/j.1004-4140.2021.30.04.10.
ZHU L J, ZHU X M, SONG D D, et al. AI detection efficiency of pulmonary nodules under dual-source CT with different tube voltages[J]. CT Theory and Applications, 2021, 30(4): 495−502. DOI: 10.15953/j.1004-4140.2021.30.04.10. (in Chinese).
|
[12] |
SNOECKX A, REYNTIENS P, DESBUQUOIT D, et al. Evaluation of the solitary pulmonary nodule: Size matters, but do not ignore the power of morphology[J]. Insights into Imaging, 2018, 9(1): 73−86. DOI: 10.1007/s13244-017-0581-2.
|
[13] |
HE C J, LIU J K, LI Y, et al. Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules[J]. Frontiers in Oncology, 2022, 12: 1027985. DOI: 10.3389/fonc.2022.1027985.
|
[14] |
傅奕铖, 余烨, 陈杏彪, 等. 双层探测器光谱CT鉴别诊断肺癌与炎性结节的价值[J]. 中华放射学杂志, 2021, 55(12): 1264−1269. DOI: 10.3760/cma.j.cn112149-20210125-00061.
FU Y C, YU Y, CHEN X B, et al. Value of dual-layer spectral detector CT in differentiating the diagnosis of lung cancer and inflammatory nodules[J]. Chinese Journal of Radiology, 2021, 55(12): 1264−1269. DOI: 10.3760/cma.j.cn112149-20210125-00061. (in Chinese).
|
[15] |
LIN J Z, ZHANG L, ZHANG C Y, et al. Application of gemstone spectral computed tomography imaging in the characterization of solitary pulmonary nodules: Preliminary result[J]. Journal of Computer Assisted Tomography, 2016, 40(6): 907−911. DOI: 10.1097/RCT.0000000000000469.
|
[16] |
ZEGADŁO A, ŻABICKA M, RÓŻYK A, et al. A new outlook on the ability to accumulate an iodine contrast agent in solid lung tumors based on virtual monochromatic images in dual energy computed tomography (DECT): Analysis in two phases of contrast enhancement[J]. Journal of Clinical Medicine, 2021, 10(9): 1870. DOI: 10.3390/jcm10091870.
|
[17] |
CHEN M L, LI X T, WEI Y Y, et al. Can spectral computed tomography imaging improve the differentiation between malignant and benign pulmonary lesions manifesting as solitary pure ground glass, mixed ground glass, and solid nodules?[J]. Thoracic Cancer, 2019, 10(2): 234−242. DOI: 10.1111/1759-7714.12937.
|
[18] |
张厚丽, 罗虎, 王康, 等. 采用双能CT构建肺结节良恶性预测模型及碘图定量参数的临床分析[J]. 中华肺部疾病杂志(电子版), 2022, 15(5): 630−636.
ZHANG H L, LUO H, WANG K, et al. Construction of a predictive model of benign and malignant pulmonary nodules using dual-energy CT and the clinical value of quantitative parameters of iodine map[J]. Chinese Journal of Lung Diseases (Electronic Edition), 2022, 15(5): 630−636. (in Chinese).
|
[19] |
ZHANG Y, CHENG J J, HUA X L, et al. Can spectral CT imaging improve the differentiation between malignant and benign solitary pulmonary nodules?[J]. PLoS One, 2016, 11(2): e0147537. DOI: 10.1371/journal.pone.0147537.
|
[20] |
邱建升, 辛小燕, 杨雯, 等. 双层探测器光谱CT单能量图像及电子云密度图鉴别诊断肺磨玻璃结节良性与恶性的价值[J]. 中华放射学杂志, 2022, 56(2): 175−181. DOI: 10.3760/cma.j.cn112149-20210205-00102.
QIU J S, XIN X Y, YANG W, et al. The value of virtual monoenergetic images and electron density map derived from dual-layer spectral detector CT in differentiating benign from malignant pulmonary ground glass nodules[J]. Chinese Journal of Radiology, 2022, 56(2): 175−181. DOI: 10.3760/cma.j.cn112149-20210205-00102. (in Chinese).
|
[21] |
黄梅萍, 兰长青, 王洁. 双源CT电子密度/有效原子序数(Rho/Z)在孤立性肺结节中的诊断价值[J]. 现代医用影像学, 2024, 33(1): 43−47. DOI: 10.3969/j.issn.1006-7035.2024.01.011.
HUANG M P, LAN C Q, WANG J. The value of dual source CT Rho/Z in diagnosis of solitary pulmonary nodules[J]. Modern Medical Imagelogy, 2024, 33(1): 43−47. DOI: 10.3969/j.issn.1006-7035.2024.01.011. (in Chinese).
|
[22] |
GONZÁLEZ-PÉREZ V, ARANA E, BARRIOS M, et al. Differentiation of benign and malignant lung lesions: Dual-energy computed tomography findings[J]. European Journal of Radiology, 2016, 85(10): 1765−1772. DOI: 10.1016/j.ejrad.2016.07.019.
|
[23] |
XU X, SUI X, ZHONG W, et al. Clinical utility of quantitative dual-energy CT iodine maps and CT morphological features in distinguishing small-cell from non-small-cell lung cancer[J]. Clinical Radiology, 2019, 74(4): 268−277. DOI: 10.1016/j.crad.2018.10.012.
|
[24] |
崔兆国, 伍建林, 宋冬冬, 等. 双能量CT碘图相关定量参数联合CT征象建模鉴别肺癌病理亚型的应用价值[J]. 检验医学与临床, 2020, 17(17): 2532−2534, 2538. DOI: 10.3969/j.issn.1672-9455.2020.17.030.
CUI Z G, WU J L, SONG D D, et al. The value of quantitative parameters associated with dual energy CT iodine graph combined with CT sign modeling in differentiating pathological subtypes of lung cancer[J]. Laboratory Medicine and Clinic, 2020, 17(17): 2532−2534, 2538. DOI: 10.3969/j.issn.1672-9455.2020.17.030. (in Chinese).
|
[25] |
ZHANG Z T, ZOU H Y, YUAN A M, et al. A single enhanced dual-energy CT scan may distinguish lung squamous cell carcinoma from adenocarcinoma during the venous phase[J]. Academic Radiology, 2020, 27(5): 624−629. DOI: 10.1016/j.acra.2019.07.018.
|
[26] |
程子珊, 李圣磊, 李文武, 等. 能谱CT多参数定量分析鉴别肺癌病理类型的应用价值[J]. 中华肿瘤防治杂志, 2022, 29(1): 59−65. DOI: 10.16073/j.cnki.cjcpt.2022.01.09.
CHENG Z S, LI S L, LI W W, et al. Value of multi-parameter quantitative analysis of spectral CT in differentiating pathological types of lung cancer[J]. Chinese Journal of Cancer Prevention and Treatment, 2022, 29(1): 59−65. DOI: 10.16073/j.cnki.cjcpt.2022.01.09. (in Chinese).
|
[27] |
DENIFFEL D, SAUTER A, FINGERLE A, et al. Improved differentiation between primary lung cancer and pulmonary metastasis by combining dual-energy CT-derived biomarkers with conventional CT attenuation[J]. European Radiology, 2021, 31(2): 1002−1010. DOI: 10.1007/s00330-020-07195-9.
|
[28] |
SATO Y, ISHIYAMA M, NAKANO S, et al. Ringlike peripheral increased iodine concentration for the differentiation of primary lung cancer and pulmonary metastases on contrast-enhanced dual-energy CT[J]. American Journal of Roentgenology, 2023, 220(6): 828−837. DOI: 10.2214/AJR.22.28654.
|
[29] |
YANG Y, LI K H, SUN D D, et al. Invasive pulmonary adenocarcinomas versus preinvasive lesions appearing as pure ground-glass nodules: Differentiation using enhanced dual-source dual-energy CT[J]. American Journal of Roentgenology, 2019, 213(3): W114−W122. DOI: 10.2214/AJR.19.21245.
|
[30] |
WANG S Q, LIU G Q, FU Z H, et al. Predicting pathological invasiveness of lung adenocarcinoma manifesting as ggo-predominant nodules: A combined prediction model generated from DECT[J]. Academic Radiology, 2021, 28(4): 509−516. DOI: 10.1016/j.acra.2020.03.007.
|
[31] |
CHEN M W, DING L, DENG S T, et al. Differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules: Combination of dual-energy CT parameters and quantitative-semantic features[J]. Academic Radiology, 2024, 19: S1076-6332(24)00082-5. DOI: 10.1016/j.acra.2024.02.011.
|
[32] |
武卫杰, 岳松伟, 吕培杰, 等. 能谱CT平扫多参数成像判断纯磨玻璃密度肺腺癌病理亚型[J]. 中国医学影像技术, 2020, 36(6): 858−862. DOI: 10.13929/j.issn.1003-3289.2020.06.013.
WU W J, YUE S W, LV P J, et al. Spectral CT plain multi-parameter imaging in differentiating pathological subtypes of pure ground glass opacity lung adenocarcinoma[J]. Chinese Journal of Medical Imaging Technology, 2020, 36(6): 858−862. DOI: 10.13929/j.issn.1003-3289.2020.06.013. (in Chinese).
|
[33] |
GAO L, WEI Y, LIU S Q, et al. The value of radiomics based on dual-energy CT for differentiating benign from malignant solitary pulmonary nodules[J]. BMC Medical Imaging, 2022, 22(1): 95. DOI: 10.1186/s12880-022-00824-3.
|
[34] |
CHEN Z Y, YI L, PENG Z W, et al. Development and validation of a radiomic nomogram based on pretherapy dual-energy CT for distinguishing adenocarcinoma from squamous cell carcinoma of the lung[J]. Frontiers in Oncology, 2022, 12: 949111. DOI: 10.3389/fonc.2022.949111.
|
[35] |
ZHENG Y T, HAN X Y, JIA X, et al. Dual-energy CT-based radiomics for predicting invasiveness of lung adenocarcinoma appearing as ground-glass nodules[J]. Frontiers in Oncology, 2023, 13: 1208758. DOI: 10.3389/fonc.2023.1208758.
|
[36] |
WANG Y, CHEN H B, CHEN Y Y, et al. A semiautomated radiomics model based on multimodal dual-layer spectral CT for preoperative discrimination of the invasiveness of pulmonary ground-glass nodules[J]. Journal of Thoracic Disease, 2023, 15(5): 2505−2516. DOI: 10.21037/jtd-22-1605.
|
[37] |
WU L H, LI J, RUAN X W, et al. Prediction of VEGF and EGFR expression in peripheral lung cancer based on the radiomics model of spectral CT enhanced images[J]. International Journal of General Medicine, 2022, 15: 6725−6738. DOI: 10.2147/IJGM.S374002.
|
[38] |
MA J W, JIANG X, WANG Y M, et al. Dual-energy CT-based radiomics in predicting EGFR mutation status non-invasively in lung adenocarcinoma[J]. Heliyon, 2024, 10(2): e24372. DOI: 10.1016/j.heliyon.2024.e24372.
|
1. |
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