Use quantitative parameters in spectral computed tomography for the differential diagnosis of metastatic mediastinal lymph nodes in lung cancer patients.

Lymph node metastasis lung cancer spectral computed tomography (spectral CT)

Journal

Journal of thoracic disease
ISSN: 2072-1439
Titre abrégé: J Thorac Dis
Pays: China
ID NLM: 101533916

Informations de publication

Date de publication:
Aug 2021
Historique:
received: 08 03 2021
accepted: 23 06 2021
entrez: 16 9 2021
pubmed: 17 9 2021
medline: 17 9 2021
Statut: ppublish

Résumé

Accurate diagnosis of mediastinal lymph node (LN) metastases is very important for the treatment and prognosis in lung cancer patients. Spectral computed tomography (CT), as a non-invasive approach, has good prospects for detecting mediastinal nodal metastasis. However, the diagnostic criteria of differentiating metastatic and nonmetastatic LNs have not been determined. Clinical and imaging data of 64 lung cancer patients (mean age 61.3±10.3 years, 41 men) from April to December 2019 were retrospectively analyzed. The unenhanced scan and contrast enhanced arterial phase (AP) and venous phase (VP) spectral CT scans were performed. The 70 keV monochromatic image and iodine-based image in all phases were analyzed to measure the parameters of LNs. LNs were divided into the metastatic and non-metastatic groups based on confirmative pathological results, and their differences were statistically analyzed. The receiver operating characteristics curve (ROC) was used to evaluate the efficacy of the differential diagnosis. Seventy-four metastatic LNs and 152 non-metastatic LNs were obtained. Compared with non-metastatic LNs, metastatic LNs often had a larger size (P<0.001). In the unenhanced scans, the density of metastatic LNs was lower than that of non-metastatic LNs (P<0.001); however, there was no difference in CT value in AP and VP between metastatic and non-metastatic LNs (P=0.07, P=0.08, respectively). A statistically significant difference was found in iodine concentration (IC), normalized iodine concentration (NIC) and slope of the spectral curve (λHU) in unenhanced scan, IC and λHU in AP, as well as IC, NIC and λHU in VP between metastatic and non-metastatic LNs. There was no difference in NIC in AP between them. Combined with morphology, spectral CT quantitative parameters demonstrate certain diagnostic efficiency for differential diagnosis between metastatic and non-metastatic LNs in lung cancer patients.

Sections du résumé

BACKGROUND BACKGROUND
Accurate diagnosis of mediastinal lymph node (LN) metastases is very important for the treatment and prognosis in lung cancer patients. Spectral computed tomography (CT), as a non-invasive approach, has good prospects for detecting mediastinal nodal metastasis. However, the diagnostic criteria of differentiating metastatic and nonmetastatic LNs have not been determined.
METHODS METHODS
Clinical and imaging data of 64 lung cancer patients (mean age 61.3±10.3 years, 41 men) from April to December 2019 were retrospectively analyzed. The unenhanced scan and contrast enhanced arterial phase (AP) and venous phase (VP) spectral CT scans were performed. The 70 keV monochromatic image and iodine-based image in all phases were analyzed to measure the parameters of LNs. LNs were divided into the metastatic and non-metastatic groups based on confirmative pathological results, and their differences were statistically analyzed. The receiver operating characteristics curve (ROC) was used to evaluate the efficacy of the differential diagnosis.
RESULTS RESULTS
Seventy-four metastatic LNs and 152 non-metastatic LNs were obtained. Compared with non-metastatic LNs, metastatic LNs often had a larger size (P<0.001). In the unenhanced scans, the density of metastatic LNs was lower than that of non-metastatic LNs (P<0.001); however, there was no difference in CT value in AP and VP between metastatic and non-metastatic LNs (P=0.07, P=0.08, respectively). A statistically significant difference was found in iodine concentration (IC), normalized iodine concentration (NIC) and slope of the spectral curve (λHU) in unenhanced scan, IC and λHU in AP, as well as IC, NIC and λHU in VP between metastatic and non-metastatic LNs. There was no difference in NIC in AP between them.
CONCLUSIONS CONCLUSIONS
Combined with morphology, spectral CT quantitative parameters demonstrate certain diagnostic efficiency for differential diagnosis between metastatic and non-metastatic LNs in lung cancer patients.

Identifiants

pubmed: 34527311
doi: 10.21037/jtd-21-385
pii: jtd-13-08-4703
pmc: PMC8411177
doi:

Types de publication

Journal Article

Langues

eng

Pagination

4703-4713

Informations de copyright

2021 Journal of Thoracic Disease. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jtd-21-385). The work of HC was supported by the Natural Science Foundation of Guangdong Province, China (2019A1515011382) and the Science and Technology Planning Project of Guangzhou, Guangdong Province, China (201904010130). The work of Suidan Huang was supported by 2019 Achievement Transformation and Cultivation Project of the First Affiliated Hospital of Guangzhou Medical University (ZH201906). The other authors have no conflicts of interest to declare.

Références

Hum Pathol. 2013 Aug;44(8):1586-96
pubmed: 23522064
Radiol Clin North Am. 2018 Jul;56(4):497-506
pubmed: 29936943
Respirology. 2015 Jan;20(1):129-37
pubmed: 25263085
Surg Oncol. 2012 Sep;21(3):230-6
pubmed: 22197027
J Thorac Oncol. 2015 Nov;10(11):1515-22
pubmed: 26536193
Ann Thorac Surg. 2017 Dec;104(6):1805-1814
pubmed: 29102039
Medicine (Baltimore). 2017 Jul;96(28):e7479
pubmed: 28700488
J Thorac Cardiovasc Surg. 2011 Dec;142(6):1393-400.e1
pubmed: 21963329
Invest Radiol. 2012 Jan;47(1):65-70
pubmed: 21934517
Diagn Interv Radiol. 2011 Sep;17(3):181-94
pubmed: 20945292
Acad Radiol. 2018 Nov;25(11):1398-1404
pubmed: 29752156
Eur J Radiol. 2015 Feb;84(2):228-34
pubmed: 25497234
Eur J Surg Oncol. 2015 Nov;41(11):1464-70
pubmed: 26329783
Eur Radiol. 2014 Aug;24(8):1981-8
pubmed: 24895031
Acta Otolaryngol. 2015 Jul;135(7):722-8
pubmed: 25719763
Diagn Interv Imaging. 2014 Nov;95(11):1017-26
pubmed: 24780370
Eur Radiol. 2018 Feb;28(2):760-769
pubmed: 28835993
Med Sci Monit. 2020 Jun 02;26:e922675
pubmed: 32483109
Histopathology. 2001 May;38(5):466-70
pubmed: 11422485
Med Clin North Am. 2019 May;103(3):463-473
pubmed: 30955514
Eur Radiol. 2012 May;22(5):1008-13
pubmed: 22134894
Eur Radiol. 2018 Dec;28(12):5241-5249
pubmed: 29869176
J Thorac Oncol. 2016 Jan;11(1):39-51
pubmed: 26762738
Chin J Cancer Res. 2013 Dec;25(6):722-8
pubmed: 24385700
Curr Opin Pulm Med. 2010 Jul;16(4):307-14
pubmed: 20453649
Eur J Radiol. 2016 Jun;85(6):1219-23
pubmed: 27161073
J Clin Oncol. 2015 Jul 20;33(21):2370-5
pubmed: 26077238
Oncology. 2021;99(2):96-104
pubmed: 32980838
J Thorac Oncol. 2015 Dec;10(12):1675-84
pubmed: 26709477
J Clin Oncol. 2017 Apr 10;35(11):1162-1170
pubmed: 28029318

Auteurs

Suidan Huang (S)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Hongjia Meng (H)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Renli Cen (R)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Zhiwen Ni (Z)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Xiaoling Li (X)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Sushant Suwal (S)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Huai Chen (H)

Department of Radiology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Classifications MeSH