Radiomics Analysis of Multiparametric MRI Evaluates the Pathological Features of Cervical Squamous Cell Carcinoma

Wu, Qingxia; Shi, Dapeng; Dou, S. X.; Shi, Ligang; Liu, Mingbo; Dong, Li; Chang, Xiaowan; Wang, Meiyun

doi:10.1002/jmri.26301

Cited by 54 publications

(44 citation statements)

References 27 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…29 To date, it has already been shown that some MR parameters, including the tumor volume and the maximum diameter of the resectable CC on MRI, minimal ADC value, minimal ADC ratio, and the DCE parameters (K trans , V e ), may be used to predict LVSI. 2,30,31 In one study, the best distinguishing parameter was the minimal ADC ratio, with an AUC of 0.970; others ranged from 0.748 to 0.885. 2,30,31 In our study we found that the T 2 values could distinguish LVSI-positive and LVSI-negative CC, while the ADC values between the two groups did not show significant differences.…”

Section: Discussionmentioning

confidence: 99%

“…2,30,31 In one study, the best distinguishing parameter was the minimal ADC ratio, with an AUC of 0.970; others ranged from 0.748 to 0.885. 2,30,31 In our study we found that the T 2 values could distinguish LVSI-positive and LVSI-negative CC, while the ADC values between the two groups did not show significant differences. This may be due to tumor heterogeneity.…”

Section: Discussionmentioning

confidence: 99%

“…30 Radiomics analyses of T 2 W signal intensity has been shown to differentiate LVSI status. 31 However, the AUC of the ROC was relatively low, with a value of 0.710. Our study suggested that the T 2 value could be a potential tool to predict LVSI, although it does not seem possible to definitively ascertain or rule out the presence of LVSI using only the T 2 value.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study

Jie

Zhang

et al. 2020

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background: The application value of T 2 mapping in evaluating cervical cancer (CC) features remains unclear. Purpose: To investigate the role of T 2 values in evaluating CC classification, grade, and lymphovascular space invasion (LVSI) in comparison to apparent diffusion coefficient (ADC), and to compare synthetic T 2-weighted (T 2 W) images calculated from T 2 values to conventional T 2 W images for CC staging. Study Type: Retrospective. Population: Sixty-three patients with histopathologically confirmed CC. Field Strength/Sequence: 3T, conventional T 2 W turbo spin-echo, diffusion-weighted echo-planar, and accelerated T 2 mapping sequence. Assessment: T 2 and ADC values between different pathological features of CC were compared. The diagnostic accuracies of conventional and synthetic T 2 W images in staging were also compared. Statistical Tests: Parameters were compared using an independent t-test, Wilcoxon signed-rank test, and the chi-square test. Receiver operating characteristic analysis was performed. Results: The T 2 values varied significantly between well/moderately differentiated and poorly differentiated tumors ([92.8 AE 9.5 msec] vs. [83.8 AE 9.5 msec], P < 0.05) and between LVSI-positive and LVSI-negative CC ([82.2 AE 8.2 msec] vs. [93.9 AE 9.1 msec], P < 0.05). The ADC values showed a significant difference for grade ([0.76 AE 0.10 × 10 −3 mm 2 /s] vs. [0.65 AE 0.11 × 10 −3 mm 2 /s], P < 0.05) and no difference for LVSI status ([0.71 AE 0.11× 10 −3 mm 2 /s] vs. [0.73 AE 0.12× 10 −3 mm 2 /s], P = 0.472). There was no significant difference in T 2 and ADC values between squamous cell carcinoma and adenocarcinoma (P = 0.378 and P = 0.661, respectively). In MRI staging, the conventional and synthetic T 2 W images resulted in a similar accuracy (71% vs. 68%, P = 0.698). Data Conclusion: The accelerated T 2 mapping sequence may facilitate grading and staging of CC by providing quantitative T 2 maps and synthetic T 2 W images in one acquisition. T 2 values may be superior to ADC in predicting LVSI. Level of Evidence: 2 Technical Efficacy Stage: 2

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study

Jie

Zhang

et al. 2020

Magnetic Resonance Imaging

View full text Add to dashboard Cite

show abstract

“…T2 weighted imaging (T2WI) is a stable and essential sequence of cervical scanning according to the protocol for staging and evaluation of cervical cancer proposed by the European Society of Urogenital Radiology 2010 17 . Although radiomics analysis of cervical tissue has been widely performed on T2W images 6,[18][19][20] , its nonquantitative nature underlines the need for investigating the reproducibility of this sequence in a multi-center scenario. Thus, the purpose of the current study was to quantitatively identify the influence of different scanners and acquisition parameters on the robustness of T2WI radiomics features (RFs) based on females' cervix, which might have some implications for further radiomics studies on cervical lesions.…”

mentioning

confidence: 99%

Impact of different scanners and acquisition parameters on robustness of MR radiomics features based on women’s cervix

Yuan

Suo

et al. 2020

Sci Rep

View full text Add to dashboard Cite

MR Radiomics based on cervical lesions from one single scanner has achieved promising results. However, it is a challenge to achieve clinical translation. Considering multi-scanners and non-uniform scanning parameters from different centers in a real-world medical scenario, we should first identify the influence of such conditions on the robustness of MR radiomics features (RFs) based on the female cervix. In this study, 9 healthy female volunteers were enrolled and 3 kiwis were selected as references. Each of them underwent T2 weighted imaging in three different 3.0-T MR scanners with uniform acquisition parameters, and in one MR scanner with various scanning parameters. A total of 396 RFs were extracted from their images with and without decile intensity normalization. The RFs’ reproducibility was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). Representative features were selected using the hierarchical cluster analysis and their discrimination abilities were estimated by ROC analysis through retrospective comparison with the junctional zone and the outer muscular layer of healthy cervix in patients (n = 58) with leiomyoma. This study showed that only a few RFs were robust across different MR scanners and acquisition parameters based on females’ cervix, which might be improved by decile intensity normalization method.

show abstract

“…Previous studies have reported that tumor characteristics at the cellular and genetic levels can be re ected in the phenotypic patterns and subsequently captured by radiomics signatures [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Radiomic Analysis of Gd-EOB-DTPA-enhanced MRI Predicts Ki-67 Expression in Hepatocellular Carcinoma

Fan

Wang

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Nuclear protein Ki-67 indicates the status of cell proliferation and has been regarded as an attractive biomarker for the prognosis of HCC. The aim of this study is to investigate which radiomics model derived from different sequences and phases of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI was superior to predict Ki-67 expression in hepatocellular carcinoma (HCC), then further to validate the optimal model for preoperative prediction of Ki-67 expression in HCC. Methods: This retrospective study included 151 (training cohort: n=103; validation cohort: n=48) pathologically confirmed HCC patients. Radiomics features were extracted from the artery phase (AP), portal venous phase (PVP), hepatobiliary phase (HBP), and T2-weighted (T2W) images. A logistic regression with the least absolute shrinkage and selection operator (LASSO) regularization was used to select features to build a radiomics score (Rad-score). A final combined model including the optimal Rad-score and clinical risk factors was established. Receiver operating characteristic (ROC) curve analysis, Delong test and calibration curve were used to assess the predictive performance of the combined model. Decision cure analysis (DCA) was used to evaluate the clinical utility. Results: The AP radiomics model with higher decision curve indicating added more net benefit, gave a better predictive performance than the HBP and T2W radiomic models. The combined model (AUC = 0.922 vs 0.863) including AP Rad-score and serum AFP levels improved the predictive performance more than the AP radiomics model (AUC=0.873 vs 0.813) in the training and validation cohort. Calibration curve of the combined model showed a good agreement between the predicted and the actual probability. DCA of the validation cohort revealed that at a range threshold probability of 30-60%, the combined model added more net benefit compared with the AP radiomics model. Conclusions: A combined model including AP Rad-score and serum AFP levels based on enhanced MRI can preoperatively predict Ki-67 expression in HCC.

show abstract

Radiomics Analysis of Multiparametric MRI Evaluates the Pathological Features of Cervical Squamous Cell Carcinoma

Abstract: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Cited by 54 publications

References 27 publications

Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study

Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study

Impact of different scanners and acquisition parameters on robustness of MR radiomics features based on women’s cervix

Radiomic Analysis of Gd-EOB-DTPA-enhanced MRI Predicts Ki-67 Expression in Hepatocellular Carcinoma

Contact Info

Product

Resources

About

Radiomics Analysis of Multiparametric MRI Evaluates the Pathological Features of Cervical Squamous Cell Carcinoma

Abstract: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Cited by 54 publications

References 27 publications

Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study

Novel T2 Mapping for Evaluating Cervical Cancer Features by Providing Quantitative T2 Maps and Synthetic Morphologic Images: A Preliminary Study

Impact of different scanners and acquisition parameters on robustness of MR radiomics features based on women’s cervix

Radiomic Analysis of Gd-EOB-DTPA-enhanced MRI&nbsp;Predicts Ki-67 Expression in Hepatocellular Carcinoma

Contact Info

Product

Resources

About

Radiomic Analysis of Gd-EOB-DTPA-enhanced MRI Predicts Ki-67 Expression in Hepatocellular Carcinoma