Invasive Lobular Breast Cancer: Data to Support Surgical Decision Making

Initial interpretation scores of screening mammograms and cancer detection in BreastScreen Norway

PURPOSE

To explore the association between radiologists' interpretation scores, early performance measures and cumulative reading volume in mammographic screening.

METHOD

We analyzed 1,689,731 screening examinations (3,379,462 breasts) from BreastScreen Norway 2012-2020, all breasts scored 1-5 by two independent radiologists. Score 1 was considered negative/benign and score ≥2 positive in this scoring system. We performed descriptive analyses of recall, screen-detected cancer, positive predictive value (PPV) 1, mammographic features and histopathological characteristics by breast-based interpretation scores, and cumulative reading volume by examination-based interpretation scores.

RESULTS

Counting breasts and not women, 3.9 % (132,570/3,379,462) had a score of ≥2 by one or both radiologists. Of these, 84.8 % (112,440/132,570) were given a maximum score 2. Total recall rate was 1.6 % (53,735/3,379,462), 69.3 % (37,220/53,735) given maximum score 2. Among the 0.3 % (9733/3,379,462) diagnosed with screen-detected cancer, 34.6 % (3369/9733) had maximum score 3. The percentages of recall, screen-detected cancer and PPV-1 increased by increasing the sum of scores assigned by two radiologists (p < 0.001 for trend). Higher proportions of masses were observed among recalls and screen-detected cancers with low scores, and higher proportions of spiculated masses were observed for high scores (p < 0.001). Proportions of invasive carcinoma, histological grade 3 and lymph node positive tumors were higher for high versus low scores (p < 0.001). The proportion of examinations scored 1 increased by cumulative reading volume.

CONCLUSIONS

We observed higher rates of recall and screen-detected cancer and less favorable histopathological tumor characteristics for high versus low interpretation scores. However, a considerable number of recalls and screen-detected cancers had low interpretation scores.

Electrical lymph node scanning (ELS) system for real-time intra-operative detection of involved axillary lymph nodes in adjuvant breast cancer patients

Lymph node (LN) status is an essential prognostic factor in breast cancer (BC) patients, with an important role in the surgical and therapeutic plan. Recently, we have been developed a novel system for real-time intra-operative electrical LN scanning in BC patients. The ELS scores were calibrated by pathological evaluation of the LNs. Herein, we evaluated the efficacy of ELS in a prospective study for non-chemo-treated breast cancer patients. This is a prospective study in which ELS scores are blind for pathologists who declare the clearance or involvement of LNs based on permanent pathology as the gold standard. ELS and frozen-section (FS) pathology results were achieved intra-operatively, and samples were sent for the permanent pathology. The score of ELS did not affect the surgeons' decision, and the treatment approach was carried out based on FS pathology and pre-surgical data, such as imaging and probable biopsies. Patients were recruited from October 2021 through November 2022, and 381 lymph nodes of 97 patients were included in the study. In this study we recruited 38 patients (39.2%) with sentinel lymph node biopsy (SLNB) and 59 patients (60.8%) with ALND. Of the 381 LNs scored by ELS, 329 sentinel LNs underwent routine pathology, while others (n = 52) underwent both FS and permanent pathology. ELS showed a sensitivity of 91.4% for node-positive patients, decreasing to 84.8% when considering all LNs. Using ROC analysis, ELS diagnosis showed a significant AUC of 0.878 in relation to the permanent pathology gold standard. Comparison of ELS diagnosis for different tumor types and LN sizes demonstrated no significant differences, while increasing LN size correlated with enhanced ELS sensitivity. This study confirmed ELS's efficacy in real-time lymph node detection among non-chemo-treated breast cancer patients. The use of ELS's pathological scoring for intra-operative LN diagnosis, especially in the absence of FS pathology or for non-sentinel LN involvement, could improve prognosis and reduce complications by minimizing unnecessary dissection.

Invasive lobular breast cancer: Focus on prevention, genetics, diagnosis, and treatment

Invasive lobular cancer (ILC) is the most common of the breast cancer special types, accounting for up to 15% of all breast malignancies. The distinctive biological features of ILC include the loss of the cell adhesion molecule E-cadherin, which drives the tumor's peculiar discohesive growth pattern, with cells arranged in single file and dispersed throughout the stroma. Typically, such tumors originate in the lobules, are more commonly bilateral compared to invasive ductal cancer (IDC) and require a more accurate diagnostic examination through imaging. They are luminal in molecular subtype, and exhibit estrogen and progesterone receptor positivity and HER2 negativity, thus presenting a more unpredictable response to neoadjuvant therapies. There has been a significant increase in research focused on this distinctive breast cancer subtype, including studies on its pathology, its clinical and surgical management, and the high-resolution definition of its genomic profile, as well as the development of new therapeutic perspectives. This review will summarize the heterogeneous pattern of this unique disease, focusing on challenges in its comprehensive clinical management and on future insights and research objectives.

Tumor Characteristics of Bilateral Breast Cancer Compared with Unilateral Breast Cancer

BACKGROUND

Bilateral breast cancer (BC) has an incidence of 1 to 3 %. This study aimed to describe the clinicopathologic characteristics and management of bilateral BC, estimate disease-free survival (DFS), and compare DFS with unilateral BC.

METHODS

A retrospective analysis was performed for patients who had bilateral invasive BC or unilateral invasive BC and contralateral ductal carcinoma in situ (DCIS) treated at Mayo Clinic Rochester from 2008 to 2022. A 4:1 matched cohort of patients with unilateral invasive BC was used for comparison. The groups were compared using Wilcoxon rank-sum or chi-square tests. Disease-free survival was analyzed using the Kaplan-Meier method and log-rank test, with Cox proportional hazards regression used for multivariable analysis.

RESULTS

The study identified 278 cases of bilateral breast cancer (177 cases of bilateral invasive cancer and 101 cases of unilateral invasive cancer with contralateral DCIS), representing 4.1 % of invasive BCs. Biologic subtype was concordant between sides in 79.8 % of the patients. Initial surgery was bilateral mastectomy for 76.6 %, bilateral lumpectomy for 20.5 %, and unilateral mastectomy with unilateral lumpectomy for 2.9 % of the patients. Pathogenic variants in breast cancer predisposition genes were present in 21.7 % of those tested. The patients who had bilateral BC presented with a higher cT category than the patients who had unilateral BC (p = 0.02), and a higher proportion presented with ILC (17.3 % vs 10.9 %; p = 0.004), estrogen receptor-positive (ER+) disease (89.2 % vs 84.2 %; p = 0.04), multicentric/multifocal disease (37.1 % vs 24.3 %; p < 0.001), breast cancer pathogenic variant (21.7 % vs 12.4 %; p = 0.02), and palpable presentation (48.2 % vs 40.8 %; p = 0.03). The patients with bilateral BC showed DFS similar to that for the unilateral BC cohort (p = 0.71).

CONCLUSIONS

Bilateral BCs most commonly are biologically concordant between sides. Bilateral BC presented more commonly with larger tumors, lobular histology, ER+ status, multicentricity or multifocality, pathogenic variant, and palpable disease. Bilateral BC is not associated with worse DFS than unilateral BC.

Contrast-Enhanced Mammography (CEM) compared to Breast Magnetic Resonance (MRI) in the evaluation of breast lobular neoplasia

PURPOSE

To compare the diagnostic performance (detection, assessment of correct disease extent and multifocality/centricity) of Contrast-Enhanced Mammography (CEM) Versus Breast Magnetic Resonance (MRI) in the study of lobular neoplasms.

METHODS

We retrospectively selected all the patients who underwent surgery for a lobular breast neoplasm, either an in situ or an invasive tumor, and had undergone both breast CEM and MRI examinations during the pre-surgical planning. Wilcoxon Signed Rank test was performed to assess the differences between size measurements using the different methods and the post-surgical pathological measurements, considered the gold standard. The agreement in identifying multifocality/multicentricity among the different methods and the pathology was assessed using the Kappa statistics.

RESULTS

We selected 19 patients, of which one presented a bilateral neoplasm. Then, the images of these 19 patients were analyzed, for a total of 52 malignant breast lesions. We found no significant differences between the post-surgical pathological size of the lesions and the calculated size with CEM and MRI (p-value of the difference respectively 0.71 and 0.47). In all 20 cases, neoplasm detection was possible both with CEM and MRI. CEM and MRI showed an excellent ability to identify multifocal and multicentric cases (K statistic equal to 0.93 for both the procedures), while K statistic was 0.11 and 0.59 for FFDM and US, respectively.

CONCLUSION

The findings of this study suggest that CEM is a reliable imaging technique in the preoperative setting of patients with lobular neoplasm, with comparable results to breast MRI.

Molecular Classification of Breast Cancer

Breast carcinomas classified based on traditional morphologic assessment provide useful prognostic information. Although morphology is still the gold standard of classification, recent advances in molecular technologies have enabled the classification of these tumors into four distinct subtypes based on its intrinsic molecular profile that provide both predictive and prognostic information. This article describes the association between the different molecular subtypes with the histologic subtypes of breast cancer and illustrates how these subtypes may affect the appearance of tumors on imaging studies.

The Impact of Chemotherapy Prescription on Long-Term Survival Outcomes in Early-Stage Invasive Lobular Carcinoma - A Systematic Review and Meta-Analysis

INTRODUCTION

Invasive lobular carcinoma (ILCs) are typically endocrine responsive breast cancers which respond poorly to chemotherapy. The long-term survival advantage of prescribing chemotherapy in such cases remains unclear. To perform a systematic review and meta-analysis assessing, the impact of prescribing chemotherapy in such patients on long-term disease-free (DFS) and overall (OS) survival outcomes.

METHODS

A systematic review and meta-analysis was performed in accordance with the PRISMA guidelines. Ten-year DFS and OS were pooled as odds ratios (ORs) with 95% confidence intervals (CI) using the Mantel-Haenszel method. Time-to-effect modelling was performed using the generic inverse variance method.

RESULTS

Overall, 9 studies including 28,218 patients were included. The mean follow-up was 74 months (range: 0-150 months) and mean age was 60 years (range: 22-90 years). Of these, 34.7% received chemotherapy (9,797/28,218) and 66.3% did not receive chemotherapy (18,421/28,218). Chemotherapy prescription failed to improve 10-year DFS (OR: 0.89, 95% CI: 0.65-1.23) and OS (OR: 0.92, 95% CI: 0.72-1.18). When using time-to-effect modelling, chemotherapy prescription failed to improve DFS (hazard ratio (HR): 1.01, 95% CI: 0.78-1.31) and OS (HR: 1.07, 95% CI: 0.89-1.27, I²= 67%).

CONCLUSION

This meta-analysis illustrates no long-term survival advantage associated with chemotherapy prescription in the setting of early-stage ILC. In the absence of well-designed, prospective clinical trials evaluating the impact of chemotherapy on long-term outcomes in ILC, these results should be considered by the multidisciplinary team when deciding on the value of systemic chemotherapy prescription in ILC.

Prediction for Distant Metastasis of Breast Cancer Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Images under Deep Learning

This research aimed to explore the effect of using magnetic resonance imaging (MRI) radiomic features to establish a model for predicting distant metastasis under dynamic contrast-enhanced MRI imaging with deep learning algorithms. The deep learning algorithm was used to segment the images. A total of 96 cases with 100 lesions were included in the metastatic group, including 2 cases of bifocal breast cancer and 2 cases of multifocal breast cancer. There were 192 cases in the nonmetastatic group, with 197 lesions, including 5 cases of multifocal breast cancer. After dynamic contrast-enhancement, the morphological features and grayscale statistical features were extracted from the lesions to establish a prediction model through sum-sum check and feature dimension reduction. The accuracy, sensitivity, specificity, and area under receiver operator characteristic curve (AUC) of prediction models based only on imaging features were compared with those created by combining radiomic features with clinical and pathological features. The created predictive model based on radiomic features for distant metastases in breast cancer showed a sensitivity of 66.7%, a specificity of 84.2%, an accuracy of 78.3%, and an AUC of 0.744. The sensitivity of the prediction model for distant metastasis of breast cancer was 67.7%, the specificity was 86.8%, the accuracy was 80.5%, and the AUC was 0.763. Bone, lung, and liver were the most common distant metastatic sites of breast cancer. Under the dynamic contrast-enhanced MRI of deep learning, the prediction model combining radiomic features with clinical and pathological features showed better predictive performance.