scholarly journals Radiomic analysis of Gd-EOB-DTPA-enhanced MRI predicts Ki-67 expression in hepatocellular carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yanfen Fan ◽  
Yixing Yu ◽  
Ximing Wang ◽  
Mengjie Hu ◽  
Chunhong Hu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Calibration Curve ◽  
Validation Cohort ◽  
Predictive Performance ◽  
Hepatobiliary Phase ◽  
Net Benefit ◽  
Combined Model ◽  
Ki 67 ◽  
Portal Venous Phase ◽  
Enhanced Mri

Abstract 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.

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

2020 ◽  
Author(s):  
Yanfen Fan ◽  
Yixing Yu ◽  
Ximing Wang ◽  
Mengjie Hu ◽  
Chunhong Hu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Calibration Curve ◽  
Validation Cohort ◽  
Predictive Performance ◽  
Hepatobiliary Phase ◽  
Net Benefit ◽  
Combined Model ◽  
Ki 67 ◽  
Portal Venous Phase ◽  
Enhanced Mri

Abstract 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.

scholarly journals A Nomogram for Preoperatively Predicting the Ki-67 Index of a Pituitary Tumor: A Retrospective Cohort Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiangming Cai ◽  
Junhao Zhu ◽  
Jin Yang ◽  
Chao Tang ◽  
Feng Yuan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Calibration Curve ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Treatment Strategies ◽  
Predictive Performance ◽  
Maximum Dimension ◽  
Ki 67 ◽  
Training Cohort ◽  
Index Level

BackgroundThe Ki-67 index is an indicator of proliferation and aggressive behavior in pituitary adenomas (PAs). This study aims to develop and validate a predictive nomogram for forecasting Ki-67 index levels preoperatively in PAs.MethodsA total of 439 patients with PAs underwent PA resection at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020; they were enrolled in this retrospective study and were classified randomly into a training cohort (n = 300) and a validation cohort (n = 139). A range of clinical, radiological, and laboratory characteristics were collected. The Ki-67 index was classified into the low Ki-67 index (<3%) and the high Ki-67 index (≥3%). Least absolute shrinkage and selection operator algorithm and uni- and multivariate logistic regression analyses were applied to identify independent risk factors associated with Ki-67. A nomogram was constructed to visualize these risk factors. The receiver operation characteristic curve and calibration curve were computed to evaluate the predictive performance of the nomogram model.ResultsAge, primary-recurrence subtype, maximum dimension, and prolactin were included in the nomogram model. The areas under the curve (AUCs) of the nomogram model were 0.694 in the training cohort and 0.658 in the validation cohort. A well-fitted calibration curve was also generated for the nomogram model. A subgroup analysis revealed stable predictive performance for the nomogram model. A correlation analysis revealed that age (R = −0.23; p < 0.01), maximum dimension (R = 0.17; p < 0.01), and prolactin (R = 0.16; p < 0.01) were all significantly correlated with the Ki-67 index level.ConclusionsAge, primary-recurrence subtype, maximum dimension, and prolactin are independent predictors for the Ki-67 index level. The current study provides a novel and feasible nomogram, which can further assist neurosurgeons to develop better, more individualized treatment strategies for patients with PAs by predicting the Ki-67 index level preoperatively.

scholarly journals A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongdong Zhou ◽  
Xiaoli Liu ◽  
Xinhui Wang ◽  
Fengna Yan ◽  
Peng Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Surgical Therapy ◽  
Calibration Curve ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Alpha Fetoprotein ◽  
Clinicopathologic Characteristics

Abstract Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

scholarly journals Prediction of Microvascular Invasion in Hepatocellular Carcinoma: Preoperative Gd-EOB-DTPA-Dynamic Enhanced MRI and Histopathological Correlation

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Mengqi Huang ◽  
Bing Liao ◽  
Ping Xu ◽  
Huasong Cai ◽  
Kun Huang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prediction Model ◽  
Tumor Size ◽  
Univariate Analysis ◽  
Microvascular Invasion ◽  
Arterial Phase ◽  
Hepatobiliary Phase ◽  
Imaging Features ◽  
Tumor Margin ◽  
Enhanced Mri

Objective. To investigate the imaging features observed in preoperative Gd-EOB-DTPA-dynamic enhanced MRI and correlated with the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. Methods. 66 HCCs in 60 patients with preoperative Gd-EOB-DTPA-dynamic enhanced MRI were retrospectively analyzed. Features including tumor size, signal homogeneity, tumor capsule, tumor margin, peritumor enhancement during mid-arterial phase, peritumor hypointensity during hepatobiliary phase, signal intensity ratio on DWI and apparent diffusion coefficients (ADC), T1 relaxation times, and the reduction rate between pre- and postcontrast enhancement images were assessed. Correlation between these features and histopathological presence of MVI was analyzed to establish a prediction model. Results. Histopathology confirmed that MVI were observed in 17 of 66 HCCs. Univariate analysis showed tumor size (p=0.003), margin (p=0.013), peritumor enhancement (p=0.001), and hypointensity during hepatobiliary phase (p=0.004) were associated with MVI. A multiple logistic regression model was established, which showed tumor size, margin, and peritumor enhancement were combined predictors for the presence of MVI (α=0.1). R2 of this prediction model was 0.353, and the sensitivity and specificity were 52.9% and 93.0%, respectively. Conclusion. Large tumor size, irregular tumor margin, and peritumor enhancement in preoperative Gd-EOB-DTPA-dynamic enhanced MRI can predict the presence of MVI in HCC.

scholarly journals Higher Enhancement Intrahepatic Nodules on the Hepatobiliary Phase of Gd-EOB-DTPA-Enhanced MRI as a Poor Responsive Marker of Anti-PD-1/PD-L1 Monotherapy for Unresectable Hepatocellular Carcinoma

Liver Cancer ◽  
2021 ◽  
pp. 1-14
Author(s):  
Tomoko Aoki ◽  
Naoshi Nishida ◽  
Kazuomi Ueshima ◽  
Masahiro Morita ◽  
Hirokazu Chishina ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Checkpoint Inhibitors ◽  
Objective Response ◽  
Evaluation Criteria ◽  
Progression Free Survival ◽  
Imaging Biomarker ◽  
Hepatobiliary Phase ◽  
Enhanced Mri ◽  
Phase Images ◽  
Magnetic Resonance Imaging Mri

<b><i>Introduction:</i></b> Immune checkpoint inhibitors (ICIs) are promising agents for the treatment of hepatocellular carcinoma (HCC). However, the establishment of noninvasive measure that could predict the response to ICIs is challenging. This study aimed to evaluate tumor responses to ICIs using the hepatobiliary phase of gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI), which was shown to reflect Wnt/β-catenin activating mutation. <b><i>Methods:</i></b> A total of 68 intrahepatic HCC nodules from 18 patients with unresectable HCC and Child-Pugh class A liver function who received anti-programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1) monotherapy were enrolled in this study. All patients had viable intrahepatic lesions evaluable using the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI within the 6 months prior to the treatment. The relative enhancement ratio was calculated, and the time to nodular progression (TTnP) defined as 20% or more increase in each nodule was compared between higher or hypo-enhancement HCC nodules. Then, the progression-free survival (PFS) and objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1) were compared between patients with and without HCC nodules with higher enhancement on hepatobiliary phase images. <b><i>Results:</i></b> The median PFS was 2.7 (95% confidence interval [CI]: 1.4–4.0) months in patients with HCC nodules with higher enhancement (<i>n</i> = 8) and 5.8 (95% CI: 0.0–18.9) months in patients with hypointense HCC nodules (<i>n</i> = 10) (<i>p</i> = 0.007). The median TTnP of HCC nodules with higher enhancement (<i>n</i> = 23) was 1.97 (95% CI: 1.86–2.07) months and that of hypointense HCC nodules (<i>n</i> = 45) was not reached (<i>p</i> = 0.003). The ORR was 12.5% (1/8) versus 30.0% (3/10); the disease control rate was 37.5% (3/8) versus 70.0% (7/10), respectively, in patients with or without higher enhancement intrahepatic HCC nodules. <b><i>Conclusion:</i></b> The TTnP on HCC nodules with higher enhancement and the median PFS in patients who carried higher enhancement intrahepatic HCC nodules were significantly shorter than those in hypointense HCC nodules with anti-PD-1/PD-L1 monotherapy. The intensity of the nodule on the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI is a promising imaging biomarker for predicting unfavorable response with anti-PD-1/PD-L1 monotherapy in patients with HCC.

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