Incidental Bilateral Ductal Carcinoma In Situ (DCIS) in Excisional Surgery for Gynecomastia.

Male breast cancer is a rare disease, and it is important to have a high index of suspicion in patients presenting with breast symptoms, such as a breast mass or nipple discharge. Most male patients who are diagnosed with breast cancer present with breast complaints and/or a strong family history of cancer. Here, we will present a 47-year-old male patient who was diagnosed with bilateral ductal carcinoma in situ during a routine gynecomastia surgery after massive weight loss. This case demonstrates the importance of sending breast tissue specimens for pathology, especially in a male patient.

Comparison of locoregional recurrence risk among nipple-sparing mastectomy, skin-sparing mastectomy, and simple mastectomy in patients with ductal carcinoma in situ: a single-center study.

BACKGROUND: In invasive breast cancer, there are no differences among the mid- and long-term oncological safety results of nipple-sparing mastectomy (NSM), skin-sparing mastectomy (SSM), and simple mastectomy (SM). There are several reports comparing NSM and SSM with SM in the context of ductal carcinoma in situ (DCIS); however, the eligibility criteria vary among institutions, and there are no reports that compare all three surgical methods simultaneously within the same institution. This study aimed to compare the local recurrence and survival rates of the three techniques (NSM, SSM, and SM) in Japanese patients undergoing mastectomy for DCIS. METHODS: Patients undergoing NSM, SSM, or SM at our institution between 2006 and 2015 were identified, and their outcomes were analyzed. RESULTS: The mean follow-up period was 80.4 months (standard deviation [SD]: 37.1 months). NSM was performed in 152 cases, SSM in 49, and SM in 44. Five of 245 patients developed local recurrences. Four of these patients had invasive cancer. The primary endpoints of 5-year cumulative local recurrence were 2.4% (95% confidence interval [CI]: 0.0-5.0) for NSM, 2.2% (95% CI: 0.0-6.3) for SSM, and 0% (95% CI: 0.0-0.0) for SM. There were no significant differences among the 5-year local recurrence rates. CONCLUSIONS: In this single-center, retrospective study, the oncological safety of SSM and NSM for DCIS was comparable to that of conventional SM.

Long-term Outcome After Helical Tomotherapy Following Breast Conserving Surgery for Ductal Carcinoma In Situ.

Background: This retrospective study aimed to investigate the outcomes and adverse events (AEs) associated with adjuvant radiotherapy with helical tomotherapy (hT) after breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS). Methods: Twenty-eight patients with DCIS underwent postoperative hT between 2011 and 2020. hT was chosen since it provided optimal target coverage and tolerable organ-at-risk doses to the lungs and heart when tangential 3-dimensional conformal radiotherapy (3D-CRT) was presumed to provide unfavorable dosimetry. The median total (single) dose was 50.4 Gy (1.8 Gy). The median time between BCS and the start of hT was 5 weeks (range, 4-38 weeks). Statistical analysis included local recurrence-free survival, overall survival (OS), and secondary cancer-free survival. AEs were classified according to the Common Toxicity Criteria for Adverse Events, version 5. Results: The patients' median age was 58 years. The median follow-up period was 61 months (range, 3-123 months). The 1-, 3-, and 5-year OS rates were 100% each. None of the patients developed secondary cancer, local recurrence, or invasive breast cancer during follow-up. The most common acute AEs were dermatitis (n = 27), fatigue (n = 4), hyperpigmentation (n = 3), and thrombocytopenia (n = 4). The late AE primarily included surgical scars (n = 7) and hyperpigmentation (n = 5). None of the patients experienced acute or late AEs > grade 3. The mean conformity and homogeneity indices were 0.9 (range, 0.86-0.96) and 0.056 (range, 0.05-0.06), respectively. Conclusion: hT after BCS for DCIS is a feasible and safe form of adjuvant radiotherapy for patients in whom 3D-CRT is contraindicated due to unfavorable dosimetry. During follow-up, there were no recurrences, invasive breast cancer diagnoses, or secondary cancers, while the adverse effects were mild.

The impact of extensive intraductal component (EIC) on the genomic risk of recurrence in early hormone receptor positive breast cancer.

BACKGROUND: Early invasive ductal carcinoma (IDC) breast cancer often presents with a coexisting ductal carcinoma in situ (DCIS) component, while about 5 % of cases present with an extensive (>25 %) intraductal component (EIC). The impact of EIC on the genomic risk of recurrence is unclear. METHODS: Patients with early hormone receptor-positive HER2neu-negative (HR + HER2-) IDC breast cancer and a known OncotypeDX Breast Recurrence Score® (RS) who underwent breast surgery at our institute were included. Using a rule-based text-analysis algorithm, we analyzed pathological reports and categorized patients into three groups: EIC, non-extensive DCIS (DCIS-L), and pure-IDC (NO-DCIS). Genomic risk was determined using OncotypeDX RS. RESULTS: A total of 33 (4.6 %) EIC cases, 377 (57.2 %) DCIS-L cases and 307 (42.8 %) NO-DCIS cases were identified. Patients in the EIC group were younger and had lower tumor grades than other groups. The distribution of genomic risk varied between the groups, with EIC tumors significantly less likely to have a high RS (>25) compared to DCIS-L and No-DCIS tumors (3 % vs 20 % and 20 %, respectively; p = 0.03). When adjusted to age, tumor size, grade and LNs involvement, both DCIS-L and NO-DCIS groups were significantly correlated with a higher probability of high RS compared to the EIC group (OR 12.3 and OR 13.1, respectively; p < 0.02). Moreover, patients with EIC had a lower likelihood for adjuvant chemotherapy recommendation. CONCLUSIONS: In early HR + HER2- IDC, an EIC correlates with a reduced genomic recurrence risk. The impact on genomic risk seems to be influenced by the extent, not merely the presence, of DCIS.

Eco-evolutionary Guided Pathomic Analysis to Predict DCIS Upstaging.

Cancers evolve in a dynamic ecosystem. Thus, characterizing cancer's ecological dynamics is crucial to understanding cancer evolution and can lead to discovering novel biomarkers to predict disease progression. Ductal carcinoma in situ (DCIS) is an early-stage breast cancer characterized by abnormal epithelial cell growth confined within the milk ducts. Although there has been extensive research on genetic and epigenetic causes of breast carcinogenesis, none of these studies have successfully identified a biomarker for the progression and/or upstaging of DCIS. In this study, we show that ecological habitat analysis of hypoxia and acidosis biomarkers can significantly improve prediction of DCIS upstaging. First, we developed a novel eco-evolutionary designed approach to define habitats in the tumor intra-ductal microenvironment based on oxygen diffusion distance in our DCIS cohort of 84 patients. Then, we identify cancer cells with metabolic phenotypes attributed to their habitat conditions, such as the expression of CA9 indicating hypoxia responding phenotype, and LAMP2b indicating a hypoxia-induced acid adaptation. Traditionally these markers have shown limited predictive capabilities for DCIS upstaging, if any. However, when analyzed from an ecological perspective, their power to differentiate between indolent and upstaged DCIS increased significantly. Second, using eco-evolutionary guided computational and digital pathology techniques, we discovered distinct spatial patterns of these biomarkers and used the distribution of such patterns to predict patient upstaging. The patterns were characterized by both cellular features and spatial features. With a 5-fold validation on the biopsy cohort, we trained a random forest classifier to achieve the area under curve(AUC) of 0.74. Our results affirm the importance of using eco-evolutionary-designed approaches in biomarkers discovery studies in the era of digital pathology by demonstrating the role of eco-evolution dynamics in predicting cancer progression.

Ductal Carcinoma In Situ.

In breast cancer (BC) pathogenesis models, normal cells acquire somatic mutations and there is a stepwise progression from high-risk lesions and ductal carcinoma in situ to invasive cancer. The precancer biology of mammary tissue warrants better characterization to understand how different BC subtypes emerge. Primary methods for BC prevention or risk reduction include lifestyle changes, surgery, and chemoprevention. Surgical intervention for BC prevention involves risk-reducing prophylactic mastectomy, typically performed either synchronously with the treatment of a primary tumor or as a bilateral procedure in high-risk women. Chemoprevention with endocrine therapy carries adherence-limiting toxicity.

Upper Extremity Deep Vein Thrombosis in the Setting of Ductal Carcinoma In Situ: A Case Report.

Deep vein thrombosis (DVT) is a type of venous thromboembolism that usually involves a clot formation in the deep veins of the lower extremities. Its formation is linked to Virchow's Triad which factors in venous stasis, endothelial damage, and hypercoagulability. Venous stasis is the primary factor contributing to the development of DVT and it refers to varicosity, external pressure placed on the extremity, or immobilization due to bed rest or long flights. Clinical presentation of DVT depends on the extent and location of the thrombus with common signs including localized swelling, pain, warmth, and edema. The Wells criteria are typically applied to assess the likelihood of thrombus formation alongside D-dimer assay, ultrasound, or CT imaging. As previously mentioned, these mostly occur in the lower extremities. However, upper extremity DVT has been noted and has been linked to inherited issues with coagulation and autoimmune disorders. This report will discuss a case of left-arm DVT in a patient who underwent bilateral mastectomy with sentinel node biopsy for a diagnosis of ductal carcinoma in situ in the left breast.

Is the Number or Proximity of Margins Less than 2 mm Associated with an Increased Mastectomy Rate in Patients Attempting Breast Conservation Therapy for Ductal Carcinoma In Situ?

BACKGROUND: Consensus guidelines recommend ≥ 2 mm margins in patients undergoing partial mastectomy (PM) for ductal carcinoma in situ (DCIS). It is unknown whether the number or proximity of margins less than 2 mm is associated with an increased mastectomy rate in patients attempting breast conservation therapy (BCT) for DCIS. The aim of this study is to examine this relationship. PATIENTS AND METHODS: An institutional database review identified 208 patients with DCIS who underwent PM at a tertiary referral center and community hospitals from July 2020 to June 2023. Patients with a history of breast cancer, previous surgery for breast cancer, ipsilateral invasive carcinoma, papillary carcinoma, Paget's disease, more lobular carcinoma in situ (LCIS) than DCIS present, initial mastectomy, no DCIS present, routine shave margins (of all vectors), and ≥ 2 mm margins of all six vectors were excluded. Selective intraoperative margin re-excisions were included. RESULTS: A total of 208 patients who met inclusion criteria were retrospectively reviewed. 122 (25%) had one close/positive (< 2 mm) margin and 86 (18%) had two or more close/positive margins. Of the patients with one close/positive margin, 7% (9/122) eventually underwent mastectomy. Of the patients with two or more close/positive margins, 20% (17/86) eventually underwent mastectomy. Overall, no patients with opposing margins underwent mastectomy. CONCLUSIONS: Patients undergoing PM for DCIS have a mastectomy rate that is increased threefold, with two or more close/positive margins at initial PM, when compared with those with only one close/positive margin. The presence of opposing close/positive margins at initial PM did not increase the mastectomy rate and most were cleared with re-excision.

Impact of surgical types on overall survival in patients with ductal carcinoma in situ: an analysis based on the SEER database.

Background: Breast cancer, as one of the most common malignancies among women globally, presents a concerning incidence rate, underscoring the importance of addressing the treatment of its precursor lesion, ductal carcinoma in situ (DCIS). Treatment decisions for DCIS, involving the balance between breast-conserving surgery (BCS) and mastectomy, remain an area requiring further investigation. This study aimed to compare influence of different surgical types on overall survival (OS) of patients with DCIS and identify specific subgroups with improved OS to develop an effective survival nomogram for patients. Methods: Patient data from the Surveillance, Epidemiology, and End Results (SEER) database for DCIS cohort from 2010 to 2020 were retrieved. Kaplan-Meier (K-M) survival curves were utilized to compare prognostic OS of patients with different surgical methods. Cox regression analysis was employed to determine prognostic factors and establish a nomogram to predict 3-, 5-, and 10-year survival rates. The model was confirmed by Concordance Index (C-index), calibration curves, and receiver operating characteristic (ROC) curves. Results: A total of 71,675 patients with DCIS were included. Patients who underwent subcutaneous mastectomy (SM) demonstrated the best OS compared to other surgical types. Additionally, adjuvant radiotherapy or chemotherapy in combination with surgery significantly improved OS compared to surgery alone. Among DCIS patients aged ≤74 years, those who underwent SM benefited the most in terms of OS, while in the age group of 63-74 years, patients who underwent BCS had significantly higher OS than those who underwent total (simple) mastectomy (TM)/modified radical mastectomy (MRM). Multiple factors were associated with improved OS in DCIS patients, and these factors were integrated into the nomogram to establish OS predictions. The C-index, calibration curves, and ROC curves indicated that the nomogram was suitable for assessing patient prognosis. Conclusions: This study demonstrated that SM treatment yielded the best survival rates for DCIS patients, providing important guidance for future surgical decision-making. Moreover, identifying multiple independent factors related to survival and establishing reliable survival nomograms can assist physicians in developing personalized treatment plans and prolonging patient survival.

Adherence to guideline recommendations for follow-up in patients with DCIS at a large teaching hospital in the Netherlands.

PURPOSE: Ductal-carcinoma in situ (DCIS) is a pre-invasive form of breast cancer with good prognosis. Follow-up guidelines in the Netherlands are currently the same as for invasive breast cancer. Due to fear of invasive breast cancer or recurrence, it is hypothesized that follow-up for DCIS after treatment is more intense in practice resulting in potentially unnecessary high costs. This study investigates the follow-up in practice for patients with DCIS compared to the recommendations in order to inform clinicians and policy makers how to utilize these guidelines. METHODS: Patients diagnosed with pure DCIS between 2004 and 2014 were followed up until 2018. Information on duration and frequency of follow-up visits, reasons and decision makers for shortening, and prolonging follow-up was collected. Prolonged follow-up was defined as deviation from the Dutch guideline: more than 5 years of follow-up and older than 60 years. RESULTS: Of the 227 patients the mean number of visits per year was 1.4 and mean years of follow-up was 6.0. Thirty-three percent had prolonged follow-up and 26% shorter follow-up than recommended. A majority (78%) of decision for prolonged follow-up was being made by clinicians. CONCLUSION: Follow-up duration is in almost half of patients with DCIS according to guidelines and with most prolonged follow-up only up to a year longer than recommended. In most cases suspicious findings and the timing of the population screening program appeared to cause prolonged follow-up. If accepted by patients and clinicians, future DCIS specific guidelines should address these reasons and tailor to the individual risks.

A Retrospective Analysis of Breast Cancer Presentation Among Young and Older Women in an Indian Cohort of 70 Patients.

Introduction In females, carcinoma of the breast is a common malignancy. Disease management can be challenging for the treating clinician if the condition is presented in a locally advanced stage. Clinical presentation of a disease in a defined area provides a comprehensive map to target the at-risk population efficiently and select the appropriate intervention accordingly. In this retrospective study, we analyzed different factors that can affect breast carcinoma outcomes by assessing patients for a specific period of one year. Methods This is a retrospective study of carcinoma of breast patients and was conducted between 2017 and 2018. Results We reported a 25.83% incidence of breast cancer during the study period. A painful breast lump was present in 54.2% of patients, axillary nodes were present in 50% of patients, ulcers were present in 10% of patients, and nipple discharge was present in 8.5% of patients. According to the side and quadrant of involvement, the right side was the most common site of involvement in 55.7% of patients, and the upper outer quadrant was the most common quadrant involved in 61.4% of patients. The most familiar stage of the presentation was stage II, presented in 45.7% of patients. The most common histology was infiltrating ductal carcinoma, presented in 85.7% of patients. Conclusions This retrospective cohort study shows that carcinoma of the breast is a predominant malignancy among middle-aged females in developing countries such as India. This predominance is due to unawareness regarding disease symptoms and the fear of diagnosed malignancy during the investigation of symptoms. Early detection by screening and intervention at an early stage is the core of treatment success in this malignant disease. However, it is still challenging to apply screening as a tool to pick up early malignant disease in developing countries like India.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics.

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Mammographically and sonographically occult male DCIS seen only on breast MRI.

Male breast cancer is a rare entity consisting of less than 1% of all breast cancer diagnoses, in which pure ductal carcinoma in situ (DCIS) without an invasive component accounts for approximately 10% of these diagnoses. Early diagnosis and appropriate management are essential to ensure favorable outcomes. We present a rare case of mammographically and sonographically occult pure DCIS in a male patient presenting with unilateral bloody nipple discharge, highlighting imaging features and the potential utility of breast MRI that aided diagnosis and management.

Ductal carcinoma in situ and cause-specific mortality among younger and older postmenopausal women: the Women's Health Initiative.

BACKGROUND: Whether DCIS is associated with higher breast cancer-specific and all-cause mortality is unclear with few studies in older women. Therefore, we examined DCIS and breast cancer-specific, cardiovascular (CVD)-specific, and all-cause mortality among Women's Health Initiative (WHI) Clinical Trial participants overall and by age (< 70 versus ≥ 70 years). METHODS: Of 68,132 WHI participants, included were 781 postmenopausal women with incident DCIS and 781 matched controls. Serial screening mammography was mandated with high adherence. DCIS cases were confirmed by central medical record review. Adjusted multivariable Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI). Kaplan Meier (KM) plots were used to assess 10-year and 20-year mortality rates. RESULTS: After 20.3 years total, and 13.2 years median post-diagnosis follow-up, compared to controls, DCIS was associated with higher breast cancer-specific mortality (HR 3.29; CI = 1.32-8.22, P = 0.01). The absolute difference in 20-year breast cancer mortality was 1.2% without DCIS and 3.4% after DCIS, log-rank P = 0.026. Findings were similar by age (< 70 versus ≥ 70 years) with no interaction (P interaction = 0.80). Incident DCIS was not associated with CVD-specific mortality (HR 0.77; CI-0.54-1.09, P = 0.14) or with all-cause mortality (HR 0.96; CI = 0.80-1.16, P = 0.68) with similar findings by age. CONCLUSIONS: In postmenopausal women, incident DCIS was associated with over three-fold higher breast cancer-specific mortality, with similar findings in younger and older postmenopausal women. These finding suggest caution in using age to adjust DCIS clinical management or research strategies.

Is overexpression of CD163 and CD47 in tumour cells of breast carcinoma implicated in the recruitment of tumour-associated macrophages (TAMs) in tumour microenvironment? immunohistochemical prognostic study.

BACKGROUND: Now, targeted therapy and immunotherapy are promoted. tumour -Associated Macrophages (TAMs) are an essential component of immune-response in breast cancer(BC) with prognostic controversy. Additionally, their recruiting factors are still obscure. Purpose:This study aimed to evaluate the prognostic significance of CD163 and CD47 in BC of No Special Type (BC-NST) and to explore their suggested role in recruiting TAMs. MATERIAL AND METHODS: This immunohistochemical study was conducted on 91 archival specimens of breast cases. Immunoreactivity scores were correlated with TAMs density, clinicopathological data, and survival. RESULTS: Revealed the highest CD163 expression was detected in the pure DCIS group (p = 0.016), while the highest CD47 expression and high TAMs density were reported in the invasive group (p = 0.008, and p = 0.002 respectively) followed by the DCIS group. In IC-NSTs the CD163 and CD47 scores were associated with poor prognostic parameters like(high grade, advanced stage, distant metastasis, ER negativity,Ki67 index, post-surgical chemotherapy, poor NPI group, high mitotic count, dense infiltration of TAMs, shorter OS). Also, CD47 was associated with the dens infiltration of TAMs in DCIS (p = 0.001). There was a significant correlation between tumour cell expression of CD163 and CD47 in IC-NSTs and DCIS (p = 0.002 and p = 0.009 respectively). CONCLUSIONS: High CD163 and CD47 expressions in both DCIS andIBC are intimately associated, significantly associated with poor prognosis and are important provoking factors of TAMs.

Use of beta-blockers in patients with ductal carcinoma in situ and risk of invasive breast cancer recurrence: a Swedish retrospective cohort study.

BACKGROUND: Retrospective observational studies suggest a potential role of beta-blockers as a protective strategy against progression and metastasis in invasive breast cancer. In this context, we investigated the impact of beta-blocker exposure on risk for progression to invasive breast cancer after diagnosis of ductal cancer in situ (DCIS). METHODS: The retrospective study population included 2535 women diagnosed with pure DCIS between 2006 and2012 in three healthcare regions in SwedenExposure to beta-blocker was quantified using a time-varying percentage of days with medication available. The absolute risk was quantified using cumulative incidence functions and cox models were applied to quantify the association between beta-blocker exposure and time from DCIS diagnosis to invasive breast cancer, accounting for delayed effects, competing risks and pre-specified confounders. RESULTS: The median follow-up was 8.7 years. One third of the patients in our cohort were exposed to beta-blockers post DCIS diagnosis. During the study period, 48 patients experienced an invasive recurrence, giving a cumulative incidence of invasive breast cancer progression of 1.8% at five years. The cumulative exposure to beta-blocker was associated with a reduced risk in a dose-dependent manner, though the effect was not statistically significant. CONCLUSION: Our observational study is suggestive of a protective effect of beta-blockers against invasive breast cancer after primary DCIS diagnosis. These results provide rationales for experimental and clinical follow-up studies in carefully selected DCIS groups.

Ultrasound deep learning radiomics and clinical machine learning models to predict low nuclear grade, ER, PR, and HER2 receptor status in pure ductal carcinoma in situ.

Background: Low nuclear grade ductal carcinoma in situ (DCIS) patients can adopt proactive management strategies to avoid unnecessary surgical resection. Different personalized treatment modalities may be selected based on the expression status of molecular markers, which is also predictive of different outcomes and risks of recurrence. DCIS ultrasound findings are mostly non mass lesions, making it difficult to determine boundaries. Currently, studies have shown that models based on deep learning radiomics (DLR) have advantages in automatic recognition of tumor contours. Machine learning models based on clinical imaging features can explain the importance of imaging features. Methods: The available ultrasound data of 349 patients with pure DCIS confirmed by surgical pathology [54 low nuclear grade, 175 positive estrogen receptor (ER+), 163 positive progesterone receptor (PR+), and 81 positive human epidermal growth factor receptor 2 (HER2+)] were collected. Radiologists extracted ultrasonographic features of DCIS lesions based on the 5th Edition of Breast Imaging Reporting and Data System (BI-RADS). Patient age and BI-RADS characteristics were used to construct clinical machine learning (CML) models. The RadImageNet pretrained network was used for extracting radiomics features and as an input for DLR modeling. For training and validation datasets, 80% and 20% of the data, respectively, were used. Logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms were performed and compared for the final classification modeling. Each task used the area under the receiver operating characteristic curve (AUC) to evaluate the effectiveness of DLR and CML models. Results: In the training dataset, low nuclear grade, ER+, PR+, and HER2+ DCIS lesions accounted for 19.20%, 65.12%, 61.21%, and 30.19%, respectively; the validation set, they consisted of 19.30%, 62.50%, 57.14%, and 30.91%, respectively. In the DLR models we developed, the best AUC values for identifying features were 0.633 for identifying low nuclear grade, completed by the XGBoost Classifier of ResNet50; 0.618 for identifying ER, completed by the RF Classifier of InceptionV3; 0.755 for identifying PR, completed by the XGBoost Classifier of InceptionV3; and 0.713 for identifying HER2, completed by the LR Classifier of ResNet50. The CML models had better performance than DLR in predicting low nuclear grade, ER+, PR+, and HER2+ DCIS lesions. The best AUC values by classification were as follows: for low nuclear grade by RF classification, AUC: 0.719; for ER+ by XGBoost classification, AUC: 0.761; for PR+ by XGBoost classification, AUC: 0.780; and for HER2+ by RF classification, AUC: 0.723. Conclusions: Based on small-scale datasets, our study showed that the DLR models developed using RadImageNet pretrained network and CML models may help predict low nuclear grade, ER+, PR+, and HER2+ DCIS lesions so that patients benefit from hierarchical and personalized treatment.

Racial disparities in disease-specific mortality and surgical management of patients with ductal carcinoma in situ with microinvasion.

BACKGROUND AND OBJECTIVES: Given persistent racial disparities in breast cancer outcomes, this study explores racial differences in disease-specific mortality and surgical management among patients with microinvasive ductal carcinoma in situ (DCIS-MI). METHODS: The Surveillance, Epidemiology, and End Results Program was queried for patients aged 18+ years with DCIS-MI between January 1, 2010 and December 31, 2018. The study cohort was divided into non-Hispanic Black (NHB) and non-Hispanic White (NHW) patients. Disease-specific mortality was evaluated using Cox proportional hazards models. RESULTS: A total of 3400 patients were identified, of which 569 (16.7%) were NHB and 2831 (83.3%) were NHW. Compared with NHW patients, NHB patients had more positive lymph nodes (7.6% vs. 3.9% p < 0.001). In addition, NHB women were more likely to undergo axillary lymph node dissection (6.0% vs. 3.8%, p = 0.044) and receive chemotherapy (11.8% vs. 7.2%, p < 0.001). There were no racial differences in breast surgery type (p = 0.168), reconstructive surgery (p = 0.362), or radiation therapy (p = 0.342). Overall, NHB patients had worse disease-specific mortality (adjusted hazard ratio 2.13, 95% confidence interval [CI]: 1.10-4.14) with mortality risks diverging from NHW women after 3 years (6 years rate ratio [RR] 2.12, 95% CI: 1.13-4.34; 9 years RR 2.32, 95% CI: 1.24-4.35). CONCLUSIONS: NHB women with DCIS-MI present with higher nodal disease burden and experience worse disease-specific mortality than NHW women.

Soluble NKG2DLs Are Elevated in Breast Cancer Patients and Associate with Disease Outcome.

Ligands of the natural killer group 2D (NKG2DL) family are expressed on malignant cells and are usually absent from healthy tissues. Recognition of NKG2DLs such as MICA/B and ULBP1-3 by the activating immunoreceptor NKG2D, expressed by NK and cytotoxic T cells, stimulates anti-tumor immunity in breast cancer. Upregulation of membrane-bound NKG2DLs in breast cancer has been demonstrated by immunohistochemistry. Tumor cells release NKG2DLs via proteolytic cleavage as soluble (s)NKG2DLs, which allows for effective immune escape and is associated with poor prognosis. In this study, we collected serum from 140 breast cancer (BC) and 20 ductal carcinoma in situ (DCIS) patients at the time of initial diagnosis and 20 healthy volunteers (HVs). Serum levels of sNKG2DLs were quantified through the use of ELISA and correlated with clinical data. The analyzed sNKG2DLs were low to absent in HVs and significantly higher in BC patients. For some of the ligands analyzed, higher sNKG2DLs serum levels were associated with the classification of malignant tumor (TNM) stage and grading. Low sMICA serum levels were associated with significantly longer progression-free (PFS) and overall survival (OS). In conclusion, we provide the first insights into sNKG2DLs in BC patients and suggest their potential role in tumor immune escape in breast cancer. Furthermore, our observations suggest that serum sMICA levels may serve as a prognostic parameter in the patients analyzed in this study.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials. OBJECTIVE: To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance. METHODS: In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS. RESULTS: When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved. CONCLUSION: For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.