Dataset Information

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

ABSTRACT: To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT).36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm2) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers.With a mean follow-up of 25 months (range, 11 ? 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADCmean, 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ? 0.038).Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

SUBMITTER: Meng J

PROVIDER: S-EPMC5696195 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

Meng Jie J Zhu Lijing L Zhu Li L Xie Li L Wang Huanhuan H Liu Song S Yan Jing J Liu Baorui B Guan Yue Y He Jian J Ge Yun Y Zhou Zhengyang Z Yang Xiaofeng X

Oncotarget 20170928 54

<h4>Purpose</h4>To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT).<h4>Methods</h4>36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm<sup>2</sup>) were performed before CCRT (pre-CCRT) an ...[more]

PMID: 29190929

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Project description:ObjectivesTo investigate the value of whole-tumor texture analysis of apparent diffusion coefficient (ADC) map in predicting the early recurrence of patients with locally advanced cervical squamous cell cancer (LACSC) treated with concurrent chemoradiotherapy (CCRT) and establish a combined prediction model including clinical variables and first-order texture features.MethodsIn total, 219 patients (training: n = 153; testing: n = 66) with stage IIB-IVA LACSC treated by CCRT between January 2014 and December 2019 were retrospectively enrolled in this study. Clinical variables and 22 first-order texture features extracted from ADC map were collected. The Mann-Whitney U test or independent sample t test, chi-square test or Fisher's exact were used to analyze statistically significant parameters, logistic regression analysis was used for multivariate analysis, and receiver operating characteristic analysis was used to compare the diagnostic performance.ResultsIn the clinical variables, T stage and lymph node metastasis (LNM) were independent risk factors, and the areas under the curve (AUCs) of the clinical model were 0.697 and 0.667 in the training and testing cohorts, the sensitivity and specificity were 48.8% and 85.5% in the training cohort, and 84.1% and 51.1% in the testing cohort, respectively. In the first-order texture features, mean absolute deviation (MAD) was the independent protective factor, with an AUC of 0.756 in the training cohort and 0.783 in the testing cohort. The sensitivity and specificity were 95.3% and 52.7% in the training cohort and 94.7% and 53.2% in the testing cohort, respectively. The combined model (MAD, T stage, and LNM) was established, it exhibited the highest AUC of 0.804 in the training cohort and 0.821 in the testing cohort, which was significantly higher than the AUC of the clinical prediction model. The sensitivity and specificity were 67.4% and 85.5% in the training cohort and 94.7% and 70.2% in the testing cohort, respectively.ConclusionsThe first-order texture features of the ADC map could be used along with clinical predictive biomarkers to predict early recurrence in patients with LACSC treated by CCRT.

Project description:ObjectivesTo assess whole-liver texture analysis on T1 maps for risk stratification of advanced fibrosis in patients with suspected nonalcoholic fatty liver disease (NAFLD).MethodsThis retrospective study included 53 patients. Histogram and texture parameters (volume, mean, SD, median, 5th percentile, 95th percentile, skewness, kurtosis, diff-entropy, diff-variance, contrast, and entropy) of T1 maps were calculated based on the semi-automatically segmented whole-liver volume. A two-step approach combining the Nonalcoholic Fatty Liver Disease Fibrosis Score (NFS) and Fibrosis-4 Index (FIB-4) with the liver stiffness measurement (LSM) for the risk stratification was used. Univariate analysis was performed to identify significant parameters. Logistic regression models were then run on the significant features. Diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis.ResultsIn total, 33 (62%) subjects had a low risk and 20 (38%) subjects had an intermediate-to-high risk of advanced fibrosis. The following significantly different parameters with the best performance were diff-entropy, entropy, and diff-variance, with AUROC 0.837 (95% CI 0.73-0.95), 0.821 (95% CI 0.71-0.94), and 0.807 (95% CI 0.69-0.93). The optimal combination of median, 5th percentile, and diff-entropy as a multivariate model improved the diagnostic performance to diagnose an intermediate-to-high risk of advanced fibrosis with AUROC 0.902(95% CI 0.79-0.97).ConclusionsParameters obtained by histogram and texture analysis of T1 maps may be a noninvasive analytical approach for stratifying the risk of advanced fibrosis in NAFLD.Key points• Variable flip angle (VFA) T1 mapping can be used to acquire 3D T1 maps within a clinically acceptable duration. • Whole-liver histogram and texture parameters on T1 maps in patients with NAFLD can distinguish those with an intermediate-to-high risk of advanced fibrosis. • The multivariate model of combination of texture parameters improved the diagnostic performance for a high risk of advanced fibrosis and clinical parameters offer no added value to the multivariate model.

Dataset Information

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

Publications

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

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