Ductal Carcinoma In Situ With Microinvasion Research Articles

Clinical and Imaging Characteristics of Contrast-enhanced Mammography and MRI to Distinguish Microinvasive Carcinoma from Ductal Carcinoma In situ

Rationale and ObjectivesThe prognosis of ductal carcinoma in situ with microinvasion (DCISM) is more similar to that of small invasive ductal carcinoma (IDC) than to pure ductal carcinoma in situ (DCIS). It is particularly important to accurately distinguish between DCISM and DCIS. The present study aims to compare the clinical and imaging characteristics of contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) between DCISM and pure DCIS, and to identify predictive factors of microinvasive carcinoma, which may contribute to a comprehensive understanding of DCISM in clinical diagnosis and support surveillance strategies, such as surgery, radiation, and other treatment decisions. Materials and MethodsForty-seven female patients diagnosed with DCIS were included in the study from May 2019 to August 2023. Patients were further divided into two groups based on pathological diagnosis: DCIS and DCISM. Clinical and imaging characteristics of these two groups were analyzed statistically. The independent clinical risk factors were selected using multivariate logistic regression and used to establish the logistic model [Logit(P)]. The diagnostic performance of independent predictors was assessed and compared using receiver operating characteristic (ROC) analysis and DeLong's test. ResultsIn CEM, the maximum cross-sectional area (CSAmax), the percentage signal difference between the enhancing lesion and background in the craniocaudal and mediolateral oblique projection (%RSCC, and %RSMLO) were found to be significantly higher for DCISM compared to DCIS (p = 0.001; p < 0.001; p = 0.008). Additionally, there were noticeable statistical differences in the patterns of enhancement morphological distribution (EMD) and internal enhancement pattern (IEP) between DCIS and DCISM (p = 0.047; p = 0.008). In MRI, only CSAmax (p = 0.012) and IEP (p = 0.020) showed significant statistical differences. The multivariate regression analysis suggested that CSAmax (in CEM or MR) and %RSCC were independent predictors of DCISM (all p < 0.05). The area under the curve (AUC) of CSAmax (CEM), %RSCC (CEM), Logit(P) (CEM), and CSAmax (MR) were 0.764, 0.795, 0.842, and 0.739, respectively. There were no significant differences in DeLong's test for these values (all p > 0.10). DCISM was significantly associated with high nuclear grade, comedo type, high axillary lymph node (ALN) metastasis, and high Ki-67 positivity compared to DCIS (all p < 0.05). ConclusionThe tumor size (CSAmax), enhancement index (%RS), and internal enhancement pattern (IEP) were highly indicative of DCISM. DCISM tends to express more aggressive pathological features, such as high nuclear grade, comedo-type necrosis, ALN metastasis, and Ki-67 overexpression. As with MRI, CEM has the capability to help predict when DCISM is accompanying DCIS.

Development and validation of a nomogram for predicting lymph node metastasis in ductal carcinoma in situ with microinvasion: A SEER population-based study.

Ductal carcinoma in situ with microinvasion (DCIS-MI) is a special type of breast cancer. It is an invasive lesion less than 1.0 mm in size related to simple ductal carcinoma in situ (DCIS). Lymph node metastasis (LNM) in DCIS-MI often indicates a poor prognosis. Therefore, the management of lymph nodes plays a vital role in the treatment strategy of DCIS-MI. Since DCIS-MI is often diagnosed by postoperative paraffin section and immunohistochemical detection, to obtain the best clinical benefits for such patients, we aim to establish and verify a nomogram to predict the possibility of lymph node metastasis in DCIS-MI patients and help preoperative or intraoperative clinical decision-making. A retrospective analysis of patients with DCIS-MI in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2019 was performed. The study cohort was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The risk factors were determined by univariate and multivariate logistic regression analyses in the training cohort, and a nomogram was constructed. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram in the training set and validation set. An independent data cohort was obtained from the Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB) for external validation. This study included 3951 female patients from SEER with DCIS-MI, including 244 patients with regional lymph node metastasis, accounting for 6.18% of the total. An independent test set of 323 patients from SJTU-BCDB was used for external validation. According to the multifactorial logistic regression analysis results, age at diagnosis, ethnicity, grade, and surgical modality were included in the prediction model. The areas under the ROC curves (AUCs) were 0.739 (95% CI: 0.702~0.775), 0.732 (95% CI: 0.675~0.788), and 0.707 (95%CI: 0.607-0.807) in the training, validation and external test groups, suggesting that the column line graphs had excellent differentiation. The calibration curves slope was close to 1, and the model's predicted values were in good agreement with the actual values. The DCA curves showed good clinical utility. In this study, we constructed accurate and practical columnar maps with some clinical benefit to predict the likelihood of lymph node metastasis in patients with postoperatively diagnosed DCIS-MI and provide a reference value for specifying treatment strategies.

Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images.

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

A clinical radiomics nomogram preoperatively to predict ductal carcinoma in situ with microinvasion in women with biopsy-confirmed ductal carcinoma in situ: a preliminary study

PurposeTo predict ductal carcinoma in situ with microinvasion (DCISMI) based on clinicopathologic, conventional breast magnetic resonance imaging (MRI), and dynamic contrast enhanced MRI (DCE-MRI) radiomics signatures in women with biopsy-confirmed ductal carcinoma in situ (DCIS).MethodsEighty-six women with eighty-seven biopsy-proven DCIS who underwent preoperative MRI and underwent surgery were retrospectively identified. Clinicopathologic, conventional MRI, DCE-MRI radiomics, combine (based on conventional MRI and DCE-MRI radiomics), traditional (based on clinicopathologic and conventional MRI) and mixed (based on clinicopathologic, conventional MRI and DCE-MRI radiomics) models were constructed by logistic regression (LR) with a 3-fold cross-validation, all evaluated using receiver operating characteristic (ROC) curve analysis. A clinical radiomics nomogram was then built by incorporating the Radiomics score, significant clinicopathologic and conventional MRI features of mixed model.ResultsThe area under the curves (AUCs) of clinicopathologic, conventional MRI, DCE-MRI radiomics, traditional, combine, and mixed model were 0.76 (95% confidence interval [CI] 0.59–0.94), 0.77 (95%CI 0.59–0.95), 0.74 (95%CI 0.55–0.93), 0.87 (95%CI 0.73–1), 0.8 (95%CI 0.63–0.96), and 0.93 (95%CI 0.84–1) in the validation cohort, respectively. The clinical radiomics nomogram based on mixed model showed higher AUCs than both clinicopathologic and DCE-MRI radiomics models in training/test (all P < 0.05) set and showed the greatest overall net benefit for upstaging according to decision curve analysis (DCA).ConclusionA nomogram constructed by combining clinicopathologic, conventional MRI features and DCE-MRI radiomics signatures may be useful in predicting DCISMI from DICS preoperatively.

KRT15 in early breast cancer screening and correlation with HER2 positivity, pathological gradeand N stage.

Objective: This study was designed to explore KRT15 dysregulation and its correlation with clinical characteristics among ductal carcinoma in situ (DCIS), DCIS with microinvasion (DCIS-MI)and invasive breast cancer (IBC) patients. Methods: KRT15 from lesion samples of 50 DCIS patients, 48 DCIS-MI patientsand 50 IBC patients was detected by immunohistochemistry. Results: KRT15 discriminated IBC patients from DCIS patients (area under the curve [AUC] =0.895; 95% CI=0.836-0.954) and DCIS-MI patients (AUC=0.707; 95% CI=0.606-0.808). In DCIS patients, KRT15 was negatively correlated with pathological grade (p=0.015). In DCIS-MI patients, KRT15 was positively related to estrogen receptor positivity but negatively associated with Ki-67 (both p<0.05). In IBC patients, KRT15 was negativelylinked to HER2 positivity, histological grade, N stageand tumor node metastasis stage (all p<0.05). Conclusion: KRT15 assessmentmay help with early breast cancer screening.

An MRI-Based Radiomics Nomogram to Distinguish Ductal Carcinoma In Situ with Microinvasion From Ductal Carcinoma In Situ of Breast Cancer

Accurate preoperative differentiation between ductal carcinoma in situ with microinvasion (DCISM) and ductal carcinoma in situ (DCIS) could facilitate treatment optimization and individualized risk assessment. The present study aims to build and validate a radiomics nomogram based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) that could distinguish DCISM from pure DCIS breast cancer. MR images of 140 patients obtained between March 2019 and November 2022 at our institution were included. Patients were randomly divided into a training (n=97) and a test set (n=43). Patients in both sets were further split into DCIS and DCISM subgroups. The independent clinical risk factors were selected by multivariate logistic regression to establish the clinical model. The optimal radiomics features were chosen by the least absolute shrinkage and selection operator, and a radiomics signature was built. The nomogram model was constructed by integrating the radiomics signature and independent risk factors. The discrimination efficacy of our nomogram was assessed by using calibration and decision curves. Six features were selected to construct the radiomics signature for distinguishing DCISM from DCIS. The radiomics signature and nomogram model exhibited better calibration and validation performance in the training (AUC 0.815, 0.911, 95% confidence interval [CI], 0.703-0.926, 0.848-0.974) and test (AUC 0.830, 0.882, 95% CI, 0.672-0.989, 0.764-0.999) sets than in the clinical factor model (AUC 0.672, 0.717, 95% CI, 0.544-0.801, 0.527-0.907). The decision curve also demonstrated that the nomogram model exhibited good clinical utility. The proposed noninvasive MRI-based radiomics nomogram model showed good performance in distinguishing DCISM from DCIS.

Clinicopathological characteristics, treatments, and prognosis of breast ductal carcinoma in situ with microinvasion: A narrative review.

Ductal carcinoma in situ with microinvasion (DCIS-MI) is defined as ductal carcinoma in situ (DCIS) with a microscopic invasive focus ≤1 mm in the longest diameter. The current literature is controversial concerning the clinical prognostic features and management of DCIS-MI. This narrative review described recently reported literature regarding the characteristics, treatment, and prognosis of it. Searching PubMed for relevant articles covering the period of 1982 to 2021 using the following terms by MeSH and free-word: breast cancer, microinvasion, DCIS, DCIS-MI, and invasive ductal carcinoma (IDC). DCIS-MI tends to express more aggressive pathological features such as necrosis, HER2+, ER- or PR-, and high nuclear grade. The overall prognosis of DCIS-MI is typically good, however, some indicators such as young age, HR-, HER2+ and multimicroinvasive lesions, were associated with worse prognoses. And there are also conflicting results on the differences between the prognoses of DCIS-MI and DCIS or T1a-IDC. Postoperative chemotherapy and anti-HER2 therapy still have uncertain benefits and are more likely to be used to treat high-risk patients who are HR- orHER2+ to improve the prognosis. DCIS-MI has more aggressive pathological features, which may suggest its biological behavior is worse than that of DCIS and similar to early IDC. Although the overall prognosis of DCIS-MI is good, when making decisions about adjuvant therapy clinicians need to give priority to the hormone receptor status, HER2 expression and axillary lymph node status of patients, because these may affect the prognosis and treatment response.

Survival outcomes after breast-conserving surgery plus radiotherapy compared with mastectomy in breast ductal carcinoma in situ with microinvasion

Ductal carcinoma in situ with microinvasion (DCIS-MI) is a subtype of breast cancer with a good prognosis, for which both breast conserving surgery plus radiotherapy (BCS + RT) and mastectomy are feasible surgical methods, but no clear conclusion has been made on the choice of these treatments. We used the Surveillance, Epidemiology and End Results database to extract 5432 DCIS-MI patients. Participants were divided into the BCS + RT group and the mastectomy group. We compared the overall survival (OS) and breast cancer-specific survival (BCSS) of the two groups using the Kaplan–Meier method and Cox regressions before and after propensity score matching (PSM). Before PSM, both univariate and multivariate analyses showed that BCS + RT group had significantly higher OS and BCSS compared with patients in the mastectomy group (P < 0.001). After PSM, the multivariate analysis showed that compared with mastectomy, the BCS + RT showed significantly higher OS and BCSS (HR = 0.676, 95% CI = 0.540–0.847, P < 0.001; HR = 0.565,95% CI = 0.354–0.903, P = 0.017). In addition, the subgroup analysis showed that BCS + RT is at least equivalent to mastectomy with respect to OS and BCSS in any subgroup. For patients with DCIS-MI, the prognosis of BCS + RT was superior to mastectomy.

Racial Disparities in Disease-Specific Survival and Surgical Management of Patients with Ductal Carcinoma In Situ with Microinvasion

INTRODUCTION: Despite persistent racial disparities in breast cancer outcomes, there are no studies examining the impact of race on treatment of the rare entity Ductal Carcinoma In-Situ with Microinvasion (DCIS-MI). The objective of this study is to examine racial differences in disease-specific survival (DSS) and surgical management among breast cancer patients presenting with DCIS-MI. METHODS: The Surveillance, Epidemiology, and End Results (SEER) Program was queried for patients with breast cancer age 18+ diagnosed 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). Sociodemographic, clinical, and treatment variables were compared using bivariable analysis. DSS was evaluated using a Cox proportional hazards model. RESULTS: A total of 3,476 patients were identified, of whom 608 (17.5%) identified as NHB and 2868 (82.5%) identified as NHW. The median age for NHB women was slightly younger (57 years, range [50 to 66]) than NHW women (59 years [50 to 67]; p = 0.01). Compared with NHW patients, NHB patients were more likely to undergo mastectomy (42.6% vs 38.4%, p = 0.04) and axillary lymph node dissection (ALND; 6.4% vs 3.7%, p = 0.01). Additionally, NHB patients had a worse DSS (hazard ratio 3.2, p < 0.01) compared with NHW patients. Of note, there were no racial differences in chemotherapy (p = 0.19) and radiation therapy (p = 0.34). CONCLUSION: A higher percentage of NHB women with DCIS-MI have a mastectomy and ALND than NHW women, yet NHB women have worse DSS. Future studies should examine patient, physician, and institutional factors driving surgical disparities and poor survival in NHB patients with DCIS-MI.

Clinicopathological characteristics and prognostic analysis of tumor-infiltrating lymphocytes (TILs) in ductal carcinoma in situ (DCIS) and DCIS with microinvasion (DCIS-Mi) of the breast

ObjectiveOur purpose is to evaluate the correlation of TILs with clinicopathological characteristics and disease free survival (DFS) in DCIS and DCIS-Mi breast cancer (BC) patients.MethodsWe retrospectively reviewed the data of 360 DCIS patients and 125 DCIS-Mi patients treated by a single institution from 2016 to 2019. TILs are regarded as continuous variables and are divided into low (≤ 5%), medium (5–40%) and high (≥ 40%) for statistical analysis.ResultsIn DCIS and DCIS-Mi patients, larger tumor size, higher nuclear grade, hormone receptor (HR) negativity and human epidermal growth factor receptor 2(HER2) overexpression are all related to high TILs (P < 0.05). In addition, compared with DCIS, DCIS-Mi patients were significantly associated with high TILs (P < 0.001). Based on the different results of the subtypes, we further studied the correlation between TILs and DFS in 279 cases of HER2+ patients (204 of DCIS; 75 of DCIS-Mi). In HER2+ group, DCIS-Mi was significantly associated with HR negativity (P = 0.015) and high TILs (P = 0.002) compared with DCIS patients. In the survival analysis, we found that TILs had no effect on the DFS of DCIS (P = 0.938), DCIS-Mi (P = 0.807), and HER2+ (P = 0.379) BC patients. In the univariate and multivariate cox regression analysis, the correlation between TILs and the prognosis of DFS has not been confirmed in the three BC groups (P > 0.05).ConclusionTILs have played an non-negligible role in the progress of DCIS to DCIS-Mi, especially in HER2+ BC. The predictive and prognostic value of TILs still needs further research to confirm.

Prognostic Factors and a Nomogram Predicting Survival in Patients with Breast Ductal Carcinoma in situ with Microinvasion: A Population-Based Study.

PurposeDuctal carcinoma in situ with microinvasion (DCISM) can be challenging to balance the risks of overtreatment versus undertreatment. We aim to identify prognostic factors in patients with DCISM and construct a nomogram to predict breast cancer-specific survival (BCSS).Materials and MethodsA retrospective cohort study of women diagnosed with DCISM from 1988 to 2015 who were identified in the Surveillance, Epidemiology and End Results database. Clinical variables and tumor characteristics were evaluated, and Cox proportional-hazards regression was performed. A nomogram was constructed from the multivariate logistic regression to combine all the prognostic factors to predict the prognosis of DCISM patients at 5 years, 10 years, and 15 years.ResultsWe identified 5438 total eligible breast cancer patients with a median and max survival time of 78 and 227 months, respectively. Here, patients with poorer survival outcomes were those diagnosed between 1988 and 2001, African-American race, under 40 years of age, higher tumor N stage, progesterone receptor-negative tumor, and received no surgery. The nomogram was constructed by the seven variables and passed the calibration and validation steps. The area under the receiver operating characteristic (ROC) curve (AUC) of both the training set and the validating set (5-year AUC: 0.77 and 0.88, 10-year AUC: 0.75 and 0.73, 15-year AUC: 0.72 and 0.65). Receiving chemotherapy was associated with a better BCSS (hazard ratio, HR=0.45, 95% confidence interval, 95% CI = 0.23–0.89), especially in patients with estrogen receptor (ER) negative, progesterone receptor (PR) negative (HR = 0.35, 95% CI = 0.13–0.97) and ER+PR-/ER-PR+ DCISM (HR = 0.07, 95% CI = 0.01–0.59).ConclusionOur current study is the first to construct nomograms of patients with DCISM which could help physicians identify breast cancer patients that more likely to benefit from more intensive treatment and follow-up. Chemotherapy might benefit patients with ER-PR- and ER+PR-/ER-PR+ DCISM.

Characteristics, prognosis, risk factors, and management of recently diagnosed ductal carcinoma in situ with microinvasion.

BackgroundDuctal carcinoma in situ with microinvasion (DCISM) represents ~1% of all breast cancer cases and is arguably a more aggressive subtype of ductal carcinoma in situ (DCIS). Lacking studies with a large population, the survival outcomes of DCISM are still poorly understood and the treatment recommendations remain controversial. This study aims to investigate the long‐term outcome of patients with DCISM, potential risk factors for their prognosis, and the difference of survival between patients treated with breast‐conserving surgery plus radiotherapy (BCT + RT) and mastectomy only.MethodsIn total, 1299 patients from 2008 to 2019 with DCISM were retrospectively retrieved. Clinicopathological features were analyzed. Subgroup analysis was conducted between patients who underwent BCT + RT and mastectomy only. Univariate and multivariate analyses were performed to identify prognostic factors for survival. Differences of survival between two groups were compared using the log‐rank test.ResultsTotally, 1286 patients had follow‐up information, the median follow‐up is 54.57 months, the 5‐year local–regional‐free survival (LRFS), distant metastasis‐free survival (DMFS), and overall survival (OS) were 98.6%, 97.1%, and 99.4%, respectively, two deaths were due to breast cancer. Multivariate analysis identified age <40 (p = 0.028) and close margin (≤2 mm) as independent negative prognostic factors for LRFS. No prognostic factors were identified for DMFS and OS. The 5‐year LRFS, DMFS, and OS of patients who had DCIS component ≥5 cm and underwent mastectomy without adjuvant radiotherapy were 100%, 98.4%, and 98.4%, respectively. After propensity score matching (PSM), no survival difference was observed between patients treated with BCT + RT or mastectomy only.ConclusionsDCISM patients had a good survival, even those with DCIS component ≥5 cm. Patients aged <40 or with close margin (≤2 mm) had a poorer LRFS, but not DMFS or OS. BCT + RT is a feasible choice for DCISM patients.

Breast ductal carcinoma in situ with micro-invasion versus ductal carcinoma in situ: a comparative analysis of clinicopathological and mammographic findings

To determine the differences in clinicopathological and mammographic findings between ductal carcinoma in situ (DCIS) and ductal carcinoma in situ with micro-invasion (DCIS-MI) and explore clinicopathological and mammographic factors associated with DCIS-MI. All DCIS patients with or without micro-invasion who underwent preoperative mammography at The Affiliated Hospital of Qingdao University from January 2016 through June 2020 were identified retrospectively. The correlations of clinicopathological findings with DCIS-MI were evaluated using univariate and multivariate binary logistic regression analyses. Imaging findings were compared between the groups by using the Pearson chi-square test. A total of 445 DCIS lesions and 151 DCIS-MI lesions were included in the final analysis. Large extent (≥2.7 cm), high nuclear grade, comedo-type, negative progesterone receptor (PR), negative oestrogen receptor (ER), high Ki-67 and axillary lymph node metastasis were more frequently found in DCIS-MI than in DCIS (all p<0.05), and the first four of these were found to be independent predictors of DCIS-MI in the multivariate analysis (all p<0.05). Regarding imaging findings, compared to DCIS, DCIS-MI showed fewer occult lesions and more lesions with calcifications in mass, asymmetry, and architectural distortion (p=0.004). Grouped calcifications were usually associated with DCIS, while regional calcifications were commonly found in DCIS-MI (p<0.05). Large extent, high nuclear grade, comedo-type and negative PR were found to be independent predictors of DCIS-MI. Lesions with calcifications and regional calcifications were more likely associated with DCIS-MI on mammography.

Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound.

BackgroundTo develop an ultrasound-based deep learning model to predict postoperative upgrading of pure ductal carcinoma in situ (DCIS) diagnosed by core needle biopsy (CNB) before surgery.MethodsOf the 360 patients with DCIS diagnosed by CNB and identified retrospectively, 180 had lesions upstaged to ductal carcinoma in situ with microinvasion (DCISM) or invasive ductal carcinoma (IDC) postoperatively. Ultrasound images obtained from the hospital database were divided into a training set (n=240) and validation set (n=120), with a ratio of 2:1 in chronological order. Four deep learning models, based on the ResNet and VggNet structures, were established to classify the ultrasound images into postoperative upgrade and pure DCIS. We obtained the area under the receiver operating characteristic curve (AUROC), specificity, sensitivity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) to estimate the performance of the predictive models. The robustness of the models was evaluated by a 3-fold cross-validation.ResultsClinical features were not significantly different between the training set and the test set (P value >0.05). The area under the receiver operating characteristic curve of our models ranged from 0.724 to 0.804. The sensitivity, specificity, and accuracy of the optimal model were 0.733, 0.750, and 0.742, respectively. The three-fold cross-validation results showed that the model was very robust.ConclusionsThe ultrasound-based deep learning prediction model is effective in predicting DCIS that will be upgraded postoperatively.

Axillary staging in ductal carcinoma in situ with microinvasion

Background: Ductal carcinoma in situ with microinvasion (DCISM) is a rare subtype of DCIS, with a foci of tumour cells penetrating through the basement membrane (no more than 1mm). Since 2015 to 2019, there have only been 3 (5.7%) cases in the breast unit at Hillingdon Hospitals NHS Foundation Trust (THH), a district general hospital in London. A conundrum for surgeons is that definitive diagnosis is only made upon histological examination of the final surgical specimen.. In addition to this, in the UK, there are no specific guidelines on the role of axillary staging in the management of DCISM cases. As a result, there is ongoing controversy surrounding the most appropriate management of DCISM, in particular the need of axillary staging.

Clinical and imaging characteristics of breast ductal carcinoma in situ with microinvasion.

BackgroundWe analyzed the clinical and imaging characteristics of patients with breast ductal carcinoma in situ with microinvasion (DCISM) and breast ductal carcinoma in situ (DCIS).MethodsWe analyzed the records of 40 patients diagnosed with DCISM and 61 patients with DCIS who were hospitalized at Shengjing Hospital (Shenyang, China) from January 2009 to June 2016. The size, hardness, and degree of calcification of tumors were determined by mammography and ultrasonography.ResultsIn all, 37 DCISM patients and 45 DCIS patients showed clinical palpable masses (92.5% vs 73.77%, P = 0.018). Mammography showed that the mean size of tumor was larger in DCISM patients than that of DCIS patients (3.13 ± 1.51 vs 2.68 ± 1.77, P = 0.030). Ultrasound examination revealed calcification shadows in the solid tumor mass in 17 DCISM cases and 11 DCIS patients (42.5 vs 18.03%, P = 0.007). Furthermore, estrogen receptor positivity and progesterone receptor positivity were more common in DCIS patients (32.5% vs 54.10%, P = 0.033; 22.5% vs 45.90%, P = 0.017), and the percentage of menopausal patients were higher in DCISM patients than that of DCIS patients (70.00% vs 47.54%, P = 0.026).ConclusionClinically palpable and calcified tumor masses on sonography are more commonly encountered in DCISM lesions.

Clinical characteristics of breast ductal carcinoma in situ with microinvasion: a narrative review.

Ductal carcinoma in situ (DCIS) with microinvasion (DCIS-MI) is defined as the extension of cancer cells beyond the basement membrane into adjacent tissue with no focus larger than 1 mm or a maximum diameter of less than 1 mm for multiple invasive foci. DCIS-MI constitutes approximately 1% of all breast cancer cases and 5% to 10% of cases of DCIS. The current literature is controversial concerning the clinical prognostic features and management of DCIS-MI. This narrative review described recently reported literature regarding the characteristics, diagnosis, treatment, and prognosis of DCIS-MI.

Immune microenvironment in ductal carcinoma in situ: a comparison with invasive carcinoma of the breast

BackgroundThe immune microenvironment in ductal carcinoma in situ (DCIS) and its significance are not well established. This study was conducted to evaluate the immune microenvironment of DCIS including the composition of tumor-infiltrating lymphocyte (TIL) subsets and PD-L1+ immune cells and to compare it with that of invasive breast cancer.Materials and methodsA total of 671 cases including three different disease groups of pure DCIS, DCIS with microinvasion (DCIS-M), and invasive carcinoma were included in this study. CD4+, CD8+, and FOXP3+ TIL subsets and PD-L1+ immune cells were detected with immunohistochemistry using tissue microarrays and were analyzed in relation to clinicopathologic characteristics and different disease groups.ResultsIn pure DCIS, high infiltrations of CD4+, CD8+, and FOXP3+ T cells and the presence of PD-L1+ immune cells were associated with high nuclear grade, comedo-type necrosis, hormone receptor (HR) negativity, and high Ki-67 proliferation index. All immune cell infiltrations were higher in invasive carcinoma than in pure DCIS regardless of the HR status. While CD4+ T cells were more abundant than CD8+ T cells in pure DCIS, CD8+ T cells were dominant in invasive carcinoma, especially in HR-negative tumors. Within individual cases of invasive carcinoma with DCIS component, all immune cell subset infiltration was higher in the invasive component than in the DCIS component; however, CD4+ TIL infiltration did not differ between the two components in HR-negative tumors. Comparing pure DCIS, DCIS-M, and DCIS associated with invasive carcinoma (DCIS-INV), CD4+ TIL infiltration revealed a gradual increase from pure DCIS to DCIS-M and DCIS-INV in the HR-negative group, whereas FOXP3+ TIL infiltration was significantly increased in DCIS-INV than in pure DCIS in the HR-positive group. The high infiltration of FOXP3+ TIL and the presence of PD-L1+ immune cells were associated with tumor recurrence in patients with pure DCIS.ConclusionsOur study showed that the immune microenvironment differs significantly not only between DCIS and invasive carcinoma but also between pure DCIS, DCIS-M, and DCIS-INV depending on the HR status.

Clinical comparison between ductal carcinoma in situ and ductal carcinoma in situ with microinvasion

Objective To analyze the differences in the treatment patterns, clinical characteristics, treatment outcomes and prognostic factors between breast cancer patients with ductal carcinoma in situ (DCIS) and ductal carcinoma in situ with microinvasion (DCIS-MI). Methods Clinical data of 866 female patients including 631 DCIS cases and 235 DCIS-MI cases treated in our institution between 1999 and 2013 were retrospectively analyzed. The local control (LC), disease-free survival (DFS) and overall survival (OS) rates were calculated by Kaplan-Meier survival analysis. The prognostic factors were identified by Log-rank test. Results Similar LC, DFS and OS rates were obtained between two groups (all P>0.05). The univariate analysis demonstrated that Her-2-positive patients had worse OS and DFS than Her-2-negative counterparts. Patients undergoing breast-conserving surgery without radiotherapy had lower LC and DFS rates compared with those receiving radical mastectomy. Conclusions DCIS and DCIS-MI patients have similar clinical prognosis in terms of OS, LC and DFS. Her-2 positive is an unfavorable prognostic factor for DFS and OS. The LC and DFS rates in the breast-conserving surgery alone group are worse than those in the mastectomy group. Key words: Breast ductal carcinoma in situ; Breast ductal carcinoma in situ with microinvasion; Breast neoplasm/radiotherapy; Breast neoplasm/surgery; Prognosis

Clinic-Pathological Features of Breast Ductal Carcinoma in Situ with Micro-Invasion

Background: To investigate the differences of clinic-pathological features among ductal carcinoma in situ (DCIS), ductal carcinoma in situ with micro-invasion (DCIS-MI) and early invasive carcinoma (IDC) in stage T1.Methods: From January 2014 to December 2018, 308 cases DCIS, DCIS-MI 92 cases and 111 cases of T1a, 343 cases of T1b, and 1032 cases of T1c were investigated in a retrospective analysis. The population and clinic-pathological characteristics including age, menstrual status, surgical mode, lymph node status and molecular markers were compared in each group. Survival rate of all patients were followed-up for 5 years.Results: Compared with DCIS-MI group, the higher breast-conserving rate and lower lymph node metastasis rate in the DCIS group were shown in the DCIS-MI group (p < .05). There were no significant differences in tumor diameter, number of tumors, ER, PR, HER2 and Ki67 expression, molecular typing, (p > .05). The expression of Ki67 in T1a, T1b and T1c groups increased gradually with elevated grades (p < .05). The proportion of HER2-positive patients in DCIS-MI group was significantly higher than that in T1a-b-c (p < .05). There were no significant differences in DFS and OS between the 3 groups (p > .05).Conclusions: The clinic-pathological features of DCIS-MI are similar to those of DCIS and T1a, but significantly different from T1c.