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Li MG, Luo SB, Hu YY, Li L, Lyu HL. Role of the Clinical Features and MRI Parameters on Ki-67 Expression in Hepatocellular Carcinoma Patients: Development of a Predictive Nomogram. J Gastrointest Cancer 2024:10.1007/s12029-024-01051-5. [PMID: 38592430 DOI: 10.1007/s12029-024-01051-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2024] [Indexed: 04/10/2024]
Abstract
PURPOSE To develop a nomogram using clinical features and the MRI parameters for preoperatively predicting the expression of Ki-67 in patients with hepatocellular carcinoma (HCC). METHODS One hundred and forty patients (training cohorts: n = 108; validation cohorts: n = 32) with confirmed HCC were investigated. Mann-Whitney U test, independent sample t-test, and chi-squared test were used to analyze the continuous and categorical variables. Univariate and multivariate logistic regression analyses were performed to examine the clinical variables and parameters from MRI associated with Ki-67 expression. As a result, a nomogram was developed based on these associations in patients with HCC. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves. RESULTS In the training set, multivariable logistic regression analysis revealed that lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3) levels, protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels, and tumor shape were independent predictors for Ki-67 expression (p < 0.05). These three variables and the apparent diffusion coefficient (ADC) value were used to establish a nomogram, while the ADC value was found to be a marginal significant predictor. The model demonstrated a strong ability to discriminate Ki-67 expression in both the training and validation cohorts (AUC = 0.862, 0.877). CONCLUSION A non-invasive preoperative prediction method, which incorporates MRI variables and clinical features was developed, and showed effectiveness in evaluating Ki-67 expression in HCC patients.
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Affiliation(s)
- Ming-Ge Li
- Department of Radiology, Tianjin Third Central Hospital, Tianjin, China
| | - Shu-Bin Luo
- Department of Radiology, Shengli Oilfield Central Hospital, No. 31 Jinan Road, Dongying District, Dongying, 257034, Shandong Province, China
| | - Ying-Ying Hu
- Department of Pathology, Shengli Oilfield Central Hospital, Dongying, Shandong Province, China
| | - Lei Li
- Department of Radiology, Shengli Oilfield Central Hospital, No. 31 Jinan Road, Dongying District, Dongying, 257034, Shandong Province, China
| | - Hai-Lian Lyu
- Department of Radiology, Shengli Oilfield Central Hospital, No. 31 Jinan Road, Dongying District, Dongying, 257034, Shandong Province, China.
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Liang Y, Xu F, Mou Q, Wang Z, Xiao C, Zhou T, Zhang N, Yang J, Wu H. A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma. BMC Med Imaging 2024; 24:27. [PMID: 38273242 PMCID: PMC10811868 DOI: 10.1186/s12880-024-01204-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/17/2024] [Indexed: 01/27/2024] Open
Abstract
PURPOSE To construct a gadoxetic acid-enhanced MRI (EOB-MRI) -based multivariable model to predict Ki-67 expression levels in hepatocellular carcinoma (HCC) using LI-RADS v2018 imaging features. METHODS A total of 121 patients with HCC who underwent EOB-MRI were enrolled in this study. The patients were divided into three groups according to Ki-67 cut-offs: Ki-67 ≥ 20% (n = 86) vs. Ki-67 < 20% (n = 35); Ki-67 ≥ 30% (n = 73) vs. Ki-67 < 30% (n = 48); Ki-67 ≥ 50% (n = 45) vs. Ki-67 < 50% (n = 76). MRI features were analyzed to be associated with high Ki-67 expression using logistic regression to construct multivariable models. The performance characteristic of the models for the prediction of high Ki-67 expression was assessed using receiver operating characteristic curves. RESULTS The presence of mosaic architecture (p = 0.045), the presence of infiltrative appearance (p = 0.039), and the absence of targetoid hepatobiliary phase (HBP, p = 0.035) were independent differential factors for the prediction of high Ki-67 status (≥ 50% vs. < 50%) in HCC patients, while no features could predict high Ki-67 status with thresholds of 20% (≥ 20% vs. < 20%) and 30% (≥ 30% vs. < 30%) (p > 0.05). Four models were constructed including model A (mosaic architecture and infiltrated appearance), model B (mosaic architecture and targetoid HBP), model C (infiltrated appearance and targetoid HBP), and model D (mosaic architecture, infiltrated appearance and targetoid HBP). The model D yielded better diagnostic performance than the model C (0.776 vs. 0.669, p = 0.002), but a comparable AUC than model A (0.776 vs. 0.781, p = 0.855) and model B (0.776 vs. 0.746, p = 0.076). CONCLUSIONS Mosaic architecture, infiltrated appearance and targetoid HBP were sensitive imaging features for predicting Ki-67 index ≥ 50% and EOB-MRI model based on LI-RADS v2018 features may be an effective imaging approach for the risk stratification of patients with HCC before surgery.
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Affiliation(s)
- Yingying Liang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Fan Xu
- Department of Radiology, Guangzhou Red Cross Hospital, Medical College, Jinan University, 396 Tongfu Road, Guangzhou, Guangdong Province, 510220, China
| | - Qiuju Mou
- Department of Pathology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Zihua Wang
- Department of Radiology, Foshan Hospital of Traditional Chinese Medicine, Foshan, Guangdong Province, 528000, China
| | - Chuyin Xiao
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Tingwen Zhou
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Nianru Zhang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Jing Yang
- Department of Pathology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China.
| | - Hongzhen Wu
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China.
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Zhou L, Chen Y, Li Y, Wu C, Xue C, Wang X. Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis. Front Oncol 2024; 13:1323534. [PMID: 38234405 PMCID: PMC10792117 DOI: 10.3389/fonc.2023.1323534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Background Radiomics have been increasingly used in the clinical management of hepatocellular carcinoma (HCC), such as markers prediction. Ki-67 and cytokeratin 19 (CK-19) are important prognostic markers of HCC. Radiomics has been introduced by many researchers in the prediction of these markers expression, but its diagnostic value remains controversial. Therefore, this review aims to assess the diagnostic value of radiomics in predicting Ki-67 and CK-19 expression in HCC. Methods Original studies were systematically searched in PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2023. All included studies were evaluated by the radiomics quality score. The C-index was used as the effect size of the performance of radiomics in predicting Ki-67and CK-19 expression, and the positive cutoff values of Ki-67 label index (LI) were determined by subgroup analysis and meta-regression. Results We identified 34 eligible studies for Ki-67 (18 studies) and CK-19 (16 studies). The most common radiomics source was magnetic resonance imaging (MRI; 25/34). The pooled C-index of MRI-based models in predicting Ki-67 was 0.89 (95% CI:0.86-0.92) in the training set, and 0.87 (95% CI: 0.82-0.92) in the validation set. The pooled C-index of MRI-based models in predicting CK-19 was 0.86 (95% CI:0.81-0.90) in the training set, and 0.79 (95% CI: 0.73-0.84) in the validation set. Subgroup analysis suggested Ki-67 LI cutoff was a significant source of heterogeneity (I 2 = 0.0% P>0.05), and meta-regression showed that the C-index increased as Ki-67 LI increased. Conclusion Radiomics shows promising diagnostic value in predicting positive Ki-67 or CK-19 expression. But lacks standardized guidelines, which makes the model and variables selection dependent on researcher experience, leading to study heterogeneity. Therefore, standardized guidelines are warranted for future research. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023427953.
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Affiliation(s)
- Lu Zhou
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yiheng Chen
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yan Li
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Chaoyong Wu
- Shenzhen Hospital of Beijing University of Chinese Medicine, Shenzhen, China
| | - Chongxiang Xue
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xihong Wang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, China
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Li J, Kou P, Lin L, Xiao Y, Jin H, Zhang Y, Cheng J. T1 mapping in evaluation of clinicopathologic factors for rectal adenocarcinoma. Abdom Radiol (NY) 2024; 49:279-287. [PMID: 37839066 DOI: 10.1007/s00261-023-04045-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/31/2023] [Accepted: 09/03/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE T1 mapping has been increasingly applied in the study of tumor. The purpose of this study was to evaluate the value of T1 mapping in evaluating clinicopathologic factors for rectal adenocarcinoma. MATERIALS AND METHODS Eighty-six patients with rectal adenocarcinoma confirmed by surgical pathology who underwent preoperative pelvic MRI were retrospectively analyzed. High-resolution T2-weighted imaging (T2WI), T1 mapping, and diffusion-weighted imaging (DWI) were performed. T1 and apparent diffusion coefficient (ADC) parameters were compared among different associated tumor markers, tumor grades, stages, and structure invasion statuses. A receiver operating characteristic (ROC) analysis was estimated. RESULTS T1 value showed significant difference between high- and low-grade tumors ([1531.5 ± 84.7 ms] vs. [1437.1 ± 80.3 ms], P < 0.001). T1 value was significant higher in positive than in negative perineural invasion ([1495.7 ± 89.2 ms] vs. [1449.4 ± 88.8 ms], P < 0.05). No significant difference of T1 or ADC was observed in different CEA, CA199, T stage, N stage, lymphovascular invasions, extramural vascular invasion (EMVI), and circumferential resection margin (CRM) (P > 0.05). The AUC under ROC curve of T1 value were 0.796 in distinguishing high- from low-grade rectal adenocarcinoma. The AUC of T1 value in distinguishing perineural invasion was 0.637. CONCLUSION T1 value was helpful in assessing pathologic grade and perineural invasion correlated with rectal cancer.
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Affiliation(s)
- Juan Li
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.
| | - Peisi Kou
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Liangjie Lin
- Advanced Technical Support, Philips Healthcare, Beijing, China
| | - Yunfei Xiao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Hongrui Jin
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China
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Qian H, Shen Z, Zhou D, Huang Y. Intratumoral and peritumoral radiomics model based on abdominal ultrasound for predicting Ki-67 expression in patients with hepatocellular cancer. Front Oncol 2023; 13:1209111. [PMID: 37711208 PMCID: PMC10498123 DOI: 10.3389/fonc.2023.1209111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/09/2023] [Indexed: 09/16/2023] Open
Abstract
Background Hepatocellular cancer (HCC) is one of the most common tumors worldwide, and Ki-67 is highly important in the assessment of HCC. Our study aimed to evaluate the value of ultrasound radiomics based on intratumoral and peritumoral tissues in predicting Ki-67 expression levels in patients with HCC. Methods We conducted a retrospective analysis of ultrasonic and clinical data from 118 patients diagnosed with HCC through histopathological examination of surgical specimens in our hospital between September 2019 and January 2023. Radiomics features were extracted from ultrasound images of both intratumoral and peritumoral regions. To select the optimal features, we utilized the t-test and the least absolute shrinkage and selection operator (LASSO). We compared the area under the curve (AUC) values to determine the most effective modeling method. Subsequently, we developed four models: the intratumoral model, the peritumoral model, combined model #1, and combined model #2. Results Of the 118 patients, 64 were confirmed to have high Ki-67 expression while 54 were confirmed to have low Ki-67 expression. The AUC of the intratumoral model was 0.796 (0.649-0.942), and the AUC of the peritumoral model was 0.772 (0.619-0.926). Furthermore, combined model#1 yielded an AUC of 0.870 (0.751-0.989), and the AUC of combined model#2 was 0.762 (0.605-0.918). Among these models, combined model#1 showed the best performance in terms of AUC, accuracy, F1-score, and decision curve analysis (DCA). Conclusion We presented an ultrasound radiomics model that utilizes both intratumoral and peritumoral tissue information to accurately predict Ki-67 expression in HCC patients. We believe that incorporating both regions in a proper manner can enhance the diagnostic performance of the prediction model. Nevertheless, it is not sufficient to include both regions in the region of interest (ROI) without careful consideration.
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Affiliation(s)
- Hongwei Qian
- Department of Hepatobiliary and Pancreatic Surgery, Shaoxing People’s Hospital, Shaoxing, China
- Shaoxing Key Laboratory of Minimally Invasive Abdominal Surgery and Precise Treatment of Tumor, Shaoxing, China
| | - Zhihong Shen
- Department of Hepatobiliary and Pancreatic Surgery, Shaoxing People’s Hospital, Shaoxing, China
- Shaoxing Key Laboratory of Minimally Invasive Abdominal Surgery and Precise Treatment of Tumor, Shaoxing, China
| | - Difan Zhou
- Department of Hepatobiliary and Pancreatic Surgery, Shaoxing People’s Hospital, Shaoxing, China
- Shaoxing Key Laboratory of Minimally Invasive Abdominal Surgery and Precise Treatment of Tumor, Shaoxing, China
| | - Yanhua Huang
- Department of Ultrasound, Shaoxing People’s Hospital, Shaoxing, China
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Qiu G, Chen J, Liao W, Liu Y, Wen Z, Zhao Y. Gadoxetic acid-enhanced MRI combined with T1 mapping and clinical factors to predict Ki-67 expression of hepatocellular carcinoma. Front Oncol 2023; 13:1134646. [PMID: 37456233 PMCID: PMC10348748 DOI: 10.3389/fonc.2023.1134646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 06/19/2023] [Indexed: 07/18/2023] Open
Abstract
Objectives To explore the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) combined with T1 mapping and clinical factors for Ki-67 expression in hepatocellular carcinoma (HCC). Methods A retrospective study was conducted on 185 patients with pathologically confirmed solitary HCC from two institutions. All patients underwent preoperative T1 mapping on gadoxetic acid-enhanced MRI. Patients from institution I (n = 124) and institution II (n = 61) were respectively assigned to the training and validation sets. Univariable and multivariable analyses were performed to assess the correlation of clinico-radiological factors with Ki-67 labeling index (LI). Based on the significant factors, a predictive nomogram was developed and validated for Ki-67 LI. The performance of the nomogram was evaluated on the basis of its calibration, discrimination, and clinical utility. Results Multivariable analysis showed that alpha-fetoprotein (AFP) levels > 20ng/mL, neutrophils to lymphocyte ratio > 2.25, non-smooth margin, tumor-to-liver signal intensity ratio in the hepatobiliary phase ≤ 0.6, and post-contrast T1 relaxation time > 705 msec were the independent predictors of Ki-67 LI. The nomogram based on these variables showed the best predictive performance with area under the receiver operator characteristic curve (AUROC) 0.899, area under the precision-recall curve (AUPRC) 0.946 and F1 score of 0.912; the respective values were 0.823, 0.879 and 0.857 in the validation set. The Kaplan-Meier curves illustrated that the cumulative recurrence probability at 2 years was significantly higher in patients with high Ki-67 LI than in those with low Ki-67 LI (39.6% [53/134] vs. 19.6% [10/51], p = 0.011). Conclusions Gadoxetic acid-enhanced MRI combined with T1 mapping and several clinical factors can preoperatively predict Ki-67 LI with high accuracy, and thus enable risk stratification and personalized treatment of HCC patients.
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Affiliation(s)
- Ganbin Qiu
- Imaging Department of Zhaoqing Medical College, Zhaoqing, China
- Department of Radiology, The First People’s Hospital of Zhaoqing, Zhaoqing, China
| | - Jincan Chen
- Department of Radiology, The First People’s Hospital of Zhaoqing, Zhaoqing, China
| | - Weixiong Liao
- Imaging Department of Zhaoqing Medical College, Zhaoqing, China
| | - Yonghui Liu
- Department of Radiology, The First People’s Hospital of Zhaoqing, Zhaoqing, China
| | - Zhongyan Wen
- Department of Radiology, The First People’s Hospital of Zhaoqing, Zhaoqing, China
| | - Yue Zhao
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
- Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, China
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