Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging. Issue 30 (July 2018)

• Record Type: Journal Article
• Authors: Qin, Yuhui; Yu, Xiaoping; Hou, Jing; Hu, Ying; Li, Feiping; Wen, Lu; Lu, Qiang; Fu, Yi; Liu, Siye
• Other Names: Yu. Cheng-Chia section editor.
• Is Part Of: Medicine. Volume 97:Issue 30(2018)
• Publication Date: 2018-07
• Subjects: chemoradiotherapy -- diffusion magnetic resonance imaging -- nasopharyngeal neoplasms -- radiographic image interpretation -- treatment outcome; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000011676
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: 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, CorrelatADC, Correlat D, InvDfMomADC, InvDfMom D and InvDfMom D * values, together with higher Contrast D, Contrast f, SumAvergADC, 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), InvDfMomADC ( P = .033) and SumAvergD ( 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.