The Diagnostic Performance of DCE-MRI in Evaluating the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis

Cheng, Qingqing; Huang, Jiaxi; Liang, Jianye; Ma, Mengjie; Ye, Kunlin; Shi, Changzheng; Luo, Lixia

doi:10.3389/fonc.2020.00093

Cited by 48 publications

(40 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Meta-analysis showed that 18 F-FDG PET/CT had a moderate accuracy for the early prediction for pCR (sensitivity 85%, specificity 79% and diagnostic odds ratio 21.8), especially in HER2 positive and triple negative breast cancer 16 , 17 . DCE-MRI was also an effective method for early monitoring the efficacy during NAT (sensitivity 87%, specificity 82% and diagnostic odds ratio 30.3) 18 . However, both 18 F-FDG PET/CT and DCE-MRI require sophisticated imaging, additional radiation dose for patients, and less accessible compared with ultrasound.…”

Section: Discussionmentioning

confidence: 99%

Early response and pathological complete remission in Breast Cancer with different molecular subtypes: a retrospective single center analysis

Jiang¹,

Wu²,

Huang³

et al. 2020

J. Cancer

View full text Add to dashboard Cite

Purpose: To evaluate the association of clinical early response and pathological complete remission (pCR) in breast cancer patients with different molecular subtypes. Materials and methods: Breast cancer patients who received neoadjuvant treatment (NAT) with clinical early response assessment from October 2008 to October 2018 were retrospectively analyzed. Clinical early response was defined as tumor size decreasing ≥30% evaluated by ultrasound after two cycles of NAT. Chi-square test was used to compare the pCR rates between the responder and non-responder groups with different molecular subtypes. Multivariate logistic regression was used to identify independent factors associated with the pCR. Results: A total of 328 patients were included: 100 responders and 228 non-responders. The progesterone receptor (PR) expression was an independent factor associated with clinical early response (OR=2.39, 95%CI=1.41-4.05, P =0.001). The pCR rate of breast was 50.0% for responders and 18.0% for non-responders ( P <0.001). Regarding different molecular subtypes, responders had higher pCR rates than non-responders for patients with HER2 overexpression (OR=10.66, 95%CI=2.18-52.15, P =0.001), triple negative (OR=3.29, 95%CI=1.23-8.84, P =0.016) and Luminal (HER2-) subtypes (OR=8.58, 95%CI=3.05-24.10, P <0.001) respectively. Moreover, pCR rate can be achieved as high as 88.2% in HER2 overexpression patients with early clinical response, which was significantly higher than patients without early response (41.3%, P =0.001). Multivariate analysis showed that clinical early response was an independent factor associated with the pCR rate (OR=4.87, 95%CI=2.72-8.72, P <0.001). Conclusions: Early response was significantly associated with a higher pCR rate in breast cancer patients receiving NAT, especially for patients with HER2 overexpression subtype, which warrants further clinical evaluation.

show abstract

Section: Discussionmentioning

confidence: 99%

Early response and pathological complete remission in Breast Cancer with different molecular subtypes: a retrospective single center analysis

Jiang¹,

Wu²,

Huang³

et al. 2020

J. Cancer

View full text Add to dashboard Cite

show abstract

“…The quality of studies and the likelihood of bias were evaluated using Review Manager 5.3 software (Cochrane Collaboration, Oxford, UK), based on the Quality Assessment of Diagnostic Accuracy Studies-2 ( 18 ). We assessed the risk of bias and applicability concerns in four domains, including patient selection, index tests, reference standard, and flow, and timing ( 19 ).…”

Section: Methodsmentioning

confidence: 99%

Intravoxel Incoherent Motion Diffusion-Weighted Imaging Used to Detect Prostate Cancer and Stratify Tumor Grade: A Meta-Analysis

Xie³

et al. 2020

Front. Oncol.

Self Cite

View full text Add to dashboard Cite

Objectives: Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is a promising non-invasive imaging technique to detect and grade prostate cancer (PCa). However, the results regarding the diagnostic performance of IVIM-DWI in the characterization and classification of PCa have been inconsistent among published studies. This meta-analysis was performed to summarize the diagnostic performance of IVIM-DWI in the differential diagnosis of PCa from non-cancerous tissues and to stratify the tumor Gleason grades in PCa. Materials and Methods: Studies concerning the differential diagnosis of prostate lesions using IVIM-DWI were systemically searched in PubMed, Embase, and Web of Science without time limitation. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals of the apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D * ), and perfusion fraction (f). Stata 12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC), as well as publication bias and heterogeneity. Fagan's nomogram was used to predict the post-test probabilities. Results: Twenty studies with 854 patients confirmed with PCa were included. Most of the included studies showed a low to unclear risk of bias and low concerns regarding applicability. PCa showed a significantly lower ADC (SMD = −2.34; P < 0.001) and D values (SMD = −1.86; P < 0.001) and a higher D * value (SMD = 0.29; P = 0.01) than non-cancerous tissues, but no difference was noted with the f value (SMD = −0.16; P = 0.50). Low-grade PCa showed higher ADC (SMD = 0.63; P < 0.001) and D values (SMD = 0.80; P < 0.001) than the high-grade lesions. ADC showed comparable diagnostic performance (sensitivity = 86%; specificity = 86%; AUC = 0.87) but higher post-test probabilities (60, 53, 36, and 36% for ADC, D, D * , and f values, respectively) compared with the D (sensitivity = 82%; specificity = 82%; AUC = 0.85), D * (sensitivity = 70%; specificity = 70%; AUC = 0.75), and f values (sensitivity = 73%; specificity = 68%; AUC = 0.76). Conclusion: IVIM parameters are adequate to differentiate PCa from non-cancerous tissues with good diagnostic performance but are not superior to the ADC value. Diffusion coefficients can further stratify the tumor Gleason grades in PCa.

show abstract

“…The quality of studies and likelihood of bias were evaluated using Review Manager 5.3 software (Cochrane Collaboration, Oxford, UK), referring to the Quality Assessment of Diagnostic Accuracy Studies-2 (28). We assessed the risk of bias and applicability in four domains, including patient selection, index tests, reference standard, flow, and timing (29).…”

Section: Quality Assessmentmentioning

confidence: 99%

The Diagnostic Performance of Diffusion Kurtosis Imaging in the Characterization of Breast Tumors: A Meta-Analysis

Peng

et al. 2020

Front. Oncol.

Self Cite

View full text Add to dashboard Cite

Rationale and Objectives: Diffusion kurtosis imaging (DKI) is a promising imaging technique, but the results regarding the diagnostic performance of DKI in the characterization and classification of breast tumors are inconsistent among published studies. This study aimed to pool all published results to provide more robust evidence of the differential diagnosis between malignant and benign breast tumors using DKI. Methods: Studies on the differential diagnosis of breast tumors using DKI-derived parameters were systemically retrieved from PubMed, Embase, and Web of Science without a time limit. Review Manager 5.3 was used to calculate the standardized mean differences (SMDs) and 95% confidence intervals of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC). Stata 12.0 was used to pool the sensitivity, specificity, and diagnostic odds ratio (DOR) as well as the publication bias and heterogeneity of each parameter. Fagan's nomograms were plotted to predict the post-test probabilities. Results: Thirteen studies including 867 malignant and 460 benign breast lesions were analyzed. Most of the included studies showed a low to unclear risk of bias and low concerns regarding applicability. Breast cancer showed a higher MK (SMD = 1.23, P < 0.001) but a lower MD (SMD = −1.29, P < 0.001) and ADC (SMD = −1.21, P < 0.001) than benign tumors. The MK (SMD = −1.36, P = 0.006) rather than the MD (SMD = 0.29, P = 0.20) or ADC (SMD = 0.26, P = 0.24) can further differentiate invasive ductal carcinoma from ductal carcinoma in situ. The DKI-derived MK (sensitivity = 90%, specificity = 88%, DOR = 66) and MD (sensitivity = 86% and specificity = 88%, DOR = 46) demonstrated superior diagnostic performance and post-test probability (65, 64, and 56% for MK, MD, and ADC) in differentiating malignant from benign breast lesions, with a higher sensitivity and specificity than the DWI-derived ADC (sensitivity = 85% and specificity = 83%, DOR = 29). Li et al. Characterizing Breast Tumor With DKI Conclusion: The DKI-derived MK and MD demonstrate a comparable diagnostic performance in the discrimination of breast tumors based on their microstructures and non-Gaussian characteristics. The MK can further differentiate invasive ductal carcinoma from ductal carcinoma in situ.

show abstract

The Diagnostic Performance of DCE-MRI in Evaluating the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis

Cited by 48 publications

References 36 publications

Early response and pathological complete remission in Breast Cancer with different molecular subtypes: a retrospective single center analysis

Early response and pathological complete remission in Breast Cancer with different molecular subtypes: a retrospective single center analysis

Intravoxel Incoherent Motion Diffusion-Weighted Imaging Used to Detect Prostate Cancer and Stratify Tumor Grade: A Meta-Analysis

The Diagnostic Performance of Diffusion Kurtosis Imaging in the Characterization of Breast Tumors: A Meta-Analysis

Contact Info

Product

Resources

About