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A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography

Object: By retrospectively analyzing the energy spectrum of squamous cell carcinoma, adenocarcinoma, small cell lung cancer (SCLC), and pulmonary metastases that underwent dual-layer detector spectral computed tomography (DLCT) 3-phase scan of the chest, we explored the value of a multiparameter ene...

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Autores principales: Ma, Xia, Xu, Ming, Tian, Xiao-Juan, Liu, Yong-Li, Zhang, Xin-Ri, Qiao, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811431/
https://www.ncbi.nlm.nih.gov/pubmed/35099325
http://dx.doi.org/10.1177/15330338221074498
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author Ma, Xia
Xu, Ming
Tian, Xiao-Juan
Liu, Yong-Li
Zhang, Xin-Ri
Qiao, Ying
author_facet Ma, Xia
Xu, Ming
Tian, Xiao-Juan
Liu, Yong-Li
Zhang, Xin-Ri
Qiao, Ying
author_sort Ma, Xia
collection PubMed
description Object: By retrospectively analyzing the energy spectrum of squamous cell carcinoma, adenocarcinoma, small cell lung cancer (SCLC), and pulmonary metastases that underwent dual-layer detector spectral computed tomography (DLCT) 3-phase scan of the chest, we explored the value of a multiparameter energy spectrum in the assessment of pathological types of lung tumors. Methods: Cases of squamous cell carcinoma (n = 20), adenocarcinoma (n = 24), SCLC (n = 26), and metastases (n = 14) were collected. Then the largest cross-sectional area (LCA) of the lesion, computed tomography (CT) values in the plain scan phase, arterial and venous phases (HU, HUa, and HUv), iodine concentration, and effective atomic number in the arterial and venous phases (ICa, ICv, Zeff[a], and Zeff[v]) were measured and compared among the nonsmall cell lung cancer (NSCLC), SCLC and metastases, and other 3 groups of SCLC, squamous cell carcinoma, and adenocarcinoma. Results: Only the LCA is statistically different among SCLC, NSCLC, and metastases (P < .05). And the treated subgroup analysis did not show significant differences among the groups. However, the untreated subgroup analysis showed that there was a significant difference between NSCLC and metastases in LCA, SCLC and metastases in ICa, NSCLC and SCLC in HUv, NSCLC and SCLC in Zeff(v) (P < .05). Conclusion: The energy spectrum parameters of DLCT have a certain clinical value in distinguishing NSCLC from SCLC in the Zeff(v) and distinguishing SCLC from metastases in the ICa.
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spelling pubmed-88114312022-02-04 A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography Ma, Xia Xu, Ming Tian, Xiao-Juan Liu, Yong-Li Zhang, Xin-Ri Qiao, Ying Technol Cancer Res Treat Emerging Technologies and Cancer Object: By retrospectively analyzing the energy spectrum of squamous cell carcinoma, adenocarcinoma, small cell lung cancer (SCLC), and pulmonary metastases that underwent dual-layer detector spectral computed tomography (DLCT) 3-phase scan of the chest, we explored the value of a multiparameter energy spectrum in the assessment of pathological types of lung tumors. Methods: Cases of squamous cell carcinoma (n = 20), adenocarcinoma (n = 24), SCLC (n = 26), and metastases (n = 14) were collected. Then the largest cross-sectional area (LCA) of the lesion, computed tomography (CT) values in the plain scan phase, arterial and venous phases (HU, HUa, and HUv), iodine concentration, and effective atomic number in the arterial and venous phases (ICa, ICv, Zeff[a], and Zeff[v]) were measured and compared among the nonsmall cell lung cancer (NSCLC), SCLC and metastases, and other 3 groups of SCLC, squamous cell carcinoma, and adenocarcinoma. Results: Only the LCA is statistically different among SCLC, NSCLC, and metastases (P < .05). And the treated subgroup analysis did not show significant differences among the groups. However, the untreated subgroup analysis showed that there was a significant difference between NSCLC and metastases in LCA, SCLC and metastases in ICa, NSCLC and SCLC in HUv, NSCLC and SCLC in Zeff(v) (P < .05). Conclusion: The energy spectrum parameters of DLCT have a certain clinical value in distinguishing NSCLC from SCLC in the Zeff(v) and distinguishing SCLC from metastases in the ICa. SAGE Publications 2022-01-31 /pmc/articles/PMC8811431/ /pubmed/35099325 http://dx.doi.org/10.1177/15330338221074498 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Emerging Technologies and Cancer
Ma, Xia
Xu, Ming
Tian, Xiao-Juan
Liu, Yong-Li
Zhang, Xin-Ri
Qiao, Ying
A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography
title A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography
title_full A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography
title_fullStr A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography
title_full_unstemmed A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography
title_short A Retrospectively Study: Diagnosis of Pathological Types of Malignant Lung Tumors by Dual-layer Detector Spectral Computed Tomography
title_sort retrospectively study: diagnosis of pathological types of malignant lung tumors by dual-layer detector spectral computed tomography
topic Emerging Technologies and Cancer
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811431/
https://www.ncbi.nlm.nih.gov/pubmed/35099325
http://dx.doi.org/10.1177/15330338221074498
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