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Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer

BACKGROUND: The status of pelvic lymph node (PLN) metastasis affects treatment and prognosis plans in patients with cervical cancer. However, it is hard to be diagnosed in clinical practice. PURPOSE: The present study aimed to evaluate the diagnostic value of multimodal magnetic resonance imaging (M...

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Autores principales: Xu, Jian, Ma, Yingli, Mei, Haibing, Wang, Qimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326496/
https://www.ncbi.nlm.nih.gov/pubmed/35911622
http://dx.doi.org/10.2147/IJGM.S372154
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author Xu, Jian
Ma, Yingli
Mei, Haibing
Wang, Qimin
author_facet Xu, Jian
Ma, Yingli
Mei, Haibing
Wang, Qimin
author_sort Xu, Jian
collection PubMed
description BACKGROUND: The status of pelvic lymph node (PLN) metastasis affects treatment and prognosis plans in patients with cervical cancer. However, it is hard to be diagnosed in clinical practice. PURPOSE: The present study aimed to evaluate the diagnostic value of multimodal magnetic resonance imaging (MRI) in discriminating between metastatic and non-metastatic pelvic lymph nodes (PLNs) in cervical cancer. METHODS: This retrospective study analyzed MRIs of 209 PLNs in 25 women with pathologically proven cervical cancer. All PLNs had been assessed by pre-treatment multimodal MRIs, and their status was finally confirmed by histopathology. In conventional MRI, lymph node characteristics were compared between metastatic and non-metastatic PLNs. Signal intensity, time–intensity curve (TIC) patterns minimal and mean apparent diffusion coefficients (ADC) were compared between them in DWI. In DCE-MRI, quantitative (K(trans), K(ep) and V(e)) analyses were performed on DCE-MRI sequences, and their predictive values were analyzed by ROC curves. RESULTS: Of 209 PLNs, 22 (10.53%) were metastases and 187 (89.47%) were non-metastases at histopathologic examination. Considering a comparison of lymph node characteristics, the short axis size, the long axis size, and the boundary differed significantly between the two groups (P<0.05).The differences in ADC(min), TIC types, K(trans) and V(e) between metastatic and non-metastatic PLNs were significant as well (P<0.05). The good diagnostic performance of multimodal MRI was shown in discriminating between metastatic and non-metastatic PLNs, with the sensitivity of 85.0% (17/20), specificity of 97.3% (184/189), and accuracy of 96.2% (201/209). ROC analyses showed that the diagnostic accuracy of ADC(min), K(trans) and V(e) for discriminating between metastatic and non-metastatic PLNs in cervical cancer was 83.7%, 91.4%, and 92.4% with the cut-off values of 0.72 × 10(−3)mm(2)/s, 0.52 min(−1), and 0.53 min(−1), respectively. CONCLUSION: Multimodal MRI showed good diagnostic performance in determining PLN status in cervical cancer.
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spelling pubmed-93264962022-07-28 Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer Xu, Jian Ma, Yingli Mei, Haibing Wang, Qimin Int J Gen Med Original Research BACKGROUND: The status of pelvic lymph node (PLN) metastasis affects treatment and prognosis plans in patients with cervical cancer. However, it is hard to be diagnosed in clinical practice. PURPOSE: The present study aimed to evaluate the diagnostic value of multimodal magnetic resonance imaging (MRI) in discriminating between metastatic and non-metastatic pelvic lymph nodes (PLNs) in cervical cancer. METHODS: This retrospective study analyzed MRIs of 209 PLNs in 25 women with pathologically proven cervical cancer. All PLNs had been assessed by pre-treatment multimodal MRIs, and their status was finally confirmed by histopathology. In conventional MRI, lymph node characteristics were compared between metastatic and non-metastatic PLNs. Signal intensity, time–intensity curve (TIC) patterns minimal and mean apparent diffusion coefficients (ADC) were compared between them in DWI. In DCE-MRI, quantitative (K(trans), K(ep) and V(e)) analyses were performed on DCE-MRI sequences, and their predictive values were analyzed by ROC curves. RESULTS: Of 209 PLNs, 22 (10.53%) were metastases and 187 (89.47%) were non-metastases at histopathologic examination. Considering a comparison of lymph node characteristics, the short axis size, the long axis size, and the boundary differed significantly between the two groups (P<0.05).The differences in ADC(min), TIC types, K(trans) and V(e) between metastatic and non-metastatic PLNs were significant as well (P<0.05). The good diagnostic performance of multimodal MRI was shown in discriminating between metastatic and non-metastatic PLNs, with the sensitivity of 85.0% (17/20), specificity of 97.3% (184/189), and accuracy of 96.2% (201/209). ROC analyses showed that the diagnostic accuracy of ADC(min), K(trans) and V(e) for discriminating between metastatic and non-metastatic PLNs in cervical cancer was 83.7%, 91.4%, and 92.4% with the cut-off values of 0.72 × 10(−3)mm(2)/s, 0.52 min(−1), and 0.53 min(−1), respectively. CONCLUSION: Multimodal MRI showed good diagnostic performance in determining PLN status in cervical cancer. Dove 2022-07-22 /pmc/articles/PMC9326496/ /pubmed/35911622 http://dx.doi.org/10.2147/IJGM.S372154 Text en © 2022 Xu et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Xu, Jian
Ma, Yingli
Mei, Haibing
Wang, Qimin
Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer
title Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer
title_full Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer
title_fullStr Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer
title_full_unstemmed Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer
title_short Diagnostic Value of Multimodal Magnetic Resonance Imaging in Discriminating Between Metastatic and Non-Metastatic Pelvic Lymph Nodes in Cervical Cancer
title_sort diagnostic value of multimodal magnetic resonance imaging in discriminating between metastatic and non-metastatic pelvic lymph nodes in cervical cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326496/
https://www.ncbi.nlm.nih.gov/pubmed/35911622
http://dx.doi.org/10.2147/IJGM.S372154
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