Nomogram Based on Breast MRI and Clinicopathologic Features for Predicting Axillary Lymph Node Metastasis in Patients with Early-Stage Invasive Breast Cancer: A Retrospective Study

Meng, Xue; Che, Shunan; Tian, Yuan; Xie, Lizhi; Huang, Liling; Zhao, Liyun; Guo, Ning; Li, Jing

doi:10.1016/j.clbc.2021.10.014

Cited by 6 publications

(4 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…32 In our study, tumor size was not significantly associated with Ki67 discordance although tumor size has been shown to correlate with tumor aggression and recurrence. 33,34 Previous studies have been inconclusive about whether tumor size is associated with Ki67 discordance: one study linked larger tumors to greater risk of discordance, but another study failed to detect such an association. This disagreement in the literature may reflect patient enrollment bias and should be explored further.…”

Section: Discussionmentioning

confidence: 99%

Breast Magnetic Resonance Imaging Can Predict Ki67 Discordance Between Core Needle Biopsy and Surgical Samples

Wei

Tao

et al. 2022

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background: Disagreement in assessments of Ki67 expression based on core-needle biopsy and matched surgical samples complicates decisions in the treatment of breast cancer. Purpose: To examine whether preoperative breast MRI could be useful in predicting Ki67 discordance between core-needle biopsy and surgical samples. Study Type: Retrospective. Population: Three hundred and sixty-five breast cancer patients with MRI scans and having both core-needle biopsy and surgical samples from 2017 to 2019. Field Strength/Sequence: 3.0 T, T2-weighted iterative decomposition of water and fat with echo asymmetry and least squares estimation sequence, diffusion-weighted sequence using b-values 0/1000, dynamic contrast enhanced image by volume imaged breast assessme NT. Assessment: We collected clinicopathologic variables and preoperative MRI features (tumor size, lesion type, shape of mass, spiculated margin, internal enhancement, peri-tumoral edema, intra-tumoral necrosis, multifocal/multicentric, apparent diffusion coefficient [ADC] minimum, ADC mean, ADC maximum, ADC difference). Statistical Tests: K-means clustering, multivariable logistic regression, receiver operating characteristic curve. Results: Sixty-one patients showed Ki67 discordance and 304 patients show Ki67 concordance according to our definition using K-means clustering. Multivariable regression analysis showed that the following parameters were independently associated with Ki67 discordance: peri-tumoral edema, odds ratio (OR) 2.662, 95% confidence interval (CI) 1.432-4.948; ADCmin ≤ 0.829 Â 10 À3 mm 2 /sec, OR 2.180, 95% CI 1.075-4.418; and ADCdiff > 0.317 Â 10 À3 mm 2 /sec, OR 3.365, 95% CI 1.698-6.669. This multivariable model resulted in an AUC of 0.758 (95% CI 0.711-0.802) with sensitivity and specificity being 0.803 and 0.621, respectively. Conclusion: Presence of peri-tumoral edema, smaller ADCmin and greater ADCdiff in preoperative breast MRI may indicate high risk of Ki67 discordance between core-needle biopsy and surgical samples. For patients with these MRI-based risk factors, clinicians should not rely on Ki67 assessment only from core-needle biopsy.

show abstract

Section: Discussionmentioning

confidence: 99%

Breast Magnetic Resonance Imaging Can Predict Ki67 Discordance Between Core Needle Biopsy and Surgical Samples

Wei

Tao

et al. 2022

Magnetic Resonance Imaging

View full text Add to dashboard Cite

show abstract

“…Many ductal carcinomas in situ showed non-mass enhancement, which will continue to supplement the value of SyMRI in the differential diagnosis of benign and malignant non-mass-enhanced lesions. (3) This was a single-center study with a small sample size and a lower number of BI-RADS 4 benign tumors vs. malignant tumors, which may lead to potential statistical deviation, so it is necessary to expand the sample size for the multicenter study.…”

Section: A B D Cmentioning

confidence: 99%

“…Breast cancer is the most common malignant tumor affecting women worldwide and the main cause of cancer death among women (1,2). The cure rate of early breast cancer is more than 90%; however, once recurrence and metastasis occur, the survival time of patients is only 18-30 months (3). Early diagnosis and treatment of breast cancer can significantly prolong the survival time of patients and reduce the cost of treatment (4).…”

Section: Introductionmentioning

confidence: 99%

Multiparametric MRI model with synthetic MRI, DWI multi-quantitative parameters, and differential sub-sampling with cartesian ordering enables BI-RADS 4 lesions diagnosis with high accuracy

He,

Song,

Tian

et al. 2024

Front. Oncol.

View full text Add to dashboard Cite

ObjectiveTo assess the feasibility and diagnostic performances of synthetic magnetic resonance imaging (SyMRI) combined with diffusion-weighted imaging (DWI) and differential subsampling with cartesian ordering (DISCO) in breast imaging reporting and data system (BI-RADS) 4 lesions.MethodsA total of 98 BI-RADS 4 patients, including 68 cases assigned to a malignant group and 33 cases assigned to a benign group, were prospectively enrolled, and their MRI and clinical information were collected. Two physicians jointly analyzed the characteristics of conventional MRI. T1, T2, proton density (PD), and ADC values were obtained from three different regions of interest (ROIs). Logistic regression analyses were used to select features and build models, and a nomogram was constructed with the best model.ResultsUsing the ROI delineation method at the most obvious enhancement to measure the ADC value revealed the best diagnostic performance in diagnosing BI-RADS type 4 mass lesions. The diagnostic efficiency of the maximum level drawing method of the quantitative relaxation model was better than that of the whole drawing method and the most obvious enhancement method. The best relaxation model (model A) was composed of two parameters: T2stand and ΔT1%stand (AUC=0.887), and the BI-RADS model (model B) was constructed by two MRI features of edge and TIC curve (AUC=0.793). Using the quantitative parameters of SyMRI and DWI of the best ROC method combined with DISCO enhanced MRI features to establish a joint diagnostic model (model C: edge, TIC curve type, ADClocal, T2stand, ΔT1%stand) showed the best diagnostic efficiency (AUC=0.953). The nomogram also had calibration curves with good overlapConclusionsThe combined diagnosis model of SyMRI and DWI quantitative parameters combined with DISCO can improve the diagnostic efficiency of BI-RADS 4 types of mass lesions. Also, the line diagram based on this model can be used as an auxiliary diagnostic tool.

show abstract

“…Peritumoral radiomics can reflect the microenvironment closely related to tumor growth and invasion ( 13 ), while research exploring their relevance to ALN metastasis remains limited. Additionally, clinico-radiological characteristics of breast cancer have been shown to be correlated with ALN metastasis ( 14 , 15 ). This study aims to construct and validate preoperative predictive models for ALN metastasis based on both intra- and peritumoral DCE-MRI radiomics features and clinico-radiological characteristics in breast cancer.…”

Section: Introductionmentioning

confidence: 99%

Clinical study on the prediction of ALN metastasis based on intratumoral and peritumoral DCE-MRI radiomics and clinico-radiological characteristics in breast cancer

Wang,

Shang,

Guo

et al. 2024

Front. Oncol.

View full text Add to dashboard Cite

ObjectiveTo investigate the value of predicting axillary lymph node (ALN) metastasis based on intratumoral and peritumoral dynamic contrast-enhanced MRI (DCE-MRI) radiomics and clinico-radiological characteristics in breast cancer.MethodsA total of 473 breast cancer patients who underwent preoperative DCE-MRI from Jan 2017 to Dec 2020 were enrolled. These patients were randomly divided into training (n=378) and testing sets (n=95) at 8:2 ratio. Intratumoral regions (ITRs) of interest were manually delineated, and peritumoral regions of 3 mm (3 mmPTRs) were automatically obtained by morphologically dilating the ITR. Radiomics features were extracted, and ALN metastasis-related radiomics features were selected by the Mann-Whitney U test, Z score normalization, variance thresholding, K-best algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. Clinico-radiological risk factors were selected by logistic regression and were also used to construct predictive models combined with radiomics features. Then, 5 models were constructed, including ITR, 3 mmPTR, ITR+3 mmPTR, clinico-radiological and combined (ITR+3 mmPTR+ clinico-radiological) models. The performance of models was assessed by sensitivity, specificity, accuracy, F1 score and area under the curve (AUC) of receiver operating characteristic (ROC), calibration curves and decision curve analysis (DCA).ResultsA total of 2264 radiomics features were extracted from each region of interest (ROI), 3 and 10 radiomics features were selected for the ITR and 3 mmPTR, respectively. 5 clinico-radiological risk factors were selected, including lesion size, human epidermal growth factor receptor 2 (HER2) expression, vascular cancer thrombus status, MR-reported ALN status, and time-signal intensity curve (TIC) type. In the testing set, the combined model showed the highest AUC (0.839), specificity (74.2%), accuracy (75.8%) and F1 Score (69.3%) among the 5 models. DCA showed that it had the greatest net clinical benefit compared to the other models.ConclusionThe intra- and peritumoral radiomics models based on DCE-MRI could be used to predict ALN metastasis in breast cancer, especially for the combined model with clinico-radiological characteristics showing promising clinical application value.

show abstract

Nomogram Based on Breast MRI and Clinicopathologic Features for Predicting Axillary Lymph Node Metastasis in Patients with Early-Stage Invasive Breast Cancer: A Retrospective Study

Cited by 6 publications

References 40 publications

Breast Magnetic Resonance Imaging Can Predict Ki67 Discordance Between Core Needle Biopsy and Surgical Samples

Breast Magnetic Resonance Imaging Can Predict Ki67 Discordance Between Core Needle Biopsy and Surgical Samples

Multiparametric MRI model with synthetic MRI, DWI multi-quantitative parameters, and differential sub-sampling with cartesian ordering enables BI-RADS 4 lesions diagnosis with high accuracy

Clinical study on the prediction of ALN metastasis based on intratumoral and peritumoral DCE-MRI radiomics and clinico-radiological characteristics in breast cancer

Contact Info

Product

Resources

About