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Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging

The aim of the study was to investigative the utility of gray-level co-occurrence matrix (GLCM) texture analysis based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for predicting the early response to chemoradiotherapy for nasopharyngeal carcinoma (NPC). Baseline IVIM-DWI wa...

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Autores principales: Qin, Yuhui, Yu, Xiaoping, Hou, Jing, Hu, Ying, Li, Feiping, Wen, Lu, Lu, Qiang, Fu, Yi, Liu, Siye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6078652/
https://www.ncbi.nlm.nih.gov/pubmed/30045324
http://dx.doi.org/10.1097/MD.0000000000011676
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author Qin, Yuhui
Yu, Xiaoping
Hou, Jing
Hu, Ying
Li, Feiping
Wen, Lu
Lu, Qiang
Fu, Yi
Liu, Siye
author_facet Qin, Yuhui
Yu, Xiaoping
Hou, Jing
Hu, Ying
Li, Feiping
Wen, Lu
Lu, Qiang
Fu, Yi
Liu, Siye
author_sort Qin, Yuhui
collection PubMed
description The aim of the study was to investigative the utility of gray-level co-occurrence matrix (GLCM) texture analysis based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for predicting the early response to chemoradiotherapy for nasopharyngeal carcinoma (NPC). Baseline IVIM-DWI was performed on 81 patients with NPC receiving chemoradiotherapy in a prospective nested case–control study. The patients were categorized into the residue (n = 11) and nonresidue (n = 70) groups, according to whether there was local residual lesion or not at the end of chemoradiotherapy. The pretreatment tumor volume and the values of IVIM-DWI parameters (apparent diffusion coefficient [ADC], D, D(∗), and f) and GLCM features based on IVIM-DWI were compared between the 2 groups. Receiver operating characteristic (ROC) curves in univariate and multivariate logistic regression analysis were generated to determine significant indicator of treatment response. The nonresidue group had lower tumor volume, ADC, D, Correlat(ADC), Correlat(D), InvDfMom(ADC), InvDfMom(D) and InvDfMom(D)(∗) values, together with higher Contrast(D), Contrast(f), SumAverg(ADC), SumAverg(D), and SumAverg(D)(∗) values, than the residue group (all P < .05). Based on ROC curve in univariate analysis, the area under the curve (AUC) values for individual GLCM features in the prediction of the treatment response ranged from 0.635 to 0.879, with sensitivities from 54.55% to 100.00% and specificities from 52.86% to 85.71%. Multivariate logistic regression analysis demonstrated D (P = .026), InvDfMom(ADC) (P = .033) and SumAverg(D) (P = .015) as the independent predictors for identifying NPC without residue, with an AUC value of 0.977, a sensitivity of 90.91% and a specificity of 95.71%. Pretreatment GLCM features based on IVIM-DWI, especially on the diffusion-related maps, may have the potential to predict the early response to chemoradiotherapy for NPC.
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spelling pubmed-60786522018-08-13 Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging Qin, Yuhui Yu, Xiaoping Hou, Jing Hu, Ying Li, Feiping Wen, Lu Lu, Qiang Fu, Yi Liu, Siye Medicine (Baltimore) Research Article The aim of the study was to investigative the utility of gray-level co-occurrence matrix (GLCM) texture analysis based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for predicting the early response to chemoradiotherapy for nasopharyngeal carcinoma (NPC). Baseline IVIM-DWI was performed on 81 patients with NPC receiving chemoradiotherapy in a prospective nested case–control study. The patients were categorized into the residue (n = 11) and nonresidue (n = 70) groups, according to whether there was local residual lesion or not at the end of chemoradiotherapy. The pretreatment tumor volume and the values of IVIM-DWI parameters (apparent diffusion coefficient [ADC], D, D(∗), and f) and GLCM features based on IVIM-DWI were compared between the 2 groups. Receiver operating characteristic (ROC) curves in univariate and multivariate logistic regression analysis were generated to determine significant indicator of treatment response. The nonresidue group had lower tumor volume, ADC, D, Correlat(ADC), Correlat(D), InvDfMom(ADC), InvDfMom(D) and InvDfMom(D)(∗) values, together with higher Contrast(D), Contrast(f), SumAverg(ADC), SumAverg(D), and SumAverg(D)(∗) values, than the residue group (all P < .05). Based on ROC curve in univariate analysis, the area under the curve (AUC) values for individual GLCM features in the prediction of the treatment response ranged from 0.635 to 0.879, with sensitivities from 54.55% to 100.00% and specificities from 52.86% to 85.71%. Multivariate logistic regression analysis demonstrated D (P = .026), InvDfMom(ADC) (P = .033) and SumAverg(D) (P = .015) as the independent predictors for identifying NPC without residue, with an AUC value of 0.977, a sensitivity of 90.91% and a specificity of 95.71%. Pretreatment GLCM features based on IVIM-DWI, especially on the diffusion-related maps, may have the potential to predict the early response to chemoradiotherapy for NPC. Wolters Kluwer Health 2018-07-27 /pmc/articles/PMC6078652/ /pubmed/30045324 http://dx.doi.org/10.1097/MD.0000000000011676 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0
spellingShingle Research Article
Qin, Yuhui
Yu, Xiaoping
Hou, Jing
Hu, Ying
Li, Feiping
Wen, Lu
Lu, Qiang
Fu, Yi
Liu, Siye
Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
title Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
title_full Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
title_fullStr Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
title_full_unstemmed Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
title_short Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
title_sort predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6078652/
https://www.ncbi.nlm.nih.gov/pubmed/30045324
http://dx.doi.org/10.1097/MD.0000000000011676
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