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Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI
In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twen...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695736/ https://www.ncbi.nlm.nih.gov/pubmed/33247166 http://dx.doi.org/10.1038/s41598-020-77740-5 |
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author | Chen, Jenny Hagiwara, Mari Givi, Babak Schmidt, Brian Liu, Cheng Chen, Qi Logan, Jean Mikheev, Artem Rusinek, Henry Kim, Sungheon Gene |
author_facet | Chen, Jenny Hagiwara, Mari Givi, Babak Schmidt, Brian Liu, Cheng Chen, Qi Logan, Jean Mikheev, Artem Rusinek, Henry Kim, Sungheon Gene |
author_sort | Chen, Jenny |
collection | PubMed |
description | In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (v(e), v(p), PS, F(p), K(trans)), DWI (ADC) and PET (K(i), K(1), k(2), k(3)) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median v(p), F(p), PS, and K(trans) values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. v(e) and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k(3) (p value = 8.8 × 10(−8)) and K(i) (p value = 5.3 × 10(−8)) than normal nodes. K(1) and k(2) did not show any statistically significant difference. K(i) had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of K(i) = 5.3 × 10(−3) mL/cm(3)/min, while k(3) and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with K(i) < 5.3 × 10(−3) mL/cm(3)/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET. |
format | Online Article Text |
id | pubmed-7695736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76957362020-11-30 Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI Chen, Jenny Hagiwara, Mari Givi, Babak Schmidt, Brian Liu, Cheng Chen, Qi Logan, Jean Mikheev, Artem Rusinek, Henry Kim, Sungheon Gene Sci Rep Article In this study, we investigate the feasibility of using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), diffusion weighted imaging (DWI), and dynamic positron emission tomography (PET) for detection of metastatic lymph nodes in head and neck squamous cell carcinoma (HNSCC) cases. Twenty HNSCC patients scheduled for lymph node dissection underwent DCE-MRI, dynamic PET, and DWI using a PET-MR scanner within one week prior to their planned surgery. During surgery, resected nodes were labeled to identify their nodal levels and sent for routine clinical pathology evaluation. Quantitative parameters of metastatic and normal nodes were calculated from DCE-MRI (v(e), v(p), PS, F(p), K(trans)), DWI (ADC) and PET (K(i), K(1), k(2), k(3)) to assess if an individual or a combination of parameters can classify normal and metastatic lymph nodes accurately. There were 38 normal and 11 metastatic nodes covered by all three imaging methods and confirmed by pathology. 34% of all normal nodes had volumes greater than or equal to the smallest metastatic node while 4 normal nodes had SUV > 4.5. Among the MRI parameters, the median v(p), F(p), PS, and K(trans) values of the metastatic lymph nodes were significantly lower (p = <0.05) than those of normal nodes. v(e) and ADC did not show any statistical significance. For the dynamic PET parameters, the metastatic nodes had significantly higher k(3) (p value = 8.8 × 10(−8)) and K(i) (p value = 5.3 × 10(−8)) than normal nodes. K(1) and k(2) did not show any statistically significant difference. K(i) had the best separation with accuracy = 0.96 (sensitivity = 1, specificity = 0.95) using a cutoff of K(i) = 5.3 × 10(−3) mL/cm(3)/min, while k(3) and volume had accuracy of 0.94 (sensitivity = 0.82, specificity = 0.97) and 0.90 (sensitivity = 0.64, specificity = 0.97) respectively. 100% accuracy can be achieved using a multivariate logistic regression model of MRI parameters after thresholding the data with K(i) < 5.3 × 10(−3) mL/cm(3)/min. The results of this preliminary study suggest that quantitative MRI may provide additional value in distinguishing metastatic nodes, particularly among small nodes, when used together with FDG-PET. Nature Publishing Group UK 2020-11-27 /pmc/articles/PMC7695736/ /pubmed/33247166 http://dx.doi.org/10.1038/s41598-020-77740-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Jenny Hagiwara, Mari Givi, Babak Schmidt, Brian Liu, Cheng Chen, Qi Logan, Jean Mikheev, Artem Rusinek, Henry Kim, Sungheon Gene Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI |
title | Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI |
title_full | Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI |
title_fullStr | Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI |
title_full_unstemmed | Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI |
title_short | Assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)F-FDG-PET and MRI |
title_sort | assessment of metastatic lymph nodes in head and neck squamous cell carcinomas using simultaneous (18)f-fdg-pet and mri |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695736/ https://www.ncbi.nlm.nih.gov/pubmed/33247166 http://dx.doi.org/10.1038/s41598-020-77740-5 |
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