Neoadjuvant approach in patients with early breast cancer: patient assessment, staging, and planning

Dismal pathological response to neoadjuvant chemotherapy in stage III breast cancer patients in Tanzania: A retrospective review

Response to neoadjuvant treatment in breast cancer has been associated with good oncological outcomes. In Tanzania, a majority of breast cancer patients are diagnosed at stage III; hence, they almost always require neoadjuvant therapy. However, the response to neoadjuvant therapy in these patients remains unknown. This study examined the pathological responses in women with stage III breast cancer who underwent neoadjuvant therapy and identified sociodemographic and clinical predictors of the pathological response in this cohort. This hospital-based retrospective cohort study was conducted between December 2021 and April 2022. It included women with breast cancer who received neoadjuvant therapy and underwent surgery for breast cancer at Muhimbili National Hospital in Tanzania, from January 2018 through December 2021. Data analysis was performed using SPSS version 25. A complete pathological response was identified upon pathological review of the mastectomy specimen. Chi-square tests and Fischer's exact tests were used to evaluate the factors associated with a complete pathological response, with a p value of less than 0.05 indicating statistical significance. Ethical approval was obtained from the Muhimbili University of Health and Allied Sciences Institutional Review Board. The study complied with the Helsinki Declaration on studies involving human subjects. A total of 181 breast cancer patients were recruited for the study, with a mean age of 51±12.6 (28-89) years. A complete pathological response to neoadjuvant therapy was observed in 40 (22.1%) patients which is relatively lower compared to studies from Western countries. Disease stage at diagnosis was associated with response to neoadjuvant therapy, with those at stage IIIA showing better complete response than those at stages IIIB and IIIC indicating a need to improve diagnostic strategies to capture patients in the earlier stages to improve outcomes.

Investigating the optimal timing for the ultrasound prediction of a pathologic complete response in neoadjuvant breast cancer treatment

Background

Neoadjuvant therapy (NAT) for breast cancer requires effective monitoring to assess the treatment response. To optimize treatment strategies, the early prediction of the therapeutic response is crucial. This study evaluated the predictive performance of three ultrasound models-the longest axis model (LAM), the dual axes model (DAM), and the manual segment model (MSM)-with a focus on early treatment cycles, and the relationship between tumor shrinkage and the probability of a pathologic complete response (pCR).

Methods

In total, 121 breast cancer patients (with 942 ultrasound images) at the Renmin Hospital of Wuhan University from December 2020 to July 2023 were enrolled in this prospective study. The ability of the three ultrasound models to predict the pCR across 6-8 NAT cycles was compared. Tumor response was measured as the tumor shrinkage ratio (TSR) relative to the baseline and the preceding cycle. Area under the curve (AUC) values were calculated for each model and cycle, and statistical significance was determined using the DeLong test. A logistic regression model based on the first-cycle MSM was used to quantify the relationship between the TSR and the probability of a pCR.

Results

The models had the highest AUC values in the first cycle of NAT, indicating their superior early predictive performance (P<0.05). Tumor shrinkage was significantly greater in the pCR group than in the non-pCR group. The logistic regression analysis based on the first-cycle MSM revealed a strong correlation between tumor shrinkage and the probability of a pCR, such that patients with ≥50% shrinkage had a higher likelihood of achieving a pCR.

Conclusions

Early cycle ultrasound assessments, particularly those that used the MSM, have strong predictive value for the pCR. Integrating a tumor shrinkage-based probability analysis enhances the predictive accuracy of the models. These findings support the use of early ultrasound evaluation in clinical practice to optimize NAT strategies and patient outcomes.

The role and potential of digital breast tomosynthesis in neoadjuvant systemic therapy evaluation for optimising breast cancer management: a pictorial essay

Neoadjuvant therapy (NT) has become the gold standard for treating locally advanced breast cancer (BC). The assessment of pathological response (pR) post-NT plays a crucial role in predicting long-term survival, with contrast-enhanced MRI currently recognised as the preferred imaging modality for its evaluation. Traditional imaging techniques, such as digital mammography (DM) and ultrasonography (US), encounter difficulties in post-NT assessments due to breast density, lesion changes, fibrosis, and molecular patterns. Digital breast tomosynthesis (DBT) offers solutions to prevalent challenges in DM, such as tissue overlap, and facilitates a comprehensive assessment of lesion morphology, dimensions, and margins. Studies suggest that DBT correlates more accurately with pathology than DM and US, showcasing its potential advantages. This pictorial essay demonstrates the potential of DBT as a complementary tool to DM for assessing pR after NT, including instances of true- and false-positive assessments correlated with histopathological findings. In conclusion, DBT emerges as a valuable adjunct to DM, effectively addressing its limitations in post-NT assessment. The technology's potential to diminish tissue overlap, improve discrimination, and provide multi-dimensional perspectives demonstrates promising results, indicating its utility in scenarios where MRI is contraindicated or inaccessible.

Combining Contrast-Enhanced Ultrasound with Methylene Blue for Detection of Sentinel Lymph Nodes in Early Breast Cancer

Aims/Background Sentinel lymph nodes (SLNs) are an important prognostic factor for breast cancer patients, but traditional axillary lymph node dissection methods have many complications, while sentinel lymph node biopsy has been developed as a better method. This study aimed to evaluate the efficiency of combining contrast-enhanced ultrasound (CEUS) with methylene blue for identifying SLNs in early-stage breast cancer patients. Methods This retrospective study included clinical data from 163 female patients with lymph node-negative and T1-2 early breast cancer admitted to China-Japan Friendship Hospital between August 2022 and November 2023. All patients received a periareolar injection of SonoVue followed by ultrasonography to identify SLNs. The methylene blue was used to detect SLNs during the surgery, and the patients underwent sentinel lymph node biopsy. We compared the methylene blue method with combined CEUS and methylene blue to identify the number of SLNs per patient. Furthermore, these two methods were compared to determine the number of SLNs and the number of SLNs positive in 34 SLNs positive patients. Results This study included 163 patients with tumor (T)1-2 node (N)0-3 metastasis (M)0. The identification rate of SLNs was 100% for CEUS. We detected 376 SLNs using a combined CEUS and methylene blue method, with a median of 2 (1, 5). Furthermore, methylene blue identified 627 SLNs, with a median of 3 (1, 12). However, CEUS detected a significantly lower number of SLNs than those identified by methylene blue (p < 0.001). Additionally, metastasis frequency was substantially higher for the combined CEUS and methylene blue method (66.3%, 53/80) compared to methylene blue approach alone (39.5%, 58/147) (p < 0.001). Conclusion Combining CEUS with methylene blue is expected to improve the accuracy of axillary staging in breast cancer patients while reducing surgical trauma and postoperative complications.

Is the Neutrophil-to-Lymphocyte Ratio a Predictive Factor of Pathological Complete Response in Egyptian Breast Cancer Patients Treated with Neoadjuvant Chemotherapy?

Background and Objectives: The role of the neutrophil-to-lymphocyte ratio (NLR) as a predictor of response in breast cancers after neoadjuvant chemotherapy is controversial. This study aims to explore the relationship of NLR with pathological complete response (pCR) in a cohort of Egyptian breast cancer patients who received neoadjuvant chemotherapy. Materials and Methods: Forty-six breast cancer females received preoperative neoadjuvant chemotherapy and then underwent surgery. All resected tumors were evaluated to determine the pathologic effect of the neoadjuvant chemotherapy. A complete blood count was carried out at baseline before beginning the neoadjuvant chemotherapy. The absolute count of neutrophils was divided by the absolute count of lymphocytes to calculate the NLR. Results: Of the study patients, 18 (39.1%) were considered to have a low NLR (NLR < 1.76), and 28 (60.9%) were considered to have a high NLR (NLR ≥ 1.76). Patients with a low NLR had 18-fold higher rates of pCR when compared to patients with a high NLR (OR 18.1; 95% CI (1.058-310.757); p = 0.046). Conclusions: Our findings indicate that the pretreatment NLR is a pivotal predictor factor of the pathological complete response in Egyptian breast cancer patients treated with neoadjuvant chemotherapy.

Dual-layer detector spectral computed tomography quantitative parameters for predicting pathological complete remission after neoadjuvant treatment of breast cancer

Background

Breast cancer (BC) is a common cancer among women worldwide, and although the use of neoadjuvant therapy (NAT) for BC has become more widespread, there is no standardized prediction of the efficacy of NAT for BC. This study aimed to evaluate the value of quantitative parameters of dual-layer detector spectral computed tomography (DLCT) in predicting whether BC patients can achieve pathological complete response (pCR) after NAT.

Methods

Patients who were first diagnosed with BC in Shandong Cancer Hospital and Institute and received only NAT before surgery were selected for participation in this study. All breast computed tomography (CT) imaging examinations were performed using DLCT, within 1 week before initiating NAT. The gold standard for evaluating the effect of NAT is pathologic response established at surgery. The Miller-Payne grading system was applied to assess the response to NAT. Quantitative parameters were extracted from DLCT, including CT value, normalized CT value, iodine concentration (IC), normalized iodine concentration (NIC), the slope of the spectral Hounsfield unit (HU) curve, effective atomic number, and the normalized effective atomic number. The Mann-Whitney U test was used to compare the distribution differences of DLCT quantitative parameters between the pCR group and the non-pCR group. The diagnostic performance of the quantitative parameters was analyzed by receiver operating characteristic curve.

Results

In the neoadjuvant chemotherapy group (n=80), compared with the non-pCR group, the slope of the spectral HU curve, IC, effective atomic number, and NIC of arterial phase in the pCR group were higher, and the difference was statistically significant (P<0.05); area under the curve (AUC): 0.768, 0.791, 0.834, and 0.770, respectively. In the neoadjuvant targeted therapy group (n=40), compared with the pCR group, the CT value, IC, effective atomic number, and NIC of the arterial phase in the non-pCR group were higher, and the difference was statistically significant (P<0.05); AUC: 0.844, 0.813, 0.802, and 0.766, respectively. There was no significant difference (P>0.05) in DLCT venous phase quantitative parameters between pCR and non-pCR in 70 patients treated with NAT.

Conclusions

The study suggested a possibility that DLCT provided a potential tool to develop a model for predicting pCR to NAT in BC.

Surgical outcomes of neoadjuvant endocrine treatment in early breast cancer: meta-analysis

BACKGROUND

Neoadjuvant endocrine therapy presents an important downstaging option with lower toxicity than neoadjuvant chemotherapy in oestrogen receptor (ER)-positive early breast cancer. Meta-analysis of the effects of neoadjuvant endocrine therapy on surgical outcomes across randomized clinical trials (RCTs) and cohort studies has not previously been performed.

METHODS

A systematic review and meta-analysis was performed to evaluate the effect of neoadjuvant endocrine therapy on surgical outcomes (PROSPERO (international prospective register of systematic reviews, 2020)) compared with surgery followed by adjuvant endocrine therapy. PubMed and EMBASE were searched to identify RCT and cohort studies between 1946 and 27 March 2024. Two independent reviewers manually screened the identified records and extracted the data. Risk of bias was assessed using the Cochrane Collaboration tools and random-effects meta-analysis was done with ReviewManager.

RESULTS

The search identified 2390 articles eligible for screening. The review included 20 studies (12 cohort and 8 RCTs); 19 were included in the meta-analysis with a total of 6382 patients. Overall, neoadjuvant endocrine therapy was associated with a lower mastectomy rate compared with surgery first (risk ratio (RR) 0.53, 95% c.i. 0.44 to 0.64). Subgroup analysis showed similar improvement in the mastectomy rate in the neoadjuvant endocrine therapy group versus control group irrespective of study type (RCT: RR 0.58, 95% c.i. 0.50 to 0.66; cohorts: RR 0.48, 95% c.i. 0.33 to 0.70). There was no difference in the mastectomy rate by duration of neoadjuvant endocrine therapy (more than 4 months: RR 0.57, 95% c.i. 0.42 to 0.78; 4 months or less than 4 months: RR 0.52, 95% c.i. 0.43 to 0.64). Most of the studies were characterized by moderate-quality evidence with significant heterogeneity.

CONCLUSION

Neoadjuvant endocrine therapy is associated with a reduction in mastectomy rate. Given the moderate methodological quality of previous studies, further RCTs are required.

REGISTRATION ID

CRD42020209257.

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer

RATIONALE AND OBJECTIVES

To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer.

MATERIALS AND METHODS

In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA).

RESULTS

The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models.

CONCLUSION

The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Performance of Contrast-Enhanced Mammography (CEM) for Monitoring Neoadjuvant Chemotherapy Response among Different Breast Cancer Subtypes

Neoadjuvant chemotherapy (NAT) plays a crucial role in breast cancer (BC) treatment, both in advanced BC and in early-stage BC, with different rates of pathological complete response (pCR) among the different BC molecular subtypes. Imaging monitoring is mandatory to evaluate the NAT efficacy. This study evaluates the diagnostic performance of Contrast-Enhanced Mammography (CEM) in BC patients undergoing NAT. This retrospective two-center study included 174 patients. The breast lesions were classified based on the molecular subtypes in hormone receptor (HR+)/HER2-, HER2+, and triple-negative breast cancer (TNBC). The histopathological analysis performed following surgery was used as a reference standard for the pCR. Sensitivity, specificity, PPV, and NPV were measured overall and for the different subtypes. We enrolled 174 patients, 79/174 (46%) HR+/HER2-, 59/174 (33.9%) HER2+, and 35/174 (20.1%) TNBC; the pCR was found in 64/174 (36.8%), of which 57.1% were TNBCs. In the total population, the CEM sensitivity and specificity were 66.2% and 75.2%, with a PPV of 61.4% and an NPV of 78.8%. The highest specificity (80.9%) and NPV (91.7%) were found in HR+/HER2-, while the highest sensitivity (70%) and PPV appeared (73.7%) in TNBC. The results indicate that CEM is a valid tool to assess the pCR, with different performances among the subtypes of BC.

Correlation between Baseline Conventional Ultrasounds, Shear-Wave Elastography Indicators, and Neoadjuvant Therapy Efficacy in Triple-Negative Breast Cancer

In patients with triple-negative breast cancer (TNBC)-the subtype with the poorest prognosis among breast cancers-it is crucial to assess the response to the currently widely employed neoadjuvant treatment (NAT) approaches. This study investigates the correlation between baseline conventional ultrasound (US) and shear-wave elastography (SWE) indicators and the pathological response of TNBC following NAT, with a specific focus on assessing predictive capability in the baseline state. This retrospective analysis was conducted by extracting baseline US features and SWE parameters, categorizing patients based on postoperative pathological grading. A univariate analysis was employed to determine the relationship between ultrasound indicators and pathological reactions. Additionally, we employed a receiver operating characteristic (ROC) curve analysis and multivariate logistic regression methods to evaluate the predictive potential of the baseline US indicators. This study comprised 106 TNBC patients, with 30 (28.30%) in a nonmajor histological response (NMHR) group and 76 (71.70%) in a major histological response (MHR) group. Following the univariate analysis, we found that T staging, dmax values, volumes, margin changes, skin alterations (i.e., thickening and invasion), retromammary space invasions, and supraclavicular lymph node abnormalities were significantly associated with pathological efficacy (p < 0.05). Combining clinical information with either US or SWE independently yielded baseline predictive abilities, with AUCs of 0.816 and 0.734, respectively. Notably, the combined model demonstrated an improved AUC of 0.827, with an accuracy of 76.41%, a sensitivity of 90.47%, a specificity of 55.81%, and statistical significance (p < 0.01). The baseline US and SWE indicators for TNBC exhibited a strong relationship with NAT response, offering predictive insights before treatment initiation, to a considerable extent.

Surgical Planning after Neoadjuvant Treatment in Breast Cancer: A Multimodality Imaging-Based Approach Focused on MRI

Neoadjuvant chemotherapy (NACT) today represents a cornerstone in the treatment of locally advanced breast cancer and highly chemo-sensitive tumors at early stages, increasing the possibilities of performing more conservative treatments and improving long term outcomes. Imaging has a fundamental role in the staging and prediction of the response to NACT, thus aiding surgical planning and avoiding overtreatment. In this review, we first examine and compare the role of conventional and advanced imaging techniques in preoperative T Staging after NACT and in the evaluation of lymph node involvement. In the second part, we analyze the different surgical approaches, discussing the role of axillary surgery, as well as the possibility of non-operative management after-NACT, which has been the subject of recent trials. Finally, we focus on emerging techniques that will change the diagnostic assessment of breast cancer in the near future.

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

Breast cancer (BC) is the most common cancer among women worldwide. Neoadjuvant chemotherapy (NACT) indications have expanded from inoperable locally advanced to early-stage breast cancer. Achieving a pathological complete response (pCR) has been proven to be an excellent prognostic marker leading to better disease-free survival (DFS) and overall survival (OS). Although diagnostic accuracy of MRI has been shown repeatedly to be superior to conventional methods in assessing the extent of breast disease there are still controversies regarding the indication of MRI in this setting. We intended to review the complex literature concerning the tumor size in staging, response and surgical planning in patients with early breast cancer receiving NACT, in order to clarify the role of MRI. Morphological and functional MRI techniques are making headway in the assessment of the tumor size in the staging, residual tumor assessment and prediction of response. Radiomics and radiogenomics MRI applications in the setting of the prediction of response to NACT in breast cancer are continuously increasing. Tailored therapy strategies allow considerations of treatment de-escalation in excellent responders and avoiding or at least postponing breast surgery in selected patients.