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Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study
OBJECTIVES: The current study evaluates the performance of dual-energy computed tomography (DECT) derived extracellular volume (ECV) fraction based on dual-layer spectral detector CT for diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid cancer (PTC) and compares it with the val...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213667/ https://www.ncbi.nlm.nih.gov/pubmed/35756662 http://dx.doi.org/10.3389/fonc.2022.851244 |
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author | Zhou, Yan Geng, Di Su, Guo-Yi Chen, Xing-Biao Si, Yan Shen, Mei-Ping Xu, Xiao-Quan Wu, Fei-Yun |
author_facet | Zhou, Yan Geng, Di Su, Guo-Yi Chen, Xing-Biao Si, Yan Shen, Mei-Ping Xu, Xiao-Quan Wu, Fei-Yun |
author_sort | Zhou, Yan |
collection | PubMed |
description | OBJECTIVES: The current study evaluates the performance of dual-energy computed tomography (DECT) derived extracellular volume (ECV) fraction based on dual-layer spectral detector CT for diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid cancer (PTC) and compares it with the value of ECV derived from conventional single-energy CT (SECT). METHODS: One hundred and fifty-seven cervical LNs (81 non-metastatic and 76 metastatic) were recruited. Among them, 59 cervical LNs (27 non-metastatic and 32 metastatic) were affected by cervical root artifact on the contrast-enhanced CT images in the arterial phase. Both the SECT-derived ECV fraction (ECV(S)) and the DECT-derived ECV fraction (ECV(D)) were calculated. A Pearson correlation coefficient and a Bland–Altman analysis were performed to evaluate the correlations between ECV(D) and ECV(S). Receiver operator characteristic curves analysis and the Delong method were performed to assess and compare the diagnostic performance. RESULTS: ECV(D) correlated significantly with ECV(S) (r = 0.925; p <0.001) with a small bias (−0.6). Metastatic LNs showed significantly higher ECV(D) (42.41% vs 22.53%, p <0.001) and ECV(S) (39.18% vs 25.45%, p <0.001) than non-metastatic LNs. By setting an ECV(D) of 36.45% as the cut-off value, optimal diagnostic performance could be achieved (AUC = 0.813), which was comparable with that of ECV(S) (cut-off value = 34.99%; AUC = 0.793) (p = 0.265). For LNs affected by cervical root artifact, ECV(D) also showed favorable efficiency (AUC = 0.756), which was also comparable with that of ECV(S) (AUC = 0.716) (p = 0.244). CONCLUSIONS: ECV(D) showed a significant correlation with ECV(S). Compared with ECV(S), ECV(D) showed comparable performance in diagnosing metastatic cervical LNs in PTC patients, even though the LNs were affected by cervical root artifacts on arterial phase CT. |
format | Online Article Text |
id | pubmed-9213667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92136672022-06-23 Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study Zhou, Yan Geng, Di Su, Guo-Yi Chen, Xing-Biao Si, Yan Shen, Mei-Ping Xu, Xiao-Quan Wu, Fei-Yun Front Oncol Oncology OBJECTIVES: The current study evaluates the performance of dual-energy computed tomography (DECT) derived extracellular volume (ECV) fraction based on dual-layer spectral detector CT for diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid cancer (PTC) and compares it with the value of ECV derived from conventional single-energy CT (SECT). METHODS: One hundred and fifty-seven cervical LNs (81 non-metastatic and 76 metastatic) were recruited. Among them, 59 cervical LNs (27 non-metastatic and 32 metastatic) were affected by cervical root artifact on the contrast-enhanced CT images in the arterial phase. Both the SECT-derived ECV fraction (ECV(S)) and the DECT-derived ECV fraction (ECV(D)) were calculated. A Pearson correlation coefficient and a Bland–Altman analysis were performed to evaluate the correlations between ECV(D) and ECV(S). Receiver operator characteristic curves analysis and the Delong method were performed to assess and compare the diagnostic performance. RESULTS: ECV(D) correlated significantly with ECV(S) (r = 0.925; p <0.001) with a small bias (−0.6). Metastatic LNs showed significantly higher ECV(D) (42.41% vs 22.53%, p <0.001) and ECV(S) (39.18% vs 25.45%, p <0.001) than non-metastatic LNs. By setting an ECV(D) of 36.45% as the cut-off value, optimal diagnostic performance could be achieved (AUC = 0.813), which was comparable with that of ECV(S) (cut-off value = 34.99%; AUC = 0.793) (p = 0.265). For LNs affected by cervical root artifact, ECV(D) also showed favorable efficiency (AUC = 0.756), which was also comparable with that of ECV(S) (AUC = 0.716) (p = 0.244). CONCLUSIONS: ECV(D) showed a significant correlation with ECV(S). Compared with ECV(S), ECV(D) showed comparable performance in diagnosing metastatic cervical LNs in PTC patients, even though the LNs were affected by cervical root artifacts on arterial phase CT. Frontiers Media S.A. 2022-06-08 /pmc/articles/PMC9213667/ /pubmed/35756662 http://dx.doi.org/10.3389/fonc.2022.851244 Text en Copyright © 2022 Zhou, Geng, Su, Chen, Si, Shen, Xu and Wu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhou, Yan Geng, Di Su, Guo-Yi Chen, Xing-Biao Si, Yan Shen, Mei-Ping Xu, Xiao-Quan Wu, Fei-Yun Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study |
title | Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study |
title_full | Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study |
title_fullStr | Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study |
title_full_unstemmed | Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study |
title_short | Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study |
title_sort | extracellular volume fraction derived from dual-layer spectral detector computed tomography for diagnosing cervical lymph nodes metastasis in patients with papillary thyroid cancer: a preliminary study |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213667/ https://www.ncbi.nlm.nih.gov/pubmed/35756662 http://dx.doi.org/10.3389/fonc.2022.851244 |
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