Meta-Analysis of Quantitative Dynamic Contrast-Enhanced MRI for the Assessment of Neoadjuvant Chemotherapy in Breast Cancer

2019 ◽  
Vol 85 (6) ◽  
pp. 645-653 ◽  
Author(s):  
Wei Jun ◽  
Wang Cong ◽  
Xie Xianxin ◽  
Jiang Daqing
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
High Sensitivity ◽  
Cochrane Library ◽  
Operating Characteristics ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

The purpose of this meta-analysis was to determine the value of quantitative dynamic contrast-enhanced (DCE) MRI (DCE-MRI) in evaluating the response of breast cancer to neoadjuvant chemotherapy (NAC). PubMed, Embase, and Cochrane Library databases (from building to July 31, 2018) were searched to collect articles about the therapeutic evaluation of NAC using the quantitative DCE-MRI in patients with breast cancer. The sensitivities and specificities of quantitative DCE-MRI in the evaluation of NAC for breast cancer were extracted from the articles. Meta-DiSc1.4 was applied to evaluate the efficacy of the sensitivity and specificity; forest figure and summary receiver operating characteristics (SROC) were created. A total of 356 articles were enrolled in this study, including 739 cases in total, in which 218 cases were effective and the other 521 cases were ineffective to NAC, considering the pathological results as the gold standard. The sensitivity and specificity in the included 14 articles of quantitative DCE-MRI ( Ktrans, kep, and ve) in comprehensively evaluating NAC for breast cancer were 84 per cent (95% confidence interval (CI): 78–88%) and 83 per cent (95% CI: 79–86%), respectively. The area under SROC was 0.899 (95% CI: 0.867–0.943). The sensitivity and specificity in the three articles of Ktrans evaluating NAC for breast cancer were 84.1 per cent (95% CI: 71.0–92.1%) and 81.3 per cent (95% CI: 70.5%-88.5%), respectively. The area under SROC was 0.899 (95% CI: 0.834–0.962). Our study confirmed that the quantitative DCE-MRI is able to monitor NAC treatment for breast cancer because of its high sensitivity and specificity. However, there is a high degree of heterogeneity in published studies, highlighting the lack of standardization in the field.

scholarly journals The diagnostic performance of CESM and CE-MRI in evaluating the pathological response to neoadjuvant therapy in breast cancer: a systematic review and meta-analysis

2020 ◽  
Vol 93 (1112) ◽  
pp. 20200301
Author(s):  
Sudan Tang ◽  
Chunhong Xiang ◽  
Quan Yang
Keyword(s):  
Breast Cancer ◽  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Treatment Strategies ◽  
Pathological Response ◽  
Cochrane Library ◽  
Excellent Performance ◽  
Contrast Enhanced ◽  
Sensitivity Specificity

Objectives: Neoadjuvant chemotherapy (NAC) is an important method for breast cancer treatment. By monitoring its pathological response, the selection of clinical treatment strategies can be guided. In this study, the meta-analysis was used to compare the accuracy of contrast-enhanced MRI (CE-MRI) and contrast-enhanced spectral mammography (CESM) in detecting the pathological response of NAC. Methods: Literatures associated to CE-MRI and CESM in the evaluation of pathological response of NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to assess the quality of studies. Pooled sensitivity, specificity, and the area under the SROC curve were calculated to evaluate the diagnostic accuracy of CE-MRI and CESM in monitoring the pathological response of NAC. Results: There were 24 studies involved, 18 of which only underwent CE-MRI examination, three of which only underwent CESM examination, and three of which underwent both CE-MRI and CESM examination. The pooled sensitivity and specificity of CE-MRI were 0.77 (95%CI, 0.67–0.84) and 0.82 (95%CI, 0.73–0.89), respectively. The pooled sensitivity and specificity of CESM were 0.83 (95%CI, 0.66–0.93) and 0.82 (95%CI, 0.68–0.91), respectively. The AUCs of SROC curve for CE-MRI and CESM were 0.86 and 0.89, respectively. Conclusions: Compared to CE-MRI, CESM has equal specificity, greater sensitivity and excellent performance, which may have a brighter prospect in evaluating the pathological response of breast cancer to NAC. Advances in knowledge: CESM showed equal specificity, greater sensitivity, and excellent performance than CE-MRI.

scholarly journals Accuracy of Various Forms of Contrast-Enhanced MRI for Diagnosing Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Chun Zhao ◽  
Hongyan Dai ◽  
Juwei Shao ◽  
Qian He ◽  
Wei Su ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
High Sensitivity ◽  
Cochrane Library ◽  
Significant Heterogeneity ◽  
Chi Square ◽  
Enhanced Mri ◽  
Contrast Enhanced ◽  
Contrast Enhanced Mri

BackgroundContrast-enhanced MRI can be used to identify patients with hepatocellular carcinoma (HCC). However, studies around the world have found differing diagnostic accuracies for the technique. Hence, we designed this meta-analysis to assess the accuracy of contrast-enhanced MRI for HCC diagnosis.MethodsWe conducted a systematic search for all studies reporting the diagnostic accuracy of contrast-enhanced MRI for HCC in the databases of MEDLINE, EMBASE, Cochrane Library, Web of Science, SCOPUS, ScienceDirect, and Google Scholar from inception until January 2021. We used the “Midas” package from the STATA software to perform the meta-analysis.ResultsOur study was based on 21 publications with 5,361 patients. The pooled HCC diagnosis sensitivity and specificity were 75% (95% CI, 70%–80%) and 90% (95% CI, 88%–92%), respectively, for gadoxetic acid-enhanced MRI; and they were 70% (95% CI, 57%–81%) and 94% (95% CI, 85%–97%), respectively, for MRI with extracellular contrast agents (ECA-MRI). We found significant heterogeneity with a significant chi-square test and an I2 statistic >75%. We also found significant publication bias as per Deeks’ test results and funnel plot.ConclusionWe found that both types of contrast-enhanced MRI are accurate diagnostic and surveillance tools for HCC and offer high sensitivity and specificity. Further studies on different ethnic populations are required to strengthen our findings.

scholarly journals Ultra-early changes in vascular parameters from dynamic contrast enhanced MRI of breast cancer xenografts following systemic therapy with doxorubicin and liver X receptor agonist

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Kathinka E. Pitman ◽  
Kine M. Bakke ◽  
Alexandr Kristian ◽  
Eirik Malinen
Keyword(s):  
Breast Cancer ◽  
Combination Therapy ◽  
Repeated Measures ◽  
Treatment Effects ◽  
Liver X Receptor ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Cytotoxic Treatment ◽  
Breast Cancer Xenografts

Abstract Background Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) may be used to depict tumour vascular structure and for therapy response assessment in various tumour sites. The purpose of the current work is to examine whether ultra-early changes in tumour physiology following cytotoxic treatment with doxorubicin and liver X receptor (LXR) agonist GW3965 are detectable by DCE-MRI. Methods 36 female, athymic nude foxn1nu mice with bilaterally implanted breast cancer xenografts (17 with ER-positive HBCx34, 19 with triple-negative HBCx39) were randomised in the following treatment groups; control, GW3965 (40 mg/kg p.o.), doxorubicin (8 mg/kg i.v.) and a combination therapy of GW3965 and doxorubicin. DCE-MRI (3D FLASH on a 7 T preclinical scanner) was performed at baseline and one and six days after onset of treatment. Wash-in (30 s p.i.) and wash-out (300 s p.i.) enhancement were quantified from dynamic uptake curves, before voxel-by-voxel fitting to the pharmacokinetic Tofts model and generation of maps for the resulting parameters Ktrans, νe and νB. Treatment effect was evaluated by univariate repeated measures mixed-effects maximum likelihood regression models applied to median tumour data. Results We found no effects of any treatment 24 h post treatment. After 6 days, doxorubicin given as both mono- and combination therapy gave significant increases of ~ 30% in wash-in enhancement (p < 0.011) and Ktrans (p < 0.017), and 40–50% in νB (p < 0.024) for HBCx34, but not for HBCx39. No effects of GW3965 were observed at any time (p > 0.1). Conclusions Twenty-four h after onset of treatment was too early to evaluate treatment effects by DCE-MRI. Early enhancement and Ktrans were approximately equally sensitive metrics to capture treatment effects six days pt. Pharmacokinetic modelling however allowed us to attribute the observed effect to changes in tumour perfusion rather than increased retention.

scholarly journals Pharmacokinetic parameters and radiomics model based on dynamic contrast enhanced MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Meijie Liu ◽  
Ning Mao ◽  
Heng Ma ◽  
Jianjun Dong ◽  
Kun Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Lymph Node ◽  
Regression Method ◽  
Pharmacokinetic Parameters ◽  
Combined Model ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Preoperative Prediction ◽  
Contrast Enhanced

Abstract Background To establish pharmacokinetic parameters and a radiomics model based on dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for predicting sentinel lymph node (SLN) metastasis in patients with breast cancer. Methods A total of 164 breast cancer patients confirmed by pathology were prospectively enrolled from December 2017 to May 2018, and underwent DCE-MRI before surgery. Pharmacokinetic parameters and radiomics features were derived from DCE-MRI data. Least absolute shrinkage and selection operator (LASSO) regression method was used to select features, which were then utilized to construct three classification models, namely, the pharmacokinetic parameters model, the radiomics model, and the combined model. These models were built through the logistic regression method by using 10-fold cross validation strategy and were evaluated on the basis of the receiver operating characteristics (ROC) curve. An independent validation dataset was used to confirm the discriminatory power of the models. Results Seven radiomics features were selected by LASSO logistic regression. The radiomics model, the pharmacokinetic parameters model, and the combined model yielded area under the curve (AUC) values of 0.81 (95% confidence interval [CI]: 0.72 to 0.89), 0.77 (95% CI: 0.68 to 0.86), and 0.80 (95% CI: 0.72 to 0.89), respectively, for the training cohort and 0.74 (95% CI: 0.59 to 0.89), 0.74 (95% CI: 0.59 to 0.90), and 0.76 (95% CI: 0.61 to 0.91), respectively, for the validation cohort. The combined model showed the best performance for the preoperative evaluation of SLN metastasis in breast cancer. Conclusions The model incorporating radiomics features and pharmacokinetic parameters can be conveniently used for the individualized preoperative prediction of SLN metastasis in patients with breast cancer.

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