Are ADC values of readout-segmented echo-planar diffusion-weighted imaging (RESOLVE) correlated with pathological prognostic factors in rectal adenocarcinoma?

Tang, Cui; Lin, Moubin; Jin-lei, XU; Zhang, Lan-hua; Zuo, Xiaoming; Zhang, Zhongshuai; Liu, Meng-xiao

doi:10.1186/s12957-018-1445-z

Cited by 15 publications

(19 citation statements)

References 26 publications

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“…The results of the quantitative and qualitative analysis indicate that the image quality of RESOLVE DWI is better than that of SS-EPI DWI. The technique of RESOLVE DWI has proven to provide better detection and image quality in rectal, prostate, kidney, neck, and breast compared with SS-EPI DWI [ 15 , 16 , 18 , 35 , 36 ]. Our study also supports this conclusion.…”

Section: Discussionmentioning

confidence: 99%

High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma

et al. 2020

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Background We assessed the image quality of endometrial cancer lesions by readout segmentation of long variable echo-trains (RESOLVE) diffusion-weighted imaging (DWI) compared with that by single-shot echo-planar imaging (SS-EPI) DWI, aimed to explore the value of RESOLVE DWI for determining myometrial invasion and clinical stage in endometrial cancer. Materials and methods From April 2017 to March 2018, a total of 30 endometrial cancer patients (mean age 52.8 ± 9.0 years), who had undergone RESOLVE DWI and SS-EPI DWI, were included in the study. The image quality of endometrial carcinoma by two kinds of DWI scanning methods was compared qualitatively and quantitatively. The Spearman rank correlation test was used to assess the correlation of qualitative image quality scores between two readers. The accuracy of two DWI methods in detecting myometrial invasion and staging of endometrial carcinoma was calculated according to postoperative pathological results. The indexes were analyzed including sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). Results The qualitative score of RESOLVE DWI group was superior to SS-EPI DWI group in every aspect of five aspects (all P < 0.001). Interobserver agreement of depiction was good or excellent in two DWI sequences. Signal to noise ratio and contrast to noise ratio values in RESOLVE DWI group were both higher than those in SS-EPI DWI group (P<0.001). No statistical difference of apparent diffusion coefficient value was observed between two DWI groups (P = 0.261). The specificity, accuracy, PPV, and NPV of estimating myometrial invasion by RESOLVE DWI in three cases (intramucosal lesion, <50% superficial invasion and ≥ 50% deep invasion) were all higher than those by SS-EPI DWI for endometrial carcinoma. Especially RESOLVE DWI was valuable in judging <50% superficial invasion (95%CI:0.586, 0.970). No significant difference in accuracy staging was between the two DWI groups (P = 0.125). Conclusion RESOLVE DWI can provide higher quality images of endometrial carcinoma than SS-EPI DWI. The high-quality images are helpful for precise assessment of myometrial invasion in endometrial cancer.

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Section: Discussionmentioning

confidence: 99%

High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma

et al. 2020

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“…Previous studies have shown by NCCN, degree of differentiation, T stage, and N stage are powerful prognostic factors for patients with rectal cancer [3]. Several studies showed a statistically significant correlation between the apparent diffusion coefficient value, derived from diffusion-weighted images, and tumor differentiation grade [16, 17]; however, some studies showed a contradictory result [18, 19]. In this study, radiomics and tumor differentiation grade showed a statistically significant correlation.…”

Section: Discussionmentioning

confidence: 99%

MRI-based radiomics of rectal cancer: preoperative assessment of the pathological features

Jia³

et al. 2019

BMC Med Imaging

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BackgroundThis study aimed to evaluate the significance of MRI-based radiomics model derived from high-resolution T2-weighted images (T2WIs) in predicting tumor pathological features of rectal cancer.MethodsA total of 152 patients with rectal cancer who underwent surgery without any neoadjuvant therapy between March 2017 and September 2018 were included retrospectively. The patients were scanned using a 3-T magnetic resonance imaging, and high-resolution T2WIs were obtained. Lesions were delineated, and 1029 radiomics features were extracted. Least absolute shrinkage and selection operator was used to select features, and multilayer perceptron (MLP), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) were trained using fivefold cross-validation to build a prediction model. The diagnostic performance of the prediction models was assessed using the receiver operating characteristic curves.ResultsA total of 1029 features were extracted, and 15, 11, and 11 features were selected to predict the degree of differentiation, T stage, and N stage, respectively. The best performance of the radiomics model for the degree of differentiation, T stage, and N stage was obtained by SVM [area under the curve (AUC), 0.862; 95% confidence interval (CI), 0.750–0.967; sensitivity, 83.3%; specificity, 85.0%], MLP (AUC, 0.809; 95% CI, 0.690–0.905; sensitivity, 76.2%; specificity, 74.1%), and RF (AUC, 0.746; 95% CI, 0.622-0.872; sensitivity, 79.3%; specificity, 72.2%).ConclusionThis study demonstrated that the high-resolution T2WI–based radiomics model could serve as pretreatment biomarkers in predicting pathological features of rectal cancer.

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“…Previous studies have shown by NCCN, degree of differentiation, T stage, and N stage are powerful prognostic factors for patients with rectal cancer [3]. Several studies showed a statistically significant correlation between the apparent diffusion coefficient value, derived from diffusion-weighted images, and tumor differentiation grade [16,17]; however, some studies showed a contradictory result [18,19]. In this study, radiomics and tumor differentiation grade showed a statistically significant correlation.…”

Section: Discussionmentioning

confidence: 42%

MRI-based Radiomics of Rectal Cancer: Preoperative Assessment of the Pathological Features

Shen

Jia³

et al. 2019

Preprint

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[EXSCINDED] Abstract Background This study aimed to evaluate the significance of MRI-based radiomics model derived from high-resolution T2-weighted images (T2WIs) in predicting tumor pathological features of rectal cancer.Methods A total of 152 patients with rectal cancer who underwent surgery without any neoadjuvant therapy between March 2017 and September 2018 were included retrospectively. The patients were scanned using a 3-tesla magnetic resonance imaging, and high-resolution T2WIs were obtained. Lesions were delineated, and 1029 radiomics features were extracted. Least absolute shrinkage and selection operator was used to select features, and multilayer perceptron (MLP), logistic regression, support vector machine (SVM), decision tree, random forest (RF), and K-nearest neighbor were trained using fivefold cross-validation to build a prediction model. The diagnostic performance of the prediction models was assessed using the receiver operating characteristic curves.Results A total of 1029 features were extracted, and 15, 11, and 11 features were selected to predict the degree of differentiation, T stage, and N stage, respectively. The best performance of the radiomics model for the degree of differentiation, T stage, and N stage was obtained by SVM [area under the curve (AUC), 0.862; 95% confidence interval (CI), 0.750–0.967; sensitivity, 83.3%; specificity, 85.0%], MLP (AUC, 0.809; 95% CI, 0.690–0.905; sensitivity, 76.2%; specificity, 74.1%), and RF (AUC, 0.809; 95% CI, 0.690–0.905; sensitivity, 76.2%; specificity, 74.1%).Conclusion This study demonstrated that the high-resolution T2WI–based radiomics model could serve as pretreatment biomarkers in predicting pathological features of rectal cancer.

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Are ADC values of readout-segmented echo-planar diffusion-weighted imaging (RESOLVE) correlated with pathological prognostic factors in rectal adenocarcinoma?

Cited by 15 publications

References 26 publications

High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma

High resolution diffusion-weighted imaging with readout segmentation of long variable echo-trains for determining myometrial invasion in endometrial carcinoma

MRI-based radiomics of rectal cancer: preoperative assessment of the pathological features

MRI-based Radiomics of Rectal Cancer: Preoperative Assessment of the Pathological Features

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