Validation study of the UICC TNM classification of malignant tumors, seventh edition, in breast cancer

Predictive value of contrast-enhanced ultrasonography and ultrasound elastography for management of BI-RADS category 4 nonpalpable breast masses

PURPOSE

The objective of this study was to investigate the independent risk factors and associated predictive values of contrast-enhanced ultrasound (CEUS), shear wave elastography (SWE), and strain elastography (SE) for high-risk lesions (HRL) and malignant tumors (MT) among nonpalpable breast masses classified as BI-RADS category 4 on conventional ultrasound.

METHODS

This prospective study involved consecutively admitted patients with breast tumors from January 2018, aiming to explore the management of BI-RADS category 4 breast tumors using CEUS and elastography. We conducted a retrospective review of patient data, focusing on those with a history of a nonpalpable mass as the primary complaint. Pathologic findings after surgical resection served as the gold standard. The CEUS arterial-phase indices were analyzed using contrast agent arrival-time parametric imaging processing mode, while quantitative and qualitative indices were examined on ES images. Independent risk factors were identified through binary logistic regression multifactorial analysis. The predictive efficacy of different modalities was compared using a receiver operating characteristics curve. Subsequently, a nomogram for predicting the risk of HRL/MT was established based on a multifactorial logistic regression model.

RESULTS

A total of 146 breast masses from 146 patients were included, comprising 80 benign tumors, 12 HRLs, and 54 MTs based on the final pathology. There was no significant difference in pathologic size between the benign and HRL/MT groups [8.00(6.25,10.00) vs. 9.00(6.00,10.00), P = 0.506]. The diagnostic efficacy of US plus CEUS exceeded that of US plus SWE/SE for BI-RADS 4 nonpalpable masses, with an AUC of 0.954 compared to 0.798/0.741 (P ＜ 0.001). Further stratified analysis revealed a more pronounced improvement for reclassification of BI-RADS 4a masses (AUC: 0.943 vs. 0.762/0.675, P ＜ 0.001) than BI-RADS 4b (AUC:0.950 vs. 0.885/0.796, P＞0.05) with the assistance of CEUS than SWE/SE. Employing downgrade CEUS strategies resulted in negative predictive values ranging from 95.2 % to 100.0 % for BI-RADS 4a and 4b masses. Conversely, using upgrade nomogram strategies, which included the independent predictive risk factors of irregular enhanced shape, poor defined enhanced margin, earlier enhanced time, increased surrounding vessels, and presence of contrast agent retention, the diagnostic performance achieved an AUC of 0.947 with good calibration.

CONCLUSION

After investigating the potential of CEUS and ES in improving risk assessment and diagnostic accuracy for nonpalpable BI-RADS category 4 breast masses, it is evident that CEUS has a more significant impact on enhancing classification compared to ES, particularly for BI-RADS 4a subgroup masses. This finding suggests that CEUS may offer greater benefits in improving risk assessment and diagnostic accuracy for this specific subgroup of breast masses.

Evaluating breast ultrasound S-detect image analysis for small focal breast lesions

Background

S-Detect is a computer-assisted, artificial intelligence-based system of image analysis that has been integrated into the software of ultrasound (US) equipment and has the capacity to independently differentiate between benign and malignant focal breast lesions. Since the revision and upgrade in both the breast imaging-reporting and data system (BI-RADS) US lexicon and the S-Detect software in 2013, evidence that supports improved accuracy and specificity of radiologists' assessment of breast lesions has accumulated. However, such assessment using S-Detect technology to distinguish malignant from breast lesions with a diameter no greater than 2 cm requires further investigation.

Methods

The US images of focal breast lesions from 295 patients in our hospital from January 2019 to June 2022 were collected. The BI-RADS data were evaluated by the embedded program and as manually modified prior to the determination of a pathological diagnosis. The receiver operator characteristic (ROC) curves were constructed to compare the diagnostic accuracy between the assessments of the conventional US images, the S-Detect classification, and the combination of the two.

Results

There were 326 lesions identified in 295 patients, of which pathological confirmation demonstrated that 239 were benign and 87 were malignant. The sensitivity, specificity, and accuracy of the conventional imaging group were 75.86%, 93.31%, and 88.65%. The sensitivity, specificity, and accuracy of the S-Detect classification group were 87.36%, 88.28%, and 88.04%, respectively. The assessment of the amended combination of S-Detect with US image analysis (Co-Detect group) was improved with a sensitivity, specificity, and accuracy of 90.80%, 94.56%, and 93.56%, respectively. The diagnostic accuracy of the conventional US group, the S-Detect group, and the Co-Detect group using area under curves was 0.85, 0.88 and 0.93, respectively. The Co-Detect group had a better diagnostic efficiency compared with the conventional US group (Z = 3.882, p = 0.0001) and the S-Detect group (Z = 3.861, p = 0.0001). There was no significant difference in distinguishing benign from malignant small breast lesions when comparing conventional US and S-Detect techniques.

Conclusions

The addition of S-Detect technology to conventional US imaging provided a novel and feasible method to differentiate benign from malignant small breast nodules.

The novel sugar transporter SLC50A1 as a potential serum-based diagnostic and prognostic biomarker for breast cancer

Background

The novel sugar transporter and membrane protein SLC50A1 has been identified as a potential candidate biomarker for breast cancer; however, its potential as a serum biomarker for breast cancer detection and prognosis is unclear. The aim of this study was to investigate the serum expression profile of SLC50A1 and to determine its diagnostic and prognostic significance in breast cancer.

Materials and methods

Bioinformatics analysis was conducted, and data for SLC50A1 expression in human breast cancer were collected. Semi-quantitative real-time PCR and ELISA were performed to compare SLC50A1 expression in several breast cancer cell lines, one paired tissue cohort (n=20) and two independent cohorts of human breast cancer patients (n=85) and healthy individuals (n=30). The results were analyzed statistically, and associations between clinicopathological and survival data were evaluated by multivariate Cox regression analysis.

Results

SLC50A1 was confirmed as a candidate breast cancer gene by bioinformatics analysis. SLC50A1 mRNA expression levels were significantly upregulated in breast cancer (P<0.001). Serum SLC50A1 levels were able to discriminate between women with breast cancer and healthy women with a sensitivity of 75.3% and a specificity of 100.0% (P<0.001; area under the curve=0.915). Interestingly, SLC50A1 protein expression was associated with estrogen receptor (P=0.016) and HER2 status (P=0.037). Furthermore, SLC50A1 levels were positively related to unfavorable 3-year outcomes in patients with high-grade breast cancer (HR =1.823, P=0.01), indicating its potential use as an independent prognostic factor.

Conclusion

SLC50A1 can be used as a serum-based diagnostic and prognostic biomarker in breast cancer. However, further studies are needed to clarify its potential role as a therapeutic target.

Application of contrast-enhanced ultrasound in the diagnosis of small breast lesions

BACKGROUND

Breast cancer is the most common cancer in women worldwide. The purpose of the study was to observe the features of contrast-enhanced ultrasound (CEUS) and the combination with Breast Imaging-Reporting and Data System (BI-RADS) of conventional ultrasound for assessing small breast lesions.

OBJECTIVES

The study was to explore the small breast lesions' features of contrast-enhanced ultrasound (CEUS) and the combination with Breast Imaging-Reporting and Data System (BI-RADS) of conventional ultrasound, in order to improve the diagnostic accuracy of early breast cancer.

METHODS

105 lesions were subject to conventional US (ultrasound) and CEUS before operations or biopsies. Among 105 breast lesions, six patient diagnoses were established by thick core-needle biopsy, while the rest were all confirmed by surgery and pathology.

RESULTS

Significant differences were found between benign and malignant lesions in qualitative and quantitative indexes (peak) of CEUS (P < 0.05). The qualitative features of malignant small breast lesions were as follows: (1) enhanced intensity within the lesion was not uniform (61/61,100%); (2) the speed of wash-in was earlier than the surrounding tissue (58/61, 95.1%); (3) lesion interior and the surrounding tissues had contrast vessel performance (61/61,100%). Peak of malignant lesions (35.77±11.45) was higher than that of benign lesions (31.96±10.76) (P < 0.05). The diagnostic performance of BI-RADS-US plus qualitative indexes (method one) in terms of area under receiver operating characteristic curve (AUROC) were the highest (i.e., AUROC = 0.817), in comparison with other combined diagnostic methods. The associated sensitivity, specificity and accuracy were 78.69%, 84.09% and 80.95%, respectively. With method one, however, was similar with US-BI-RADS in specificity, 11 malignant breast lesions were regarded as a higher classification of BI-RADS and classified into malignant group, which were identified as benign on US-BI-RADS originally.

CONCLUSIONS

CEUS was useful to differentiate benign from malignant small breast lesions, and the combination of CEUS and BI-RADS-US can improve the early diagnosis of breast cancers.

Presentation of the Molecular Subtypes of Breast Cancer Detected By Immunohistochemistry in Surgically Treated Patients

INTRODUCTION

The detection of estrogen, progesterone and HER-2 neu receptors on the surface of the tumour cell is a significant prognostic factor, alone or in combination. The presence or absence of receptors on the surface of the tumour cell is associated with the conditional gene expression in the tumour cell itself. Based on these genetically determined expressions of the tumour cell, five molecular subtypes of breast cancer have been classified on the St. Gallen International Expert Consensus in 2011 that can be immunohistochemically detected, with each subtype manifesting certain prognosis and aggression.

AIM

Analyzing the presentation of molecular subtypes of breast cancer that are immunohistochemically detected in surgically treated patients at the Clinic for Thoracic and Vascular Surgery.

MATERIAL AND METHODS

We used the international classification on molecular subtypes of breast cancer which divides them into: Luminal A (ER+ and/or PR+, HER-2 negative, Ki-67 < 14%), Luminal B with HER-2 negative (ER+ and/or PR+, HER-2 negative, Ki-67 ≥ 14%), Luminal B with HER-2 positive (ER+ and/or PR+, HER-2+, any Ki-67), HER-2 enriched (ER-, PR-, HER-2+), and basal-like (triple negative) (ER-, PR-, HER-2 negative, CK5/6+ and/or EGFR+). A total of 290 patients, surgically treated for breast cancer, were analysed during 2014.

RESULTS

In our analysis, we found that Luminal A was present in 77 (26.55%) patients, Luminal B HER-2 negative was present in 91 (31.38%) patients, Luminal B HER-2 positive was present in 70 (24.14%) patients, HER-2 enriched was present in 25 (8.62%) patients and basal-like (or triple negative) was present in 27 (9.31%) patients.

CONCLUSION

Detecting the subtype of breast cancer is important for evaluating the prognosis of the disease, but also for determining and providing an adequate therapy. Therefore, determining the subtype of breast cancer is necessary for the routine histopathological assay.

Relationship of clinical and pathologic nodal staging in locally advanced breast cancer: current controversies in daily practice?

Systemic neo-adjuvant therapy plays a primary role in the management of locally advanced breast cancer. Without having any negative effect in overall survival, induction chemotherapy potentially assures a surgery approach in unresectable disease or a conservative treatment in technically resectable disease and acts on a well-vascularized tumor bed, without the modifications induced by surgery. A specific issue has a central function in the neo-adjuvant setting: lymph nodes status. It still represents one of the strongest predictors of long-term prognosis in breast cancer. The discussion of regional radiation therapy should be a matter of debate, especially in a pathological complete response. Currently, the indication for radiotherapy is based on the clinical stage before the surgery, even for the irradiation of the loco-regional lymph nodes. Regardless of pathological down-staging, radiation therapy is accepted as standard adjuvant treatment in locally advanced breast cancer.