Axillary ultrasound during neoadjuvant systemic therapy in triple-negative breast cancer patients

Improving Prediction Accuracy of Residual Axillary Lymph Node Metastases in Node-Positive Triple-Negative Breast Cancer: A Radiomics Analysis of Ultrasound-Guided Clip Locations Using the SHAP Method

RATIONALE AND OBJECTIVES

To construct a radiomics nomogram derived from multiparametric ultrasound (US) imaging using the SHapley Additive exPlanations (SHAP) method for the accurate identification of residual axillary lymph node metastases post-neoadjuvant chemotherapy (NAC) among patients with triple-negative breast cancer (TNBC).

METHODS

A total of 405 consecutive patients with pathologically confirmed TNBC between 2016 and 2023 were recruited in the study and were divided into training (n = 284) and validation cohorts (n = 121). Radiomics features capturing detailed tumor characteristics were extracted from pre-NAC gray-scale US images at the locations of US-guided clip placement. The least absolute shrinkage and selection operator and the maximum relevance minimum redundancy algorithm were employed to identify key features and formulate the radiomics signature (RS). A nomogram based on US radiomics was then constructed using multivariable logistic regression analysis. The predictive efficacy of this model was evaluated through receiver operating characteristic curve analysis, calibration assessment, and decision curve analysis. SHAP summary plots were used to visualize the distribution of SHAP values across all features.

RESULTS

The nomogram integrates clinical and US characteristics with RS, yielded optimal AUC of 0.922 (95% CI, 0.890-0.954) in the training cohort, 0.904 (95% CI, 0.853-0.955) in the validation cohort. The calibration and decision curves confirmed favorable calibration and clinical value of the nomogram. SHAP provided further insight into the contributions of each feature to the model's outcomes.

CONCLUSION

The combined multiparametric US based radiomics nomogram plays a potential role in predicting residual axillary lymph node metastases after NAC in TNBCs.

Development of an Ultrasound-based Nomogram for Predicting Pathologic Complete Response and Axillary Response in Node-Positive Patients with Triple- Negative Breast Cancer

BACKGROUND

The accurate prediction of pathological complete response (pCR) in the breast and axillary lymph nodes (ALN) before neoadjuvant chemotherapy (NAC) is of utmost importance for the development of treatment strategies. We aim to construct a nomogram on ultrasound (US) and clinical-pathologic factors to predict breast and ALN pCR in node-positive triple-negative breast cancers (TNBCs).

METHODS

Patients identified with TNBCs from institution 1 (n = 328) were used for training cohort and those from institution 2 (n = 192) were for validation cohort. US was conducted before and after NAC, and characteristics were obtained from medical records. Univariate and multivariate regression analysis were performed to identify US and clinical-pathologic factors associated with breast and ALN pCR in the training cohort. The assessment of predictive performance was conducted using the receiving operating characteristic curve (ROC), discrimination, and calibration.

RESULTS

Overall, 34.6% of patients achieved breast pCR and 48.1% of patients achieved ALN pCR. The nomogram 1 used for predicting pCR in the breast (AUC, 0.84; 95% CI: 0.79, 0.88) outperformed the clinical (AUC, 0.73; 95% CI: 0.68, 0.78) and US models (AUC, 0.79; 95% CI: 0.74, 0.83). The nomogram 2 used for predicting pCR in the axllia (AUC, 0.83; 95% CI: 0.78, 0.87) also outperformed the clinical (AUC, 0.64; 95% CI: 0.58, 0.69) and US models (AUC, 0.80; 95% CI: 0.75, 0.84). The calibration curve and discrimination curve indicate that the nomogram has good calibration performance and clinical applicability.

CONCLUSION

The nomogram showed promising predictive performance for predicting breast and ALN pCR in patients with TNBCs.

A simple and convenient model combining multiparametric MRI and clinical features to predict tumour-infiltrating lymphocytes in breast cancer

AIM

To develop a simple and convenient method based on multiparametric magnetic resonance imaging (MRI) and clinical features to non-invasively predict tumour-infiltrating lymphocytes (TILs) in breast cancer (BC) and to explore the relationship between TIL levels and disease-free survival (DFS).

MATERIALS AND METHODS

A total of 172 BC patients were enrolled between November 2017 and June 2021 in this retrospective study. The patients were divided into high (≥10%) and low (<10%) TIL groups. Clinicopathological data were collected. MRI features were reviewed by two radiologists. Predictors associated with TILs were determined by using multivariable logistic regression analyses. Kaplan-Meier survival curves based on TIL levels were used to estimate DFS.

RESULTS

A total of 102 patients with low TILs and 70 patients with high TILs were included in the study. Tumour size (odds ratio [OR], 1.040; 95% confidence interval [CI]: 1.006, 1.075; p=0.020), apparent diffusion coefficient (ADC; OR, 1.003; 95% CI: 1.001, 1.005; p=0.015), clinical axillary lymph node status (CALNS; OR, 3.222; 95% CI: 1.372,7.568; p=0.007), and enhancement pattern (OR, 0.284; 95% CI: 0.143, 0.563; p<0.001) were independently associated with TIL levels. These features were used in the ALSE model (where A is ADC, L is CALNS, S is size, and E is enhancement pattern). High TILs were associated with better DFS (p=0.016).

CONCLUSION

The ALSE model derived from multiparametric MRI and clinical features could non-invasively predict TIL levels in BC, and high TILs were associated with longer DFS, especially in human epidermal growth factor receptor 2 (HER2)-positive BC and triple-negative BC (TNBC).

Combined conventional ultrasonography with clinicopathological features to predict axillary status after neoadjuvant therapy for breast cancer: A case-control study

OBJECTIVES

This study aimed to evaluate the value of a model combining conventional ultrasonography and clinicopathologic features for predicting axillary status after neoadjuvant therapy in breast cancer.

METHODS

This retrospective study included 329 patients with lymph node-positive who underwent neoadjuvant systemic treatment (NST) from June 2019 to March 2022. Ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes were analyzed before and after NST. The diagnostic efficacy of ultrasound, clinicopathological characteristics, and combined model were evaluated using multivariate logistic regression and receiver operator characteristic curve (ROC) analyses.

RESULTS

The area under ROC (AUC) for the ability of the combined model to predict the axillary pathological complete response (pCR) after NST was 0.882, that diagnostic effectiveness was significantly better than that of the clinicopathological model (AUC of 0.807) and the ultrasound feature model (AUC of 0.795). In addition, eight features were screened as independent predictors of axillary pCR, including clinical N stage, ERBB2 status, Ki-67, and after NST the maximum diameter reduction rate and margins of breast lesions, the short diameter, cortical thickness, and fatty hilum of lymph nodes.

CONCLUSIONS

The combined model constructed from ultrasound and clinicopathological features for predicting axillary pCR has favorable diagnostic results, which allowed more accurate identification of BC patients who had received axillary pCR after NST.

ADVANCES IN KNOWLEDGE

A combined model incorporated ultrasound and clinicopathological characteristics of breast lesions and axillary lymph nodes demonstrated favorable performance in evaluating axillary pCR preoperatively and non-invasively.

Mechanism-Based Sonodynamic–Chemo Combinations against Triple-Negative Breast Cancer

Due to its noninvasive nature, site-confined irradiation, and high tissue penetrating capabilities, ultrasound (US)-driven sonodynamic treatment (SDT) has been proven to have broad application possibilities in neoplastic and non-neoplastic diseases. However, the inefficient buildup of sonosensitizers in the tumor site remarkably impairs SDT efficiency. The present work proposes a deep-penetrating sonochemistry nanoplatform (Pp18-lipos@SRA737&DOX, PSDL) comprising Pp18 liposomes (Pp18-lipos, Plipo), SRA737 (a CHK1 inhibitor), and doxorubicin (DOX) for the controlled formation of reactive oxygen species (ROS) and release of DOX and SRA737 upon US activation, therefore increasing chemotherapeutic effectiveness and boosting SDT efficacy. Therein, the antitumor activities of DOX have been attributed to its intercalation into the nucleus DNA and induction of cell apoptosis. CHK1 evolved to respond to DNA damage and repair the damage via cell cycle progression. SRA737 is a potent and orally bioavailable clinical drug candidate for inhibiting CHK1, demonstrating adjuvant anticancer effect in vitro and in vivo. It was interesting to find that SRA737 carried into Plipo@DOX could significantly alleviate G2/M cell cycle arrest and aggravate DNA double-strand injuries, resulting in significant cell death. The developed US-switchable nanosystem provides a promising strategy for augmenting sono-chemotherapy against breast cancer controllably and precisely.

Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics

Objective

This study aimed to incorporate clinicopathological, sonographic, and mammographic characteristics to construct and validate a nomogram model for predicting disease-free survival (DFS) in patients with triple-negative breast cancer (TNBC).

Methods

Patients diagnosed with TNBC at our institution between 2011 and 2015 were retrospectively evaluated. A nomogram model was generated based on clinicopathological, sonographic, and mammographic variables that were associated with 1-, 3-, and 5-year DFS determined by multivariate logistic regression analysis in the training set. The nomogram model was validated according to the concordance index (C-index) and calibration curves in the validation set.

Results

A total of 636 TNBC patients were enrolled and divided into training cohort (n = 446) and validation cohort (n = 190). Clinical factors including tumor size > 2 cm, axillary dissection, presence of LVI, and sonographic features such as angular/spiculated margins, posterior acoustic shadows, and presence of suspicious lymph nodes on preoperative US showed a tendency towards worse DFS. The multivariate analysis showed that no adjuvant chemotherapy (HR = 6.7, 95% CI: 2.6, 17.5, p < 0.0005), higher axillary tumor burden (HR = 2.7, 95% CI: 1.0, 7.1, p = 0.045), and ≥ 3 malignant features on ultrasound (HR = 2.4, CI: 1.1, 5.0, p = 0.021) were identified as independent prognostic factors associated with poorer DFS outcomes. In the nomogram, the C-index was 0.693 for the training cohort and 0.694 for the validation cohort. The calibration plots also exhibited excellent consistency between the nomogram-predicted and actual survival probabilities in both the training and validation cohorts.

Conclusions

Clinical variables and sonographic features were correlated with the prognosis of TNBCs. The nomogram model based on three variables including no adjuvant chemotherapy, higher axillary tumor load, and more malignant sonographic features showed good predictive performance for poor survival outcomes of TNBC.

Key Points

• The absence of adjuvant chemotherapy, heavy axillary tumor load, and malignant-like sonographic features can predict DFS in patients with TNBC.

• Mammographic features of TNBC could not predict the survival outcomes of patients with TNBC.

• The nomogram integrating clinicopathological and sonographic characteristics is a reliable predictive model for the prognostic outcome of TNBC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08910-4.