Prognostic importance of ultrasound BI-RADS classification in breast cancer patients

Observational analysis of clinical and pathological characteristics and their prognostic impact in Mexican patients with breast cancer: A multi-center study

Breast cancer is the most incidental and deadly neoplasm worldwide; in Mexico, very few epidemiologic reports have analyzed the pathological features and its impact on their clinical outcome. Here, we studied the relation between pathological features and the clinical presentation at diagnosis and their impact on the overall and progression-free survival of patients with breast cancer. For this purpose, we collected 199 clinical records of female patients, aged at least 18 years old (y/o), with breast cancer diagnosis confirmed by biopsy. We excluded patients with incomplete or conflicting clinical records. Afterward, we performed an analysis of overall and progression-free survival and associated risks. Our results showed an average age at diagnosis of 52 y/o (24-85), the most common features were: upper outer quadrant tumor (32%), invasive ductal carcinoma (76.8%), moderately differentiated (44.3%), early clinical stages (40.8%), asymptomatic patients (47.8%), luminal A subtype (47.8%). Median overall survival was not reached, but median progression-free survival was 32.2 months (29.75-34.64, CI 95%) associated risk were: clinical stage (p < 0.0001) symptomatic presentation (p = 0.009) and histologic grade (p = 0.02). Therefore, we concluded that symptom presence at diagnosis impacts progression-free survival, and palpable symptoms are related to an increased risk for mortality.

Gail model and fifth edition of ultrasound BI-RADS help predict axillary lymph node metastasis in breast cancer-A multicenter prospective study

RATIONALE AND OBJECTIVES

We aim to assess the performance of the Gail model and the fifth edition of ultrasound BI-RADS (Breast Imaging Reporting and Data System) in breast cancer for predicting axillary lymph node metastasis (ALNM).

MATERIALS AND METHODS

We prospectively studied 958 female patients with breast cancer between 2018 and 2019 from 35 hospitals in China. Based on B-mode, color Doppler, and elastography, radiologists classified the degree of suspicion based on the fifth edition of BI-RADS. Individual breast cancer risk was assessed with the Gail model. The association between the US BI-RADS category and the Gail model in terms of ALNM was analyzed.

RESULTS

We found that US BI-RADS category was significantly and independently associated with ALNM (P < 0.001). The sensitivity, specificity, and accuracy of BI-RADS category 5 for predicting ALNM were 63.6%, 71.6%, and 68.6%, respectively. Combining the Gail model with the BI-RADS category showed a significantly higher sensitivity than using the BI-RADS category alone (67.8% vs. 63.6%, P < 0.001). The diagnostic accuracy of the BI-RADS category combined with the Gail model was better than that of the Gail model alone (area under the curve: 0.71 vs. 0.50, P < 0.001).

CONCLUSION

Based on the conventional ultrasound and elastography, the fifth edition of ultrasound BI-RADS category could be used to predict the ALNM of breast cancer. ALNM was likely to occur in patients with BI-RADS category 5. The Gail model could improve the diagnostic sensitivity of the US BI-RADS category for predicting ALNM in breast cancer.

Gail Model Improves the Diagnostic Performance of the Fifth Edition of Ultrasound BI-RADS for Predicting Breast Cancer: A Multicenter Prospective Study

RATIONALE AND OBJECTIVES

The sonographic appearance of benign and malignant breast nodules overlaps to some extent, and we aimed to assess the performance of the Gail model as an adjunctive tool to ultrasound (US) Breast Imaging Reporting and Data System (BI-RADS) for predicting the malignancy of nodules.

MATERIALS AND METHODS

From 2018 to 2019, 2607 patients were prospectively enrolled by 35 health care facilities. An individual breast cancer risk was assessed by the Gail model. Based on B-mode US, color Doppler, and elastography, all nodules were evaluated according to the fifth edition of BI-RADS, and these nodules were all confirmed later by pathology.

RESULTS

We demonstrated that the Gail model, age, tumor size, tumor shape, growth orientation, margin, contour, acoustic shadowing, microcalcification, presence of duct ectasia, presence of architectural distortion, color Doppler flow, BI-RADS, and elastography score were significantly related to breast cancer (all p < 0.001). The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the curve (AUC) for combining the Gail model with the BI-RADS category were 95.6%, 91.3%, 85.0%, 97.6%, 92.8%, and 0.98, respectively. Combining the Gail model with the BI-RADS showed better diagnostic efficiency than the BI-RADS and Gail model alone (AUC 0.98 vs 0.80, p < 0.001; AUC 0.98 vs 0.55, p < 0.001) and demonstrated a higher specificity than the BI-RADS (91.3% vs 59.4%, p < 0.001).

CONCLUSION

The Gail model could be used to differentiate malignant and benign breast lesions. Combined with the BI-RADS category, the Gail model was adjunctive to US for predicting breast lesions for malignancy. For the diagnosis of malignancy, more attention should be paid to high-risk patients with breast lesions.

Comparison of clinicopathological characteristics and prognosis in breast cancer patients with different Breast Imaging Reporting and Data System categories

Purpose

The Breast Imaging Reporting and Data System (BI-RADS) is a systematic and standardized scheme of the radiological findings of breast. However, there were different BI-RADS categories between breast cancers as the clinical characteristics in previous studies. We analyzed the association of BI-RADS categories with the clinicopathological characteristics and prognosis of breast cancer.

Methods

A total of 44,184 patients with invasive breast cancers assigned to BI-RADS category 3, 4, or 5 in preoperative mammography or ultrasonography were analyzed retrospectively using large-scale data from the Korean Breast Cancer Society registration system. The difference in the clinicopathological factors and prognoses according to the BI-RADS categories (BI-RADS 3–4 and BI-RADS 5) were compared between the mammography and ultrasonography groups. Comparisons of the clinicopathological factors in both groups were made using logistic regression analysis, while the prognoses were based on the breast cancer-specific survival using the Kaplan-Meier method and Cox proportional hazards model.

Results

The factors associated with BI-RADS were T stage, N stage, palpability, histology grade, and lymphovascular invasion in the mammography group; and N stage, palpability, histology grade, and lymphovascular invasion in the ultrasonography group. In the survival analysis, there were significant differences in the breast cancer-specific survival of the BI-RADS category groups in both of the mammography (hazard ratio [HR], 3.366; P < 0.001) and ultrasonography (HR, 2.877; P < 0.001) groups.

Conclusion

In this study, the BI-RADS categories of preoperative mammography and ultrasonography of patients with invasive breast cancer were associated with prognosis and could be an important factor in making treatment decisions.

Management of breast lesions seen on US images: dual-model radiomics including shear-wave elastography may match performance of expert radiologists

PURPOSE

To develop a nomogram incorporating B-mode ultrasound (BMUS) and shear-wave elastography (SWE) radiomics to predict malignant status of breast lesions seen on US non-invasively.

METHODS

Data on 278 consecutive patients from Hospital #1 (training cohort) and 123 cases from Hospital #2 (external validation cohort) referred for breast US with subsequent histopathologic analysis between May 2017 and October 2019 were retrospectively collected. Using their BMUS and SWE images, we built a radiomics nomogram to improve radiology workflow for management of breast lesions. The performance of the algorithm was compared with a consensus of three ACR BI-RADS committee experts and four individual radiologists, all of whom interpreted breast US images in clinical practice.

RESULTS

Twelve features from BMUS and three from SWE were selected finally to construct the respective radiomic signature. The nomogram based on the dual-modal US radiomics achieved good diagnostic performance in the training (AUC 0.96; 95% confidence intervals [CI], 0.94-0.98) and the validation set (AUC 0.92; 95% CI, 0.87-0.97). For the 123 test lesions, the algorithm achieved 105 of 123 (85%) accuracy, comparable to the expert consensus (104 of 123 [85%], P =  0.86) and four individual radiologists (93, 99, 95 and 97 of 123, with P value of 0.05, 0.31, 0.10 and 0.18 respectively). Furthermore, the model also performed well in the BI-RADS 4 and 5 categories.

CONCLUSIONS

Performance of a dual-model US radiomics nomogram based on SWE for breast lesion classification may comparable to that of expert radiologists who used ACR BI-RADS guideline.

Diagnostic value of PD-1 mRNA expression combined with breast ultrasound in breast cancer patients

Introduction

This study explored the value of measuring programmed death 1 (PD-1) in peripheral blood, combined with breast ultrasound using the Breast Imaging Reporting and Data System (BI-RADS) classification, for differentiation between benign and malignant breast tumors.

Materials and methods

We enrolled 113 patients with breast cancer and 66 patients with benign breast tumors who were admitted to Hangzhou First People’s Hospital from September 2014 to August 2017. The mRNA level of PD-1 was detected by quantitative real-time polymerase chain reaction.

Results

The mRNA levels of PD-1 were significantly higher in the peripheral blood of patients with breast cancer than those in patients with benign breast tumors. The diagnostic sensitivity of PD-1 mRNA expression was 0.805, the specificity was 0.788, and the area under the curve (AUC) was 0.848 (P < 0.001); the sensitivity of breast ultrasound-based BI-RADS classification was 0.752, the specificity was 0.909, and the AUC was 0.906 (P < 0.001); and the combined sensitivity, specificity, and AUC of the two assays were 0.920, 0.879, and 0.938, respectively (P < 0.001). Progesterone receptor-positive breast cancer patients exhibited high levels of PD-1 expression (P < 0.001).

Conclusion

This study suggests that the measurement of PD-1 combined with breast ultrasound-based BI-RADS classification represents a significant improvement for breast cancer diagnosis compared with diagnoses based on either method alone.

Correlations Among Ultrasound-Guided Diffuse Optical Tomography, Microvessel Density, and Breast Cancer Prognosis

OBJECTIVES

To investigate the correlation among ultrasound-guided diffuse optical tomography (DOT), microvessel density, and breast cancer prognosis.

METHODS

Before surgery, the total hemoglobin (Hb) concentrations of 184 female patients with breast cancer with only a single lesion were measured. During follow-up, 23 patients had recurrence or metastatic disease after surgery. Among these patients, 18 with recurrence or metastatic disease within 3 years after surgery were paired with 18 patients without recurrence or metastatic disease. We retrospectively reviewed the pathologic sections of those 36 patients, conducted immunohistochemical staining, and counted the microvessel densities. Then we analyzed the correlation between microvessel density and total Hb, compared total Hb and microvessel density among breast cancers with different prognoses, and tested the value of DOT in predicting the prognosis of breast cancer.

RESULTS

Microvessel density and total Hb were linearly correlated (r = 0.584; P < .001). Total Hb and microvessel density were significantly increased in the metastasis group (P = .001 and .027, respectively). A receiver operating characteristic curve analysis showed that at a total Hb cutoff value of 221.7 μmol/L, the sensitivity, specificity, and area under the curve of DOT for predicting recurrence or metastasis were 0.826, 0.516, and 0.660, respectively.

CONCLUSIONS

The total Hb concentration can reflect a tumor's blood supply. Patients with a high total Hb concentration and microvessel density have a higher risk for a poorer prognosis. Total Hb can be used as an indicator of breast cancer prognosis. Diffuse optical tomography can help physicians identify patients with a high risk of metastasis and make clinical decisions.

Does patient age affect the PPV3 of ACR BI-RADS Ultrasound categories 4 and 5 in the diagnostic setting?

OBJECTIVES

To calculate the positive predictive value of biopsies performed (PPV₃) of the Ultrasound section of the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS US) atlas categories 4 and 5 in different age groups and to determine whether patient age influences the PPV₃ of each category in the diagnosis of breast lesions.

METHODS

We identified 2,433 ACR BI-RADS US categories 4 and 5 lesions with a known pathological diagnosis in 2,433 women. The patients were classified into three age groups (<35, 35-50, and >50 years). The age-related PPV₃ of each category in the three age groups were calculated based on the pathological diagnoses and compared using the chi-squared test.

RESULTS

The overall PPV₃ of each category was within the reference range provided by the ACR in 2013. PPV₃ gradually increased with increasing age in patients with category 4 lesions. PPV₃ in the oldest group with subcategories 4A and 4B lesions were close to or exceeded the reference values.

CONCLUSIONS

PPV₃ and age were significantly associated in patients with category 4 lesions according to the newest edition of ACR BI-RADS US in the diagnostic setting. Closer attention should be given to older patients when assigning a final assessment category.

KEY POINTS

• In patients with category 4 lesions , the likelihood of malignancy is associated with age. • In patients with category 5 lesions, the association is not definite. • Closer attention should be given to older patients in applying the ACR BI-RADS US.