Histopathological analysis of mucinous breast cancer subtypes and comparison with invasive carcinoma of no special type

Deep Learning for Distinguishing Mucinous Breast Carcinoma From Fibroadenoma on Ultrasound

PURPOSE

Mucinous breast carcinoma (MBC) tends to be misdiagnosed as fibroadenomas (FA) due to its benign imaging characteristics. We aimed to develop a deep learning (DL) model to differentiate MBC and FA based on ultrasound (US) images. The model could contribute to the diagnosis of MBC for radiologists.

METHODS

In this retrospective study, 884 eligible patients (700 FA patients and 184 MBC patients) with 2257 US images were enrolled. The images were randomly divided into a training set (n = 1805 images) and a test set (n = 452 images) in a ratio of 8:2. First, we used the training set to establish DL model, DL+ age-cutoff model and DL+ age-tree model. Then, we compared the diagnostic performance of three models to get the optimal model. Finally, we evaluated the diagnostic performance of radiologists (4 junior and 4 senior radiologists) with and without the assistance of the optimal model in the test set.

RESULTS

The DL+ age-tree model yielded higher areas under the receiver operating characteristic curve (AUC) than DL model and DL+ age-cutoff model (0.945 vs. 0.835, P < .001; 0.945 vs. 0.931, P < .001, respectively). With the assistance of DL+ age-tree model, both junior and senior radiologists' AUC had significant improvement (0.746-0.818, P = .010, 0.827-0.860, P = .005, respectively).

CONCLUSIONS

The DL+ age-tree model based on US images and age showed excellent performance in the differentiation of MBC and FA. Moreover, it can effectively improve the performance of radiologists with different degrees of experience that may contribute to reducing the misdiagnosis of MBC.

A prognostic nomogram for patients with HR+ mucinous breast carcinoma based on the SEER database and a Chinese cohort study

Purpose

The study aimed to develop a nomogram model for individual prognosis prediction in patients with hormone receptors positive (HR+) mucinous breast carcinoma (MBC) and assess the value of neoadjuvant chemotherapy (NAC) in this context.

Methods

A total of 6,850 HR+ MBC patients from the SEER database were identified and randomly (in a 7:3 ratio) divided into training cohorts and internal validation cohorts. 77 patients were enrolled from the Chongqing University Cancer Hospital as the external validation cohort. Independent risk factors affecting overall survival (OS) were selected using univariate and multivariate Cox regression analysis, and nomogram models were constructed and validated. A propensity score matching (PSM) approach was used in the exploration of the value of NAC versus adjuvant chemocherapy (AC) for long-term prognosis in HR+ MBC patients.

Results

Multivariate Cox regression analysis showed 8 independent prognostic factors: age, race, marital status, tumor size, distant metastasis, surgery, radiotherapy, and chemotherapy. The constructed nomogram model based on these 8 factors exhibited good consistency and accuracy. In the training group, internal validation group and external validation group, the high-risk groups demonstrated worse OS (p<0.0001). Subgroup analysis revealed that NAC had no impact on OS (p = 0.18), or cancer specific survival (CSS) (p = 0.26) compared with AC after PSM.

Conclusions

The established nomogram model provides an accurate prognostic prediction for HR+ MBC patients. NAC does not confer long-term survival benefits compared to AC. These findings provide a novel approach for prognostic prediction and clinical practice.

Special Types of Breast Cancer: Clinical Behavior and Radiological Appearance

Breast cancer is a complex disease that includes entities with different characteristics, behaviors, and responses to treatment. Breast cancers are categorized into subgroups based on histological type and grade, and these subgroups affect clinical presentation and oncological outcomes. The subgroup of "special types" encompasses all those breast cancers with insufficient features to belong to the subgroup "invasive ductal carcinoma not otherwise specified". These cancers account for around 25% of all cases, some of them having a relatively good prognosis despite high histological grade. The purpose of this paper is to review and illustrate the radiological appearance of each special type, highlighting insights and pitfalls to guide breast radiologists in their routine work.

Histopathological Profile of Different Breast Lesions: A Single-Center Observational Study

OBJECTIVE

To describe the histopathological pattern of different breast lesions among tissue specimens sent to our laboratory.

METHOD

A record-based study using a retrospective review of 255 histologically diagnosed breast biopsy reports in the histopathology department of authors from December 2016 to November 2021 was conducted. The specimens were collected from core biopsy, lumpectomy, and mastectomy. All data obtained were analyzed using the Statistical Package for the Social Sciences (SPSS) version 28 (IBM SPSS Statistics, Armonk, NY). Then, the findings were presented using text, tables, and charts.

RESULT

A total of 255 breast lesions were analyzed in this study. Most of the cases were benign (58.8%), followed by inflammatory lesions (21.6%), and malignant (19.6%). Fibroadenoma was the most prevalent benign lesion (36.7%), and most of the patients (70.9%) were in the age group of 20-39 years old. The most common inflammatory lesion was granulomatous mastitis (56.4%), and most of the cases were diagnosed in the age group of 30-39 years old. Invasive ductal carcinoma (IDC) was the most encountered histological type of carcinoma (62%). Of the malignant cases, 52% were diagnosed before the age of 50 years. Among these 50 cases, grade 2 was the most prevalent one (46%).

CONCLUSION

Benign breast lesions are more common than malignant breast lesions, and fibroadenoma is the most common benign subtype. Granulomatous mastitis is the most prevalent inflammatory breast lesion. About two-thirds of malignant cases are non-Arab. Invasive ductal carcinoma with no special type (NST) is the most common malignant subtype.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

Spectrum of Mucin-containing Lesions of the Breast: Multimodality Imaging Review with Pathologic Correlation

Mucin-containing lesions of the breast encompass a wide range of benign and malignant processes. The spectrum of histologic findings includes incidental mucus-filled benign cysts or ducts, mucocele-like lesions (MLLs), mucin-producing ductal carcinoma in situ, and invasive mucinous carcinoma. MLL is characterized by the presence of mucin-containing cysts that are typically associated with extravasated stromal mucin. MLL is often benign but can be associated with epithelial atypia or malignancy. Mucinous carcinoma represents the malignant end of the spectrum of mucinous lesions of the breast. Evidence-based literature supports a conservative approach for benign MLLs without associated atypia or malignancy, reserving excision for those lesions exhibiting such pathologic features. The most common imaging finding for MLL is microcalcifications at mammography. No specific imaging feature is predictive of malignant outcome at surgical excision. Invasive mucinous carcinoma is a heterogeneous breast tumor subtype, as defined according to the World Health Organization criteria. Mucinous carcinomas are categorized into pure (>90% mucinous component) or mixed (10%-90% mucinous component) subtypes. Pure mucinous carcinomas are generally associated with excellent prognosis and survival, with a few exceptions. Mixed mucinous carcinomas do not have the same favorable prognosis and instead behave similarly to invasive breast carcinomas of no special type. Characteristic diagnostic imaging features can be identified for mucinous carcinoma based on its mucinous and nonmucinous contents. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

On Ultrasonographic Features of Mucinous Carcinoma with Micropapillary Pattern

Objective

To describe the sonographic features of pure mucinous carcinoma with micropapillary pattern (MUMPC) and compare with different pathological type of mucinous breast carcinoma.

Methods

Subjects were retrospectively reviewed at Suzhou Municipal Hospital from January 2015 to June 2019. Sonographic features of 49 cases (9 MUMPC, 19cPMBC, and 21 MMBC) pathologically confirmed MBC were recorded according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon. The differences in sonographic features among different type of mucinous breast carcinoma were discussed, including clinical features and sonographic features, shape, lesion boundary, peripheral hyperechoic ring, echo pattern, posterior acoustic feature, thickness peripheral hyperechoic area, and blood flow.

Results

All MUMPC had no lymph node metastasis (88.9%, 8/9), and most of the MUMPC showed no thickness peripheral hyperechoic area (88.9%, 8/9) and blood flow (55.6%, 5/9) within the tumor. Furthermore, MUMPC had mixed cystic and solid components (33.3%, 3/9) and solid echoic (66.7%, 6/9) structures, with regular shape (66.7%, 6/9) and peripheral hyperechoic ring (66.7%, 6/9). Seven cases of the MUMPC showed circumscribed margin (77.8%, 7/9), and there was significant difference among the three groups (p < 0.05). In addition, there were 7 cases (77.8%, 7/9) of MUMPC tumor ≤2cm, which was significantly different from cPMBC (26.3%, 5/19) and MMBC (28.6%, 6/21) (p < 0.05). There was no significant difference in ultrasonographic features of MBC with different sizes when stratified by tumor size (p > 0.05).

Conclusion

Most of the MUMPC showed a circumscribed margin, peripheral hyperechoic ring, and without lymph node metastasis and thickness peripheral hyperechoic area. However, it is challenging to distinguish MUMPC from PMBC and MMBC on ultrasound. Future research should focus on developing novel analysis methods for ultrasound imaging, conducting studies with larger sample sizes and diverse population groups.

Pure Mucinous Carcinoma of the Breast: Radiologic-Pathologic Correlation

Mucinous carcinoma (MC) of the breast is a rare, specialized subtype of invasive breast carcinoma (IBC) accounting for approximately 1% to 4% of all primary breast malignancies. Mucinous carcinoma occurs predominantly in patients who are postmenopausal or elderly. It is usually detected on screening mammography, but occasionally the patient may present with a palpable mass. The most common mammographic appearance is an equal to high density, oval or round mass with circumscribed or indistinct margins; MC can mimic a benign lesion. Histologically, MC is a well-differentiated cancer characterized by pools of mucin around neoplastic cells. Depending on mucin content, the tumor is classified as pure (≥90% mucin) or mixed (>10% and <90% mucin). Pure MCs (PMCs) are of low or intermediate nuclear grade, and the vast majority are hormone receptor-positive and human epidermal growth factor-2 receptor-negative (luminal A subtype). Pure MCs may be classified as hypocellular (type A) or hypercellular (type B) and have a lower rate of axillary lymph node involvement and more favorable prognosis than IBCs, no special type. The purpose of this article is to review the clinical features, imaging appearances, associated histopathology, and management of PMC.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Advanced magnetic resonance imaging of mixed mucinous breast cancer: A case report

Well-differentiated adenocarcinoma, a rare subtype of infiltrating ductal carcinoma, is a kind of mucinous cancer of the breast. It accounts for around 2% of all invasive breast cancers. The average age of presentation is 65-70 years, whereas women under the age of 35 account for 1% of cases. They are classified as pure or mixed carcinomas depending on the amount of mucin they include; knowing the difference is crucial for prognosis and therapy. Despite the lack of sufficient proof, the primary therapy for breast cancer is still surgery. Special forms of breast cancer are still being treated, although this is still a contentious topic. In this article, we intended to present a case of a mixed mucinous carcinoma in a 52-year-old female who was assessed by advanced magnetic resonance imaging.

Gross Cystic Disease Fluid Protein-15 (GCDFP-15) Expression Characterizes Breast Mucinous Carcinomas in Older Women

The predominant histological subtype of breast mucinous carcinoma in older women is type B (hypercellular type), and, in younger women, it is type A (hypocellular type). The characteristics of mucinous carcinomas of the same histological subtype may differ between older and younger women. This study aims to systematically clarify the pathological/immunohistochemical features of mucinous carcinomas. A total of 21 surgical cases of mucinous carcinoma (type A/B: 9/12 cases) in the older group (≥65 years) and 16 cases (type A/B: 14/2 cases) in the younger group (≤55 years) (n = 37) were included. Gross cystic disease fluid protein-15 (GCDFP-15) and eight other markers were used for immunostaining. The GCDFP-15-positive rate in the older group was high regardless of the histological subtype (type A, 77.8%; type B, 91.7%). The GCDFP-15 positivity in the older group was significantly higher than that in the younger group (p < 0.001 for Allred score). Among type A, GCDFP-15 positivity was significantly higher in the older group than in the younger group (p = 0.042 for the Allred score and p = 0.007 for the positivity rate). The present results suggest that GCDFP-15 expression characterizes mucinous carcinomas in older women.

Metastasis of the Mucionous adenocarcinoma of breast to the mandibular gingiva: Rare case report

INTRODUCTION

Mucinous adenocarcinoma (MAC) is a rare type of cancer in which more than 50% of the tumor is composed of extracellular mucin and malignant epithelial cells. MACs account for only 1.8% of all breast cancer cases. Most breast cancers present as localized diseases and are well-differentiated. Breast MAC has a better 5- and 10-year survival rate than ductal and lobular carcinomas. Distant metastasis in breast MAC is rare, especially in the oral cavity. Only 1% of all oral malignancies present with metastases to the oral cavity. The bony structures are more involved than the soft tissues. Involvement of the oral soft tissue is rare, accounting for less than 0.1% of oral metastases.

CASE DESCRIPTION

This report describes a rare case of mucinous breast adenocarcinoma with metastasis to the mandibular molar region. Diagnosis was established based on anamnesis, clinical presentation, tumor biopsy, computed tomography, mammography, and core biopsy of the breast tumor. The patient was sent to the oncology committee for breast disease where chemotherapy was indicated.

DISCUSSION

The clinical presentation of oral metastasis is not pathognomonic, and pyogenic granuloma, periodontal abscesses, sarcomas, and squamous carcinoma must be considered in the differential diagnosis. This is a rare case of oral metastasis of breast MAC, which was indicated for detection of the primary tumor.

Correlation Analysis of Pathological Features and Axillary Lymph Node Metastasis in Patients with Invasive Breast Cancer

Objective

To investigate the risk factors of axillary lymph node metastasis in patients with invasive breast cancer.

Methods

This study retrospectively included 122 cases of invasive breast cancer patients admitted to the First Medical Center of PLA General Hospital from January 2019 to September 2020. According to postoperative pathological results, axillary lymph node metastasis was divided into axillary lymph node metastasis (ALNM) group (n =40) and non-axillary lymph node metastasis (NALNM) group (n =82). General demographic information was collected and compared between the two groups. Collected pathological results included lymphovascular invasion (LVI) and the expression of estrogen receptor (ER), progestogen receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 detected by immunohistochemistry. Imaging parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) including apparent diffusion coefficient (ADC), early enhanced rate, and time-intensity curve (TIC) were also included into univariate analysis. The variables with differences between the two groups were compared by univariate analysis, and the related factors of axillary lymph node metastasis were analyzed by logistic regression model.

Results

There was no significant difference in general demographic information between the two groups. No significant differences were found in the positive rates of HER-2, ER, PR, Ki-67, pathological types, and clavicular lymph node metastasis and skin chest wall invasion between the two groups (P > 0.05). The proportion of LVI in ALNM group was significantly higher than that in NALNM group (37.50% vs. 6.10%, P < 0.001). The proportion of breast cancer on the left side in the ALNM group was higher than that in the NALNM group, and the difference was statistically significant (70.00% vs. 47.56%, P = 0.019). There were no significant differences in the imaging parameters obtained by DCE-MRI between the two groups. Binary logistics regression analysis showed that LVI (OR =12.258, 95% CI =3.681-40.812, P < 0.001) and left breast cancer (OR =3.598, 95% CI =1.404-9.219, P = 0.008) were risk factors for axillary lymph node metastasis in patients with invasive breast cancer.

Conclusion

The formation of vascular tumor thrombi in breast cancer tissue and left breast cancer are risk factors for axillary lymph node metastasis in invasive breast cancer and might be helpful for preoperative detailed assessment of the patient's condition.

A Novel Combined Nomogram Model for Predicting the Pathological Complete Response to Neoadjuvant Chemotherapy in Invasive Breast Carcinoma of No Specific Type: Real-World Study

Objective

To explore the value of a predictive model combining the multiparametric magnetic resonance imaging (mpMRI) radiomics score (RAD-score), clinicopathologic features, and morphologic features for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in invasive breast carcinoma of no specific type (IBC-NST).

Methods

We enrolled, retrospectively and consecutively, 206 women with IBC-NST who underwent surgery after NAC and obtained pathological results from August 2018 to October 2021. Four RAD-scores were constructed for predicting the pCR based on fat-suppression T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), contrast-enhanced T1-weighted imaging (T1WI+C) and their combination, which was called mpMRI. The best RAD-score was combined with clinicopathologic and morphologic features to establish a nomogram model through binary logistic regression. The predictive performance of the nomogram was evaluated using the area under receiver operator characteristic (ROC) curve (AUC) and calibration curve. The clinical net benefit of the model was evaluated using decision curve analysis (DCA).

Results

The mpMRI RAD-score had the highest diagnostic performance, with AUC of 0.848 among the four RAD-scores. T stage, human epidermal growth factor receptor-2 (HER2) status, RAD-score, and roundness were independent factors for predicting the pCR (P < 0.05 for all). The combined nomogram model based on these factors achieved AUCs of 0.930 and 0.895 in the training cohort and validation cohort, respectively, higher than other models (P < 0.05 for all). The calibration curve showed that the predicted probabilities of the nomogram were in good agreement with the actual probabilities, and DCA indicated that it provided more net benefit than the treat-none or treat-all scheme by decision curve analysis in both training and validation datasets.

Conclusion

The combined nomogram model based on the mpMRI RAD-score combined with clinicopathologic and morphologic features may improve the predictive performance for the pCR of NAC in patients with IBC-NST.

Overall Survival in Patients with Mucinous Carcinoma of Breast: A Population-Based Study

Purpose

Mucinous carcinoma of the breast (MCB) is a rare malignant tumour. Therefore, it is urgent to establish a survival prediction model for MCB patients.

Methods

Clinicopathological and follow-up data of MCB patients diagnosed between 2010 and 2015 were retrieved from the Surveillance, Epidemiology, and End Result (SEER) database. The significant factors were screened out and generated Kaplan-Meier (K-M) curves for each prognostic factor. Additionally, these factors were then utilized to build a nomogram for predicting 3-, 4-, and 5-year overall survival (OS) of MCB patients. The nomogram was evaluated using calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

Results

Moreover, a total of 4326 MCB patients were retrieved. Age, American Joint Committee on Cancer (AJCC) stage, surgery, radiotherapy and bone metastasis were identified as independently prognosis factors for OS. The corresponding areas under the ROC curves (AUCs) of the nomogram at 3, 4 and 5 years in the training and validation set were 0.770, 0.788, 0.805, 0.778, 0.797, and 0.802, respectively. The calibration curves and DCA revealed that the prediction model had an excellent performance. Finally, the risk stratification system confirmed that the powerful role of the nomogram in distinguishing results and risk stratification.

Conclusion

Briefly, the nomogram incorporating various clinicopathological indicators was established for MCB patients and may facilitate clinical decision-making.

Mucinous carcinoma in an octogenarian: Treatment and management of breast cancer in the elderly

Age is a risk factor for breast cancer in females, and over 60% of female breast cancer deaths occur in those aged 65 and older. As the population in the United States continues to age, it is expected that there will be a commensurate increase in the number of women diagnosed with breast cancer, making understanding of effective treatment and management of breast cancer in the elderly essential.

Here, we review the treatment and management of early breast cancer in the elderly. We report a case of invasive mucinous carcinoma in an 80-year-old female detected on routine clinical breast exam by her primary care physician. Mucinous carcinoma of the breast is a type of rare invasive neoplasm that generally carries an excellent prognosis. Following an ultrasound-guided core needle biopsy, a right breast needle localized segmental mastectomy was performed and the patient was prescribed an aromatase inhibitor for hormone-receptor positive tumor. After a follow-up of 8 years, the patient remains free of recurrence or metastasis and vibrantly living meaningful daily life.