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Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging
BACKGROUND: This study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence). METH...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996088/ https://www.ncbi.nlm.nih.gov/pubmed/33777787 http://dx.doi.org/10.3389/fonc.2021.632796 |
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author | Song, Chengru Cheng, Peng Cheng, Jingliang Zhang, Yong Xie, Shanshan |
author_facet | Song, Chengru Cheng, Peng Cheng, Jingliang Zhang, Yong Xie, Shanshan |
author_sort | Song, Chengru |
collection | PubMed |
description | BACKGROUND: This study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence). METHODS: Thirty-eight patients with NPL and 62 patients with NPC, who received routine head-and-neck MRI and RESOLVE (b-value: 0 and 1,000 s/mm(2)) examinations, were retrospectively evaluated as derivation cohort (February 2015 to August 2018); another 23 patients were analyzed as validation cohort (September 2018 to December 2019). The RESOLVE data were obtained from the MAGNETOM Skyra 3T MR system (Siemens Healthcare, Erlangen, Germany). Fifteen parameters derived from the whole-lesion histogram analysis (ADC(mean), variance, skewness, kurtosis, ADC(1), ADC(10), ADC(20), ADC(30), ADC(40), ADC(50), ADC(60), ADC(70), ADC(80), ADC(90), and ADC(99)) were calculated for each patient. Then, statistical analyses were performed between the two groups to determine the statistical significance of each histogram parameter. A receiver operating characteristic curve (ROC) analysis was conducted to assess the diagnostic performance of each histogram parameter for distinguishing NPL from NPC and further tested in the validation cohort; calibration of the selected parameter was tested with Hosmer–Lemeshow test. RESULTS: NPL exhibited significantly lower ADC(mean), variance, ADC(1), ADC(10), ADC(20), ADC(30), ADC(40), ADC(50), ADC(60), ADC(70), ADC(80), ADC(90) and ADC(99), when compared to NPC (all, P < 0.05), while no significant differences were found on skewness and kurtosis. Furthermore, ADC(99) revealed the highest diagnostic efficiency, followed by ADC(10) and ADC(20). Optimal diagnostic performance (AUC = 0.790, sensitivity = 91.9%, and specificity = 63.2%) could be achieved when setting ADC(99) = 1,485.0 × 10(−6) mm(2)/s as the threshold value. The predictive performance was maintained in the validation cohort (AUC = 0.817, sensitivity = 94.6%, and specificity = 56.2%) CONCLUSION: Whole-lesion ADC histograms based on RESOLVE are effective in differentiating NPC from NPL. |
format | Online Article Text |
id | pubmed-7996088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79960882021-03-27 Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging Song, Chengru Cheng, Peng Cheng, Jingliang Zhang, Yong Xie, Shanshan Front Oncol Oncology BACKGROUND: This study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence). METHODS: Thirty-eight patients with NPL and 62 patients with NPC, who received routine head-and-neck MRI and RESOLVE (b-value: 0 and 1,000 s/mm(2)) examinations, were retrospectively evaluated as derivation cohort (February 2015 to August 2018); another 23 patients were analyzed as validation cohort (September 2018 to December 2019). The RESOLVE data were obtained from the MAGNETOM Skyra 3T MR system (Siemens Healthcare, Erlangen, Germany). Fifteen parameters derived from the whole-lesion histogram analysis (ADC(mean), variance, skewness, kurtosis, ADC(1), ADC(10), ADC(20), ADC(30), ADC(40), ADC(50), ADC(60), ADC(70), ADC(80), ADC(90), and ADC(99)) were calculated for each patient. Then, statistical analyses were performed between the two groups to determine the statistical significance of each histogram parameter. A receiver operating characteristic curve (ROC) analysis was conducted to assess the diagnostic performance of each histogram parameter for distinguishing NPL from NPC and further tested in the validation cohort; calibration of the selected parameter was tested with Hosmer–Lemeshow test. RESULTS: NPL exhibited significantly lower ADC(mean), variance, ADC(1), ADC(10), ADC(20), ADC(30), ADC(40), ADC(50), ADC(60), ADC(70), ADC(80), ADC(90) and ADC(99), when compared to NPC (all, P < 0.05), while no significant differences were found on skewness and kurtosis. Furthermore, ADC(99) revealed the highest diagnostic efficiency, followed by ADC(10) and ADC(20). Optimal diagnostic performance (AUC = 0.790, sensitivity = 91.9%, and specificity = 63.2%) could be achieved when setting ADC(99) = 1,485.0 × 10(−6) mm(2)/s as the threshold value. The predictive performance was maintained in the validation cohort (AUC = 0.817, sensitivity = 94.6%, and specificity = 56.2%) CONCLUSION: Whole-lesion ADC histograms based on RESOLVE are effective in differentiating NPC from NPL. Frontiers Media S.A. 2021-03-12 /pmc/articles/PMC7996088/ /pubmed/33777787 http://dx.doi.org/10.3389/fonc.2021.632796 Text en Copyright © 2021 Song, Cheng, Cheng, Zhang and Xie http://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 Song, Chengru Cheng, Peng Cheng, Jingliang Zhang, Yong Xie, Shanshan Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging |
title | Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging |
title_full | Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging |
title_fullStr | Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging |
title_full_unstemmed | Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging |
title_short | Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging |
title_sort | value of apparent diffusion coefficient histogram analysis in the differential diagnosis of nasopharyngeal lymphoma and nasopharyngeal carcinoma based on readout-segmented diffusion-weighted imaging |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996088/ https://www.ncbi.nlm.nih.gov/pubmed/33777787 http://dx.doi.org/10.3389/fonc.2021.632796 |
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