Ductal carcinoma in situ diagnosed at US-guided 14-gauge core-needle biopsy for breast mass: preoperative predictors of invasive breast cancer

Update on the management of ductal carcinoma in situ of the breast: current approach and future perspectives

The standard treatment for ductal carcinoma in situ became well established through the results of several valuable clinical trials, and its therapeutic benefits have now come to be taken for granted. Ductal carcinoma in situ has an extremely good prognosis with the current treatment approach, with a 10-year breast cancer-specific survival rate of 97-98%. According to one retrospective cohort study, the breast cancer-specific survival rate of patients with low-grade ductal carcinoma in situ does not differ significantly between patients undergoing and not undergoing surgery. Some patients with ductal carcinoma in situ are not at a risk of progression to invasive cancer, but the predictors of such progression have not yet been clearly identified. Therefore, the same therapeutic strategies have been used to treat ductal carcinoma in situ and under the assumption that they have risks of invasive breast cancer, and a well-balanced risk/benefit ratio in respect of treatment has not yet been achieved. Based on the results of several recent clinical trials aimed at ensuring provision of a well-balanced treatment for patients with ductal carcinoma in situ which carries a good prognosis, de-escalation of postoperative adjuvant therapy has now begun. Currently, not only is the optimization of postoperative adjuvant therapy accelerating, but also clinical trials to de-escalate basic surgical treatments are under way. There is a possibility of achieving individualized treatment for patients with ductal carcinoma in situ of the breast with reduced treatment intervention. In this review, we present an overview of the current treatment approaches and potential future management strategies for ductal carcinoma in situ of the breast.

Meta-analysis of contrast-enhanced ultrasound in differential diagnosis of breast adenosis and breast cancer

This systematic review and meta-analysis study aimed to determine the total capacity of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of breast lesions and breast cancer. For collecting papers, four groups of keywords were searched in five databases. The required information was extracted from the selected papers. In addition to the descriptive findings, a meta-analysis was also conducted. Thirty-three of thirty-six studies (91.67%) on the differential diagnosis of various degrees and types of breast lesions showed that CEUS has proper performance. The pooled values related to the sensitivity and specificity of CEUS were computed by 88.00 and 76.17.

Selective omission of sentinel lymph node biopsy in mastectomy for ductal carcinoma in situ: identifying eligible candidates

BACKGROUND

Sentinel lymph node biopsy (SLNB) is recommended for patients with ductal carcinoma in situ (DCIS) undergoing mastectomy, given the concerns regarding upstaging and technical difficulties of post-mastectomy SLNB. However, this may lead to potential overtreatment, considering favorable prognosis and de-escalation trends in DCIS. Data regarding upstaging and axillary lymph node metastasis among these patients remain limited.

METHODS

We retrospectively reviewed patients with DCIS who underwent mastectomy with SLNB or axillary lymph node dissection at Gangnam Severance Hospital between January 2010 and December 2021. To explore the feasibility of omitting SLNB, we assessed the rates of DCIS upgraded to invasive carcinoma and axillary lymph node metastasis. Binary Cox regression analysis was performed to identify clinicopathologic factors associated with upstaging and axillary lymph node metastasis.

RESULTS

Among 385 patients, 164 (42.6%) experienced an invasive carcinoma upgrade: microinvasion, pT1, and pT2 were confirmed in 53 (13.8%), 97 (25.2%), and 14 (3.6%) patients, respectively. Seventeen (4.4%) patients had axillary lymph node metastasis. Multivariable analysis identified age ≤ 50 years (adjusted odds ratio [OR], 12.73; 95% confidence interval [CI], 1.18-137.51; p = 0.036) and suspicious axillary lymph nodes on radiologic evaluation (adjusted OR, 9.31; 95% CI, 2.06-41.99; p = 0.004) as independent factors associated with axillary lymph node metastasis. Among patients aged > 50 years and/or no suspicious axillary lymph nodes, only 1.7-2.3%) experienced axillary lymph node metastasis.

CONCLUSIONS

Although underestimation of the invasive component was relatively high among patients with DCIS undergoing mastectomy, axillary lymph node metastasis was rare. Our findings suggest that omitting SLNB may be feasible for patients over 50 and/or without suspicious axillary lymph nodes on radiologic evaluation.

AI analytics can be used as imaging biomarkers for predicting invasive upgrade of ductal carcinoma in situ

OBJECTIVES

To evaluate whether the quantitative abnormality scores provided by artificial intelligence (AI)-based computer-aided detection/diagnosis (CAD) for mammography interpretation can be used to predict invasive upgrade in ductal carcinoma in situ (DCIS) diagnosed on percutaneous biopsy.

METHODS

Four hundred forty DCIS in 420 women (mean age, 52.8 years) diagnosed via percutaneous biopsy from January 2015 to December 2019 were included. Mammographic characteristics were assessed based on imaging features (mammographically occult, mass/asymmetry/distortion, calcifications only, and combined mass/asymmetry/distortion with calcifications) and BI-RADS assessments. Routine pre-biopsy 4-view digital mammograms were analyzed using AI-CAD to obtain abnormality scores (AI-CAD score, ranging 0-100%). Multivariable logistic regression was performed to identify independent predictive mammographic variables after adjusting for clinicopathological variables. A subgroup analysis was performed with mammographically detected DCIS.

RESULTS

Of the 440 DCIS, 117 (26.6%) were upgraded to invasive cancer. Three hundred forty-one (77.5%) DCIS were detected on mammography. The multivariable analysis showed that combined features (odds ratio (OR): 2.225, p = 0.033), BI-RADS 4c or 5 assessments (OR: 2.473, p = 0.023 and OR: 5.190, p < 0.001, respectively), higher AI-CAD score (OR: 1.009, p = 0.007), AI-CAD score ≥ 50% (OR: 1.960, p = 0.017), and AI-CAD score ≥ 75% (OR: 2.306, p = 0.009) were independent predictors of invasive upgrade. In mammographically detected DCIS, combined features (OR: 2.194, p = 0.035), and higher AI-CAD score (OR: 1.008, p = 0.047) were significant predictors of invasive upgrade.

CONCLUSION

The AI-CAD score was an independent predictor of invasive upgrade for DCIS. Higher AI-CAD scores, especially in the highest quartile of ≥ 75%, can be used as an objective imaging biomarker to predict invasive upgrade in DCIS diagnosed with percutaneous biopsy.

CRITICAL RELEVANCE STATEMENT

Noninvasive imaging features including the quantitative results of AI-CAD for mammography interpretation were independent predictors of invasive upgrade in lesions initially diagnosed as ductal carcinoma in situ via percutaneous biopsy and therefore may help decide the direction of surgery before treatment.

KEY POINTS

• Predicting ductal carcinoma in situ upgrade is important, yet there is a lack of conclusive non-invasive biomarkers. • AI-CAD scores-raw numbers, ≥ 50%, and ≥ 75%-predicted ductal carcinoma in situ upgrade independently. • Quantitative AI-CAD results may help predict ductal carcinoma in situ upgrade and guide patient management.

Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ

OBJECTIVE

To investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment.

METHODS

Consecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established.

RESULTS

A total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867.

CONCLUSION

Multi-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.

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

PURPOSE

To 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).

METHODS

Eighty-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.

RESULTS

The 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).

CONCLUSION

A nomogram constructed by combining clinicopathologic, conventional MRI features and DCE-MRI radiomics signatures may be useful in predicting DCISMI from DICS preoperatively.

Active Surveillance for Atypical Ductal Hyperplasia and Ductal Carcinoma In Situ

Atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS) are relatively common breast lesions on the same spectrum of disease. Atypical ductal hyperblasia is a nonmalignant, high-risk lesion, and DCIS is a noninvasive malignancy. While a benefit of screening mammography is early cancer detection, it also leads to increased biopsy diagnosis of noninvasive lesions. Previously, treatment guidelines for both entities included surgical excision because of the risk of upgrade to invasive cancer after surgery and risk of progression to invasive cancer for DCIS. However, this universal management approach is not optimal for all patients because most lesions are not upgraded after surgery. Furthermore, some DCIS lesions do not progress to clinically significant invasive cancer. Overtreatment of high-risk lesions and DCIS is considered a burden on patients and clinicians and is a strain on the health care system. Extensive research has identified many potential histologic, clinical, and imaging factors that may predict ADH and DCIS upgrade and thereby help clinicians select which patients should undergo surgery and which may be appropriate for active surveillance (AS) with imaging. Additionally, multiple clinical trials are currently underway to evaluate whether AS for DCIS is feasible for a select group of patients. Recent advances in MRI, artificial intelligence, and molecular markers may also have an important role to play in stratifying patients and delineating best management guidelines. This review article discusses the available evidence regarding the feasibility and limitations of AS for ADH and DCIS, as well as recent advances in patient risk stratification.

Upgrade Rate of Ductal Carcinoma In Situ to Invasive Carcinoma and the Clinicopathological Factors Predicting the Upgrade Following a Mastectomy: A Retrospective Study

Background The rate of upgrading ductal carcinoma in situ (DCIS) to invasive cancer varies widely in the literature with no consensus regarding sentinel lymph node biopsy (SLNB) for DCIS; however, some guidelines do recommend it in the event of a mastectomy. The primary aim of this study was to determine the upgrade rate of DCIS to invasive carcinoma (IC) in patients undergoing mastectomy for DCIS and identify the clinicopathological predicting factors for the upgrade. The secondary aim was to determine the SLNB positivity rate. Methodology We retrospectively analysed consecutive patients with DCIS diagnosed through a biopsy who then underwent mastectomy over a 10-year period (2010 to 2020). Clinical, radiological, and histological variables were collected from medical records. Results We studied 143 women (mean age = 57.4 years, range = 26-85 years) who underwent mastectomy for DCIS identified on biopsy. Almost two-thirds (62.9%, 90/143) of the patients were detected on screening mammography, while 35.6% (51/143) were diagnosed following presentation with either an area of palpable concern or nipple discharge. The most common mammographic presentation of DCIS was calcification (83.9%, 120/143), and, in 85.9% of the patients, the mammographic lesion was more than 20 mm. High-grade DCIS was noted in 76.9% of preoperative biopsy results, while the rest was either low or intermediate-grade DCIS. Overall, 24.5% (35/143) were upgraded to IC (upgraded group) on postoperative histology, whereas 108/143 remained DCIS postoperatively (pure DCIS group). The positivity rate of SLNB was 4.8%. Multifocality was the only significant predictor of IC on multivariate analyses of clinicopathological predictors (odds ratio = 3.0, 95% confidence interval = 1.0-8.7). The presence of comedonecrosis was higher in the upgraded group compared to the pure DCIS group (42.9% vs. 27.8%), but this was not statistically significant. Conclusions In our study cohort, nearly one in four (24.5%) patients were upgraded from DCIS to IC on postoperative histology, with an SLNB positivity rate of 4.8%. This is important when counselling patients regarding the risk of coincident occult IC and the importance of SLNB at the time of mastectomy. Multifocality on preoperative imaging was the only significant predictive factor. Based on this result, we recommend that SLNB should also be considered if patients have multifocal DCIS and planned for oncoplastic breast-conserving surgery. However, further studies are required to investigate the association between multifocal DCIS and the risk of upgrading to IC.

Predicting Underestimation of Invasive Cancer in Patients with Core-Needle-Biopsy-Diagnosed Ductal Carcinoma In Situ Using Deep Learning Algorithms

The prediction of an occult invasive component in ductal carcinoma in situ (DCIS) before surgery is of clinical importance because the treatment strategies are different between pure DCIS without invasive component and upgraded DCIS. We demonstrated the potential of using deep learning models for differentiating between upgraded versus pure DCIS in DCIS diagnosed by core-needle biopsy. Preoperative axial dynamic contrast-enhanced magnetic resonance imaging (MRI) data from 352 lesions were used to train, validate, and test three different types of deep learning models. The highest performance was achieved by Recurrent Residual Convolutional Neural Network using Regions of Interest (ROIs) with an accuracy of 75.0% and area under the receiver operating characteristic curve (AUC) of 0.796. Our results suggest that the deep learning approach may provide an assisting tool to predict the histologic upgrade of DCIS and provide personalized treatment strategies to patients with underestimated invasive disease.

Prediction of the histologic upgrade of ductal carcinoma in situ using a combined radiomics and machine learning approach based on breast dynamic contrast-enhanced magnetic resonance imaging

Objective

To investigate whether support vector machine (SVM) trained with radiomics features based on breast magnetic resonance imaging (MRI) could predict the upgrade of ductal carcinoma in situ (DCIS) diagnosed by core needle biopsy (CNB) after surgical excision.

Materials and methods

This retrospective study included a total of 349 lesions from 346 female patients (mean age, 54 years) diagnosed with DCIS by CNB between January 2011 and December 2017. Based on histological confirmation after surgery, the patients were divided into pure (n = 198, 56.7%) and upgraded DCIS (n = 151, 43.3%). The entire dataset was randomly split to training (80%) and test sets (20%). Radiomics features were extracted from the intratumor region-of-interest, which was semi-automatically drawn by two radiologists, based on the first subtraction images from dynamic contrast-enhanced T1-weighted MRI. A least absolute shrinkage and selection operator (LASSO) was used for feature selection. A 4-fold cross validation was applied to the training set to determine the combination of features used to train SVM for classification between pure and upgraded DCIS. Sensitivity, specificity, accuracy, and area under the receiver-operating characteristic curve (AUC) were calculated to evaluate the model performance using the hold-out test set.

Results

The model trained with 9 features (Energy, Skewness, Surface Area to Volume ratio, Gray Level Non Uniformity, Kurtosis, Dependence Variance, Maximum 2D diameter Column, Sphericity, and Large Area Emphasis) demonstrated the highest 4-fold mean validation accuracy and AUC of 0.724 (95% CI, 0.619-0.829) and 0.742 (0.623-0.860), respectively. Sensitivity, specificity, accuracy, and AUC using the test set were 0.733 (0.575-0.892) and 0.7 (0.558-0.842), 0.714 (0.608-0.820) and 0.767 (0.651-0.882), respectively.

Conclusion

Our study suggested that the combined radiomics and machine learning approach based on preoperative breast MRI may provide an assisting tool to predict the histologic upgrade of DCIS.

Diffusion-weighted Breast MRI in Prediction of Upstaging in Women with Biopsy-proven Ductal Carcinoma in Situ

Background Accurate preoperative prediction of upstaging in women with biopsy-proven ductal carcinoma in situ (DCIS) is important for surgical planning, but published models using predictive MRI features remain lacking. Purpose To develop and validate a predictive model based on preoperative breast MRI to predict upstaging in women with biopsy-proven DCIS and to select high-risk women who may benefit from sentinel lymph node biopsy at initial surgery. Materials and methods Consecutive women with biopsy-proven DCIS who underwent preoperative 3.0-T breast MRI including dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) and who underwent surgery between June 2019 and March 2020 were retrospectively identified (development set) from an academic medical center. The apparent diffusion coefficients of lesions from DWI, lesion size and morphologic features on DCE MRI scans, mammographic findings, age, symptoms, biopsy method, and DCIS grade at biopsy were collected. The presence of invasive cancer and axillary metastases was determined with surgical pathology. A predictive model for upstaging was developed by using multivariable logistic regression and validated in a subsequent prospective internal validation set recruited between July 2020 and April 2021. Results Fifty-seven (41%) of 140 women (mean age, 53 years ± 11 [SD]) in the development set and 43 (41%) of 105 women (mean age, 53 years ± 10) in the validation set were upstaged after surgery. The predictive model combining DWI and clinical-pathologic factors showed the areas under the receiver operating characteristic curve at 0.87 (95% CI: 0.80, 0.92) in the development set and 0.76 (95% CI: 0.67, 0.84) in the validation set. The predicted probability of invasive cancer showed good interobserver agreement (intraclass correlation coefficient, 0.79); the positive predictive value was 85% (28 of 33), and the negative predictive value was 92% (22 of 24). Conclusion A predictive model based on diffusion-weighted breast MRI identified women at high risk of upstaging. © RSNA, 2022 Online supplemental material is available for this article See also the editorial by Baltzer in this issue.

Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer

Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) may be diagnosed with invasive breast cancer after excision. We evaluated the preoperative clinical and imaging predictors of DCIS that were associated with an upgrade to invasive carcinoma on final pathology and also compared the diagnostic performance of various statistical models. We reviewed the medical records; including mammography, ultrasound (US), and magnetic resonance imaging (MRI) findings; of 644 patients who were preoperatively diagnosed with DCIS and who underwent surgery between January 2012 and September 2018. Logistic regression and three machine learning methods were applied to predict DCIS underestimation. Among 644 DCIS biopsies, 161 (25%) underestimated invasive breast cancers. In multivariable analysis, suspicious axillary lymph nodes (LNs) on US (odds ratio [OR], 12.16; 95% confidence interval [CI], 4.94-29.95; P < 0.001) and high nuclear grade (OR, 1.90; 95% CI, 1.24-2.91; P = 0.003) were associated with underestimation. Cases with biopsy performed using vacuum-assisted biopsy (VAB) (OR, 0.42; 95% CI, 0.27-0.65; P < 0.001) and lesion size <2 cm on mammography (OR, 0.45; 95% CI, 0.22-0.90; P = 0.021) and MRI (OR, 0.29; 95% CI, 0.09-0.94; P = 0.037) were less likely to be upgraded. No significant differences in performance were observed between logistic regression and machine learning models. Our results suggest that biopsy device, high nuclear grade, presence of suspicious axillary LN on US, and lesion size on mammography or MRI were independent predictors of DCIS underestimation.

The characteristics associated with upgrade on surgical pathology of conventional imaging occult DCIS diagnosed by MRI

PURPOSE

To characterize the clinical, pathological, and imaging features of DCIS occult on conventional imaging diagnosed on MRI-guided biopsy associated with increased risk of invasive disease on surgical excision.

MATERIALS AND METHODS

All consecutive patients with MRI-detected DCIS occult on conventional imaging between January 2009 and December 2018 were included. Women were divided into two groups based on final pathology: Pure DCIS or DCIS with invasive component. Clinical, imaging, and pathological risk factors for upgrade to invasion were evaluated.

RESULTS

Of 50 patients who met the inclusion criteria, 12 (24%) were upgraded to invasive malignancy in the final pathology. The only parameters that showed statistically significant association with upgrade were related to kinetic characteristics: 53% of patients with the combination of fast early upstroke and either plateau or washout curve were upgraded, compared to 12% of women without this combination (p = 0.006). The sensitivity of combined kinetic features for predicting upgrade was 67% (95% CI 35-90%), specificity was 84% (CI 95% 68-94%), positive predictive value was 57% (CI 95% 37-75%), negative predictive value was 89% (CI 95% 77-95%), and OR was 78% (64-88%).

CONCLUSION

Kinetic characteristics show the strongest association with upgrade to invasion in DCIS occult on mammogram and US. Larger studies should be encouraged to consolidate our findings, which may have implication for treatment planning.

Clinicopathological Follow-up of Breast DCIS Diagnosed on Biopsies: A Single Institutional Study of 575 Patients

Stratifying ductal carcinoma in situ (DCIS) patients into different upgrading risk groups is important in exploiting more precise therapeutic options. Evaluation of estrogen receptor/progesterone receptor/human epidermal growth factor receptor 2 (ER/PR/HER2) status and axillary lymph node metastatic status for DCIS and their upgraded invasive counterparts can also provide diagnostic and therapeutic implications. We retrospectively studied 575 patients with first-time diagnosis of DCIS on biopsies, and followed up their final diagnosis, ER/PR/HER2 status, and axillary lymph node involvement on excisions. As a result, biopsy-diagnosed DCIS had an overall 19.1% risk to be upgraded on subsequent excisions, with 4.7% being upgraded to microinvasive carcinoma (pT1mi) and 14.4% to overt invasive carcinoma (⩾pT1a). Factors significantly associated with higher upgrading risk on multivariate analysis include biopsy guidance by ultrasound (P <.001), DCIS with suspicious microinvasion (P < .001), and DCIS diagnosed in left breast (P = .026). DCIS diagnosed in younger patients (⩽40 years old) or DCIS with high nuclear grade showed higher upgrading risk only on univariate analysis. About 80% ER + /PR + and ER-/PR- DCIS remained the same ER/PR status after being upgraded, and ER + /PR -  DCIS had the highest risk (63.6%) of having HER2 amplification in upgraded invasive carcinoma. For upgraded DCIS, microinvasive carcinoma was more likely to have HER2 amplification (50%) than overt invasive carcinoma (29.5%). Besides, pure DCIS had a low risk of axillary lymph node macrometastasis (0.74%), while the risk increased in DCIS with microinvasion (4.4%) and was highest in overt invasive carcinoma (14.7%). The findings of this study are clinically relevant with respect to criteria that might be used in selecting patients for de-escalation trials.

The appropriate number of preoperative core needle biopsy specimens for analysis in breast cancer

Ultrasound (US)-guided core needle biopsy (CNB) has been recognized as a crucial diagnostic tool for breast cancer. However, there is a lack of guidance for hospitals that are not equipped with adjunctive US. The aim of this study was to assess the sensitivity, specificity, and experience of freehanded CNB in the outpatient department, and to determine the minimum number of tissue strips required to obtain concordance for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), and tumor grade with the excised specimen.A prospective study was performed on 95 patients undergoing CNB and subsequent surgical procedures. The reliability of immunohistochemical assessments of the pathological type, tumor grade, ER, PR, and HER2 status in CNBs was compared with that of surgical specimens. Concordance between the CNBs and surgical samples was estimated as a percentage agreement, and analyzed using the chi-square test. A P < .05 was considered significant.The concordance rates of ER, PR, and HER2 status and tumor grade status between CNBs and surgically excised specimens were 97.9%, 91.6%, 82.1%, and 84.2%, respectively. The reliability of taking 2 tissue strips was similar to that of taking six tissue strips in distinguishing malignancy from benignancy, and determining the pathological type without the aid of US. Four tissue strips obtained by CNB showed good accuracy comparable to those obtained by surgical specimens in assessing ER, PR, and HER2 status and tumor grade.Two tissue strips obtained by CNB showed good accuracy in differentiating malignancy from benignancy, while at least 4 strips are recommended to obtain overall conformity of pathological biomarkers.

Necessity of sentinel lymph node biopsy in ductal carcinoma in situ patients: a retrospective analysis

BACKGROUND

Sentinel lymph node biopsy (SLNB) is unnecessarily performed too often, owing to the high upstaging rates of ductal carcinoma in situ (DCIS). This study aimed to evaluate the upstaging rates of DCIS to invasive cancer, determine the prevalence of axillary lymph node metastasis, and identify the clinicopathological factors associated with upstaging and lymph node metastasis. We also examined surgical patterns among DCIS patients and determined whether SLNB guidelines were followed.

METHODS

We retrospectively analysed 307 consecutive DCIS patients diagnosed by preoperative biopsy in a single centre between 2014 and 2018. Data from clinical records, including imaging studies, axillary and breast surgery types, and pathology results from preoperative and postoperative biopsies, were extracted. Univariate analyses using Chi-square tests and multiple logistic regression analyses were used to analyse the data.

RESULTS

The rate of upstaging to invasive cancer was 19.2% (59/307). DCIS diagnosed by core-needle biopsy (odds ratio [OR]: 6.861, 95% confidence interval [CI]: 2.429-19.379), the presence of ultrasonic mass-forming lesions (OR: 2.782, 95% CI: 1.224-6.320), and progesterone receptor-negative status (OR: 3.156, 95% CI: 1.197-8.323) were found to be associated with upstaging. The rate of sentinel lymph node metastasis was only 1.9% (4/202), and all were total mastectomy patients diagnosed by core-needle biopsy. SLNB was performed in 37.2% of 145 breast-conserving surgery patients and 91.4% of 162 total mastectomy patients. Among the 202 patients who underwent SLNB, 145 (71.7%) without invasive cancer on final pathology had redundant SLNB. Two of 59 patients (3.4%) with disease upstaged to invasive cancer had inadequate primary staging of the axilla, as the rate seemed sufficiently small.

CONCLUSIONS

In patients with a preoperative diagnosis of DCIS, although an unavoidable possibility of upstaging to invasive cancer exists, axillary metastasis is unlikely. Only 2.7% of patients with DCIS undergoing total mastectomy were found to have sentinel lymph node metastases. SLNB should not be performed in breast-conserving surgery patients and should be reserved only for total mastectomy patients diagnosed by core-needle biopsy.

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

Background

To 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.

Methods

Of 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.

Results

Clinical 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.

Conclusions

The ultrasound-based deep learning prediction model is effective in predicting DCIS that will be upgraded postoperatively.

The usefulness of ultrafast MRI evaluation for predicting histologic upgrade of ductal carcinoma in situ

PURPOSE

The purpose of this study was to investigate the usefulness of ultrafast MRI with conventional dynamic contrast-enhanced (DCE)-MRI for predicting histologic upgrade of ductal carcinoma in situ (DCIS) to invasive cancer.

METHODS

This retrospective study enrolled 53 biopsy-proven DCIS lesions in 53 patients and divided into two groups based on postoperative histopathologic diagnoses: non-upgrade and upgrade to invasive cancer groups. Imaging features of conventional DCE-MRI and ultrafast MRI, and histopathologic features were reviewed and compared between the two groups. Interobserver agreements for MRI features were analyzed by two radiologists. The radiologic and histopathologic parameters for predicting histologic upgrade of DCIS were identified using multiple linear regression.

RESULTS

Seventeen lesions (32.1 %) were histologically upgraded to invasive cancer after surgery. The interobserver agreement for ultrafast MRI parameters was excellent, and maximum slope (MS) and maximum enhancement (ME) showed the highest reliability (intraclass correlation coefficients, 0.907 and 0.897, respectively). The upgrade group showed significantly larger lesion size on MRI (median 40 mm [25^th to 75^th percentiles 16.0-83.0] vs. 18.5 mm [10.0-29.8], p < 0.001), higher MS (12.1 %/s [8.2-13.9] vs. 8.7 %/s [6.4-11.1], p = 0.004), and higher ME (236.5 % [153.7-253.7] vs. 175.4 % [140.1-207.7], p = 0.027) than non-upgrade group. Lesion size (≥ 20 mm), MS (> 11.5 %), and ME (> 229.1 %) were significant predictors for histologic upgrade, which could predict 10 cases of histologic upgrade (10/17, 58.8 %) without a false-positive case.

CONCLUSION

Preoperative ultrafast MRI with conventional DCE-MRI could be useful in management decisions for DCIS patients.

Ductal Carcinoma In Situ (DCIS) at Breast MRI: Predictors of Upgrade to Invasive Carcinoma

RATIONALE AND OBJECTIVES

To determine the upgrade rate of magnetic resonance imaging (MRI)-detected ductal carcinoma in situ (DCIS) and to identify patient, imaging, and pathologic features that may predict the risk of upgrade.

MATERIALS AND METHODS

Medical chart review from January 2007 to December 2016 identified 60 patients with 61 cases of MRI-detected DCIS and negative mammographic evaluations within 1 year prior to the MRI. Imaging and pathology reports were reviewed. Standard statistical tests, including Student's t-tests and chi-square tests, were used to compare patient, imaging, and pathologic features between the cases of DCIS that did and did not upgrade to invasive carcinoma at surgery.

RESULTS

Over a 10-year period, 60 patients (mean age 52 years, range 30-76 years) were diagnosed with 61 cases of MRI-detected DCIS. Two-thirds of DCIS cases were detected on MRI examinations that were performed for purposes of high-risk screening (67.2%, 41/61). MRI features that led to the DCIS diagnosis were nonmass enhancement in 78.7% (48/61), enhancing mass in 16.4% (10/61), nonmass enhancement and enhancing mass in 3.3% (2/61), and enhancing focus in 1.6% (1/61). Thirteen cases (21.3%, 13/61) were upgraded to invasive ductal carcinoma at surgery. DCIS cases that upgraded were larger on MRI (40 mm vs 17 mm, p < 0.01) and more likely to be associated with comedonecrosis at biopsy (38.5% [5/13] vs 6.3% [3/48], p < 0.01).

CONCLUSION

The upgrade rate of MRI-detected DCIS to invasive ductal carcinoma at surgery is 21.3%. Features that are associated with upgrade include large size on MRI and the presence of comedonecrosis at biopsy.

The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ

Background

The upgrade rate of biopsy-confirmed ductal carcinoma in situ (DCIS) to invasive carcinoma is up to 50% on final pathology. We investigated MRI and clinicopathologic predictors of the invasive components of DCIS diagnosed by preoperative biopsy and then compared MRI features between patients with DCIS, microinvasive ductal carcinoma (mIDC), and invasive ductal carcinoma (IDC) diagnosed on final pathology.

Methods

Two hundred and one patients with 206 biopsy-confirmed DCIS lesions were enrolled. MRI and clinicopathologic features were used to predict either mIDC or IDC via a cumulative logistic regression analysis. For the lesions detected on MRI, morphologic and kinetic analyses were performed using the Chi-square, Fisher’s exact, and Kruskal-Wallis tests.

Results

Of all the lesions, 112 (54.4%) were diagnosed as DCIS, 50 (24.3%) were upgraded to mIDC, and 44 (21.4%) to IDC. The detection on MRI as mass (Odds ratio (OR) = 8.84, 95% confidence interval (CI) = 1.05–74.04, P = 0.045) or non-mass enhancement (NME; OR = 11.17, 95% CI = 1.35–92.36, P = 0.025), negative progesterone receptor (PR; OR = 2.40, 95% CI = 1.29–4.44, P = 0.006), and high Ki-67 level (OR = 2.42, 95% CI = 1.30–4.50, P = 0.005) were significant independent predictors of histologic upgrade. On MRI, 87 (42.2%) lesions appeared as mass and 107 (51.9%) as NME. Irregularly shaped, not-circumscribed, heterogeneous, or rim-enhancing masses with intratumoral high signal intensity or peritumoral edema, clumped or clustered ring-enhancing NMEs, and high peak enhancement were significantly associated with histologic upgrade (P < 0.001).

Conclusion

MRI detection, negative PR, and high Ki-67 levels are associated with a histologic upgrade in patients with biopsy-confirmed DCIS. Suspicious MRI features are more frequent in such patients.

Application of magnetic resonance computer-aided diagnosis for preoperatively determining invasive disease in ultrasonography-guided core needle biopsy-proven ductal carcinoma in situ

The aim of this study was to analyze kinetic and morphologic features using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with computer-aided diagnosis (CAD) to predict occult invasive components in cases of biopsy-proven ductal carcinoma in situ (DCIS).We enrolled 138 patients with 141 breasts who underwent preoperative breast MRI and were diagnosed with DCIS via ultrasonography (US)-guided core needle biopsy performed at our institution during January 2009 to December 2012. Their clinical, mammographic, ultrasonographic, MRI, and final histologic findings were retrospectively reviewed. Their mammographic, ultrasonographic, and MRI findings were analyzed according to the American College of Radiology Breast Imaging Reporting and Data System. CAD findings of detectability, initial (fast, medium, and slow) and delay (persistent, plateau, and washout) phase enhancement kinetic descriptor, peak enhancement percentage, and lesion size were evaluated. Continuous and categorical variables were analyzed using independent t test and χ or Fisher exact test, respectively. Independent factors for predicting the presence of invasive component were evaluated by multivariate logistic regression analysis.Final histologic findings revealed that 55 breasts (39%) had DCIS with an invasive component. MRI-detected, CAD-detected, or pathologic lesion size (P = .002, P = .001, P < .001, respectively), delay washout kinetics and detectability on CAD (P < .001 and P = .004, respectively), presence of symptoms (P = .01), presence of comedonecrosis (P < .001), nuclear grade (P = .001), abnormality on mammography (P = .02), or US (P = .03) were significantly different between pure DCIS and the DCIS with an invasive component group on univariate analysis. Of those findings, multivariate analysis revealed that delay washout on CAD (odds ratio [OR], 4.36; 95% confidence interval [CI], 1.96-9.69; P = .0003) and pathologic size (OR, 1.29; 95% CI 1.05-1.57; P = .014) were independent predictive factors for the presence of an invasive component.Delay washout kinetic features measured by CAD and pathologic tumor size are potentially useful for predicting occult invasion in cases of biopsy-proven DCIS.Breast MRI including a CAD system would be helpful for predicting invasive components in cases of biopsy-proven DCIS and for selecting patients for sentinel lymph node biopsy.

Surgical Outcomes for Ductal Carcinoma in Situ: Impact of Preoperative MRI

Background The role of preoperative MRI for predicting surgical outcomes in patients diagnosed with ductal carcinoma in situ (DCIS) remains uncertain. Purpose To investigate the associations between preoperative MRI and surgical outcomes in DCIS confirmed by using US-guided core-needle biopsy (CNB) and to evaluate clinical-pathologic variables associated with a benefit from MRI. Materials and Methods Women with DCIS confirmed by using US-guided CNB between January 2012 and December 2016 were included in this retrospective study. Propensity score matching using 18 confounding covariates was used to create matched groups with MRI and without MRI, and surgical outcomes were compared. Clinical-pathologic variables were evaluated to determine women who benefited from MRI. Results A total of 541 women (mean age ± standard deviation, 50 years ± 10) were evaluated. Among 430 women who underwent MRI, 67 additional lesions (16%) were depicted, with 25 (37%) of the 67 additional lesions being malignant. Fifty-seven (13%) of the 430 women had a change in surgical plan because of their MRI findings; the change was appropriate for 31 (54%) women. In matched groups, the MRI group was associated with lower odds of positive resection margin (odds ratio [OR], 0.39; 95% confidence interval [CI]: 0.16, 0.93; P = .03) and repeat surgery (OR, 0.33; 95% CI: 0.12, 0.92; P = .03) compared with the non-MRI group. There was no difference in likelihood of initial mastectomy (OR, 1.2; 95% CI: 0.7, 2.0; P = .59) and overall mastectomy (OR, 0.93; 95% CI: 0.5, 1.6; P = .79). In the MRI group, low nuclear grade (90% [28 of 31] vs 69% [275 of 399]; P = .01), progesterone receptor positivity (81% [25 of 31] vs 61% [244 of 399]; P = .03), and human epidermal growth factor receptor 2 negativity (90% [28 of 31] vs 68% [270 of 399]; P = .01) were associated with a benefit from MRI versus no MRI. Conclusion Preoperative MRI depicted additional malignancy and reduced positive surgical margins and repeat surgery for ductal carcinoma in situ confirmed at US-guided biopsy without a higher mastectomy rate. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Pinker in this issue.

Multicentre study of the risk of invasive cancer and use of sentinel node biopsy in women with a preoperative diagnosis of ductal carcinoma in situ

Background

Ductal carcinoma in situ (DCIS) in the breast that is diagnosed by biopsy implies a risk of upstaging to invasive carcinoma (IC) on final pathology. These patients require a sentinel lymph node biopsy (SLNB) for axillary staging. A two-stage procedure is not always feasible and precise selection of patients who should be offered SLNB is crucial. The aims were: to determine the rate of upstaging, and use of redundant and required SLNB in women with a preoperative diagnosis of DCIS; and to identify patient and tumour characteristics that increase the risk of upstaging.

Methods

Patients with DCIS treated between 2008 and 2016 were identified using Orbit operation planning system software, and those suitable for the study were selected based on review of the medical records. Upstaging rates and proportions of redundant and required SLNBs were calculated. Associations between clinicopathological characteristics and upstaging were analysed using univariable and multivariable logistic regression analyses.

Results

Of 1368 patients initially identified, 975 women with a preoperative diagnosis of DCIS were included in the study. Tumours in 246 of these patients (25·2 per cent) were upstaged to IC. Redundant SLNB was performed in 392 of 975 women (40·2 per cent). Forty-four patients (4·5 per cent) with a final diagnosis of IC were not offered SLNB and thus potentially undertreated. In adjusted analysis, DCIS size, palpability and mass formation identified by breast imaging were associated with increased risk of upstaging. The Van Nuys classification was not associated with upstaging.

Conclusion

Most patients with IC on final pathology underwent SLNB, but a considerable number of patients with DCIS had a redundant SLNB. Lesion size, palpability and mass formation, but not Van Nuys classification group, are suggested risk factors for upstaging.

Predictive factors for the presence of invasive components in patients diagnosed with ductal carcinoma in situ based on preoperative biopsy

Background

In patients diagnosed with ductal carcinoma in situ (DCIS) with needle biopsy before surgery, invasive component (IC) is often found in the postoperative tissue, which results in altered post-surgical care. However, there are no clinically available factors to predict IC, and few MRI studies are available for the detection of IC in DCIS patients. The purpose of this study was to evaluate which risk factors can predict IC preoperatively.

Methods

Patients with a DCIS diagnosis based on preoperative biopsy, who underwent breast surgery Kangbuk Samsung Hospital between Jan 2005 and June 2018, were retrospectively evaluated. Clinico-pathological and breast MRI factors were compared between DCIS and DCIS with IC in postsurgical specimens.

Results

Of the 431 patients with a preoperative diagnosis of DCIS, 34 (7.9%) showed IC during the postoperative pathological investigations, and 217 (50.3%) underwent breast MRI. Among MRI-related factors, Mass-like enhancement on MRI was the sole but significant predictor of IC (HR = 0.26, C.I. = 0.07–0.93, p = 0.038), while nipple-areolar complex invasion, enhancement peak and pattern were not statistically significant. Nuclear grade was the only significant predictor of IC in the analysis of other clinico-pathological factors (HR = 2.39, C.I. = 1.05–5.42, p = 0.038 in univariate analysis, HR = 2.86, C.I. = 1.14–7.14, p = 0.025 in multivariate analysis).

Conclusions

Mass-like enhancement on MRI and high nuclear grade were associated with IC in patients with preoperative diagnosis of DCIS. Considering the high sensitivity of breast MRI for IC, further evaluation of the predictive value of MRI in preoperative DCIS patients is desirable.

Ductal carcinoma in situ of breast: update 2019

Ductal carcinoma in situ is a non-invasive form of breast cancer. Its incidence is increasing due to widespread use of mammographic screening. It presents several diagnostic and management challenges in part due to its relatively indolent behaviour. Most series analysing biomarkers in these lesions are small (<100 patients) and large clinical trials have not been frequent. Herein, we review the recent progress made in understanding the biology of this entity and the tools available for prognostication.

Breast lesions diagnosed by ultrasound-guided core needle biopsy: Can shearwave elastography predict histologic upgrade after surgery or vaccuum assisted excision?

PURPOSE

To compare breast stiffness based on shear-wave elastography (SWE) quantitative parameters with histopathologic results diagnosed by ultrasound (US)-guided core needle biopsy (CNB) to determine their association with upgrade rates after surgical excision or follow-up US as well as clinico-radiologic differences between upgrade and non-upgrade groups.

MATERIALS AND METHODS

This retrospective study enrolled 225 breast lesions from 225 patients, including 159 benign lesions, 38 high risk lesions and 28 ductal carcinoma in situ (DCIS) diagnosed by US-guided CNB. Quantitative SWE parameters of breast lesions were measured before CNB and compared according to histopathologic results (benign, high risk and DCIS) and lesion size (<20 mm and >20 mm). Clinico-radiologic and pathologic factors were compared between upgrade and non-upgrade groups after surgical excision or follow-up US.

RESULTS

After surgical excision or follow-up US after more than one year, 29 lesions were upgraded for an overall upgrade rate of 12.9% (29/225). There were significant differences between upgrade and non-upgrade groups in age, mammographic category, US category, and sonographic features, including shape, margin, orientation, imaging-histologic correlation and E ratio. Patients with lesion upgrade were much older and had lesions characterized by significantly higher mammographic and US category (>4b), irregular shape, nonparallel orientation, microlobulated or angular margin, calcification in a mass, larger size on US (>20 mm) and greater imaging-histologic discordance. Multivariate analysis showed only mean and minimum elasticity values displayed a borderline association with histologic underestimation.

CONCLUSION

Upgrade of breast lesions diagnosed by US-guided CNB can be predicted using E_mean and E_min among quantitative SWE parameters.

The usefulness of fluorodeoxyglucose-PET/CT for preoperative evaluation of ductal carcinoma in situ

Purpose

PET/CT is useful in preoperative evaluation of invasive breast cancer (IBC) to predict axillary metastasis and staging workup. The usefulness is unclear in cases of ductal carcinoma in situ (DCIS) diagnosed at biopsy before surgery, which sometimes is upgraded to IBC after definitive surgery. The aim of this study is to find out the usefulness of PET/CT on DCIS as a preoperative evaluation tool.

Methods

We investigated 102 patients preoperatively diagnosed with DCIS who subsequently underwent definitive surgery between 2010 and 2015. The uptake of ¹⁸F-fluorodeoxyglucose was graded by visual and semiquantitative methods. We analyzed the maximum standardized uptake value (SUVmax) of each patient with clinicopathologic variables. We determined optimal cutoff values for SUVmax by receiver operating characteristic curve analysis.

Results

Fifteen cases out of 102 cases (14.7%) were upgraded to IBC after surgery. The SUVmax was higher in patients upgraded to IBC (mean: 2.56 vs. 1.36) (P = 0.007). The SUVmax was significantly higher in patients who had symptoms, palpable masses, lesions over 2 cm in size and BI-RAD category 5. Both visual and semiquantitative analysis were significant predictors of IBC underestimation. SUVmax of 2.65 was the theoretical cutoff value in ROC curve analysis in predicting the underestimation of IBC. The underestimation rate was significantly higher in patients with SUVmax >2.65 (P < 0.001), over the moderate enhanced uptake on visual analysis (P < 0.001).

Conclusion

PET/CT can be used as a complementary evaluation tool to predict the underestimation of DCIS combined with the lesion size, palpable mass, symptomatic lesion, and BI-RAD category.

Current approach and future perspective for ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) has a good prognosis with the current treatment approach, with a 10-year breast cancer-specific survival rate of 97-98%. In ductal carcinoma in situ without micrometastasis, surgery and postoperative adjuvant therapy significantly improve local control, however it has been reported that the selection of the surgical procedure and adjuvant therapy does not influence breast cancer death. On the other hand, owing to widespread mammography screening, the frequency of early breast cancer detection has increased. In early breast cancer, increased incidence of DCIS is remarkable. However, there is not enough reduction of advanced cancer to match it. Problems with overdiagnosis are now being discussed all over the world. It has been reported that surgery for low-grade ductal carcinoma in situ does not contribute to breast cancer-specific survival. However, it is currently impossible to reliably identify a population that does not progress to invasive cancer even without treatment. Recently, a non-surgery clinical trial for low-risk ductal carcinoma in situ was started. There is a possibility of achieving individualized treatment for ductal carcinoma in situ with less treatment intervention, without compromising the good prognosis obtained with the current treatment approach. This review presents an overview of the current treatment approaches, problems with overdiagnosis and potential future management strategies for ductal carcinoma in situ of the breast.

Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?

PURPOSE

To assess the ability of algorithmically assessed magnetic resonance imaging (MRI) features to predict the likelihood of upstaging to invasive cancer in newly diagnosed ductal carcinoma in situ (DCIS).

MATERIALS AND METHODS

We identified 131 patients at our institution from 2000-2014 with a core needle biopsy-confirmed diagnosis of pure DCIS, a 1.5 or 3T preoperative bilateral breast MRI with nonfat-saturated T1 -weighted MRI sequences, no preoperative therapy before breast MRI, and no prior history of breast cancer. A fellowship-trained radiologist identified the lesion on each breast MRI using a bounding box. Twenty-nine imaging features were then computed automatically using computer algorithms based on the radiologist's annotation.

RESULTS

The rate of upstaging of DCIS to invasive cancer in our study was 26.7% (35/131). Out of all imaging variables tested, the information measure of correlation 1, which quantifies spatial dependency in neighboring voxels of the tumor, showed the highest predictive value of upstaging with an area under the curve (AUC) = 0.719 (95% confidence interval [CI]: 0.609-0.829). This feature was statistically significant after adjusting for tumor size (P < 0.001).

CONCLUSION

Automatically assessed MRI features may have a role in triaging which patients with a preoperative diagnosis of DCIS are at highest risk for occult invasive disease.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1332-1340.

Diagnostic value of endoscopic appearance during ductoscopy in patients with pathological nipple discharge

Background

To explore the features of ductoscopic appearance that may be diagnostic in patients with pathologic nipple discharge (PND) and to discuss the diagnostic criteria for intraductal tumors.

Methods

We reviewed 247 patients with PND but without a palpable mass who were evaluated using either surgical biopsy or excision. Data concerning patient age, duration of discharge, discharge color, and the details of endoscopic appearance were analyzed according to the pathological results.

Results

The postoperative diagnosis in 61 patients (24.70%) was a nonmass lesion, and 186 patients (76.52%) had an intraductal tumor. Among those with intraductal lesions, 10 patients (4.05%) had a malignant tumor, including 4 (1.62%) with ductal carcinoma in situ and 6 (2.43%) with invasive ductal carcinoma. On univariate analysis, patients of older age with spontaneous and bloody discharge were more likely to suffer from intraductal lesions. On logistic regression analysis, bloody nipple discharge, morphology, and a broad lesion base revealed by ductoscopy showed a statistically significant correlation with malignancy (p = 0.001, p < 0.001, p = 0.022, respectively).

Conclusions

Both clinical features and endoscopic appearance are significant for the precise diagnosis of an intraductal lesion seen on ductoscopy. The endoscopic features of bloody discharge, morphology, and a broad lesion base are independent risk factors for malignancy and represent new criteria for the diagnosis of patients with PND.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3288-3) contains supplementary material, which is available to authorized users.

Comparison of the accuracy of US-guided biopsy of breast masses performed with 14-gauge, 16-gauge and 18-gauge automated cutting needle biopsy devices, and review of the literature

OBJECTIVE

To compare the diagnostic accuracy of ultrasound (US)-guided core needle biopsy (CNB) of breast masses performed with 14-gauge, 16-gauge and 18-gauge needles.

METHODS

We retrospectively reviewed the charts of 1,112 patients who underwent US-guided breast CNB with 14-gauge, 16-gauge and 18-gauge needles. Cases with surgical excision or a minimum of 2 years of imaging follow-up were included. Rates of sample inadequacy, discordance with surgical or imaging findings and upgrade of DCIS to invasive cancer or high-risk lesion to in situ or invasive cancer were computed for each needle size.

RESULTS

The study included 703 CNBs: 203 performed with 14-gauge, 235 with 16-gauge and 265 with 18-gauge needles. There were no significant differences between 14-gauge, 16-gauge and 18-gauge needles in rates of specimen inadequacy (0 %, 0.4 % and 1.9 %, respectively) (p = 0.084); surgical discordance (2.6 %, 2.9 % and 3.8 %) (p = 0.76); imaging discordance (0 %, 0 % and 2 %) (p = 1.0); DCIS upgrade (43 %, 43 % and 36 %) (p = 1.00) or high-risk lesion upgrade (38 %, 25 % and 55 %) (p = 0.49).

CONCLUSION

There was no statistically significant difference in diagnostic accuracy of US-guided CNB of breast masses performed with 14-gauge, 16-gauge and 18-gauge needles.

KEY POINTS

• Percutaneous image-guided breast core needle biopsy (CNB) is the standard of care. • Breast CNB with 14-gauge, 16-gauge and 18-gauge needles has similar diagnostic accuracy. • Smaller gauge needles can be confidently used for ultrasound-guided breast CNB.

Stiffness at shear-wave elastography and patient presentation predicts upgrade at surgery following an ultrasound-guided core biopsy diagnosis of ductal carcinoma in situ

AIM

The aim of this study is to establish predictors of invasion in lesions yielding an ultrasound-guided biopsy diagnosis of ductal carcinoma in situ (DCIS).

MATERIALS AND METHODS

Patients subjected to ultrasound-guided core biopsy yielding DCIS were studied. At shear-wave elastography (SWE) a threshold of 50 kPa was used for mean elasticity (Emean) to dichotomise the elasticity data between invasive and non-invasive masses. Data recorded included the mammographic and ultrasound features, the referral source, and grade of DCIS in the biopsy. The chi-square test was used to detect statistical significance.

RESULTS

Of 57 lesions, 24 (42%) had invasion at excision. Symptomatic patients and patients with stiff lesions were more likely to have invasion than patients presenting through screening and with soft lesions (58% [14 of 24] versus 30% [10 of 33], p=0.03) and (51% [20 of 39] versus 22% [4 of 18], p=0.04). No other factors showed a relationship with invasion. Combining the two predictors of invasion improved risk stratification with symptomatic and stiff lesions having a risk of invasion of 67% (12 of 18) and soft lesions presenting at screening having only a 17% (2 of 12) risk of invasion (p=0.02).

CONCLUSION

Stiffness on SWE and the referral source of the patient are predictors of occult invasion in women with an ultrasound-guided core biopsy diagnosis of DCIS.

Ductal carcinoma in situ diagnosed by breast needle biopsy: Predictors of invasion in the excision specimen

BACKGROUND

A substantial proportion of women with a pre-operative diagnosis of pure ductal carcinoma in situ (DCIS) has a final diagnosis of invasive breast cancer (IBC) after surgical excision and, consequently, a potential indication for lymph node staging. The aim of our study was to identify novel predictors of invasion in patients with a needle-biopsy diagnosis of DCIS that would help us to select patients that may benefit from a sentinel node biopsy (SNB).

PATIENTS AND METHODS

We included 153 patients with a needle-biopsy diagnosis of DCIS between 2000 and 2014, which was followed by surgical excision. Several pre-operative clinical, radiological and pathological features were assessed and correlated with the presence of invasion in the excision specimen. Features that were significantly associated with upstaging in the univariable analysis were combined to calculate upstaging risks.

RESULTS

Overall, 22% (34/155) of the patients were upstaged to IBC. The following risk factors were significantly associated with upstaging: palpability, age ≤40 years, mammographic mass lesion, moderate to severe periductal inflammation and periductal loss of decorin expression. The upstaging-risk correlated with the number of risk factors present: e.g. 9% for patients without risk factors, 29% for patients with 1 risk factor, 37% for patients with 2 risk factors and 54% for patients with ≥3 risk factors.

CONCLUSION

The identified risk factors may be helpful to predict the upstaging-risk for patients with a needle-biopsy diagnosis of pure DCIS, which facilitates the performance of a selective SNB for high-risk patients and avoid this procedure in low-risk patients.

Preoperative clinicopathologic factors and breast magnetic resonance imaging features can predict ductal carcinoma in situ with invasive components

PURPOSE

Ductal carcinoma in situ (DCIS) is a non-invasive cancerous breast lesion; however, from 10% to 50% of patients with DCIS diagnosed by core needle biopsy (CNB) or vacuum-assisted core biopsy (VACB) are shown to have invasive carcinoma after surgical excision. In this study, we evaluated whether preoperative clinicopathologic factors and breast magnetic resonance image (MRI) features are predictive of DCIS with invasive components before surgery.

MATERIALS AND METHODS

Patients comprised 128 adult women with a diagnosis of DCIS as determined by pathological analysis of CNB or VACB specimens and positive MRI findings who underwent breast surgery during the period January 2011 to December 2013 at the Changhua Christian Hospital. Clinicopathologic and breast MRI factors were compared between patients with postoperative pathology indicative of true DCIS and those with postoperative pathology showing DCIS with invasive components.

RESULTS

Of the 128 patients with a preoperative diagnosis of DCIS, 73 (57.0%) had postoperative histopathologic evidence of true DCIS and 55 (43.0%) showed evidence of DCIS with invasive components. Results of statistical analyses revealed that MRI evidence of a mass-like lesion (P=0.025), nipple-areolar complex (NAC) invasion (P=0.029), larger tumor volume (P=0.010), larger maximum measurable apparent diffusion coefficient (ADC) area (P=0.039), heterogenous or rim enhancement pattern (P=0.010), as well as immunohistochemical evidence of human epidermal growth factor receptor 2 (HER-2) overexpression (P=0.010) were predictive of DCIS with an invasive component in postoperative surgical specimens.

CONCLUSION

Invasive component should be considered in biopsy proven DCIS patients with preoperative MRI evidence of a mass-like lesion, nipple-areolar complex invasion, large tumor volume, a larger maximum measurable ADC area, or a rim or heterogenous enhancement pattern, as well as in patients with immunohistochemical evidence of HER-2 overexpression.

Lesion stiffness measured by shear-wave elastography: Preoperative predictor of the histologic underestimation of US-guided core needle breast biopsy

OBJECTIVES

To determine whether lesion stiffness measured by shear-wave elastography (SWE) can be used to predict the histologic underestimation of ultrasound (US)-guided 14-gauge core needle biopsy (CNB) for breast masses.

METHODS

This retrospective study enrolled 99 breast masses from 93 patients, including 40 high-risk lesions and 59 ductal carcinoma in situ (DCIS), which were diagnosed by US-guided 14-gauge CNB. SWE was performed for all breast masses to measure quantitative elasticity values before US-guided CNB. To identify the preoperative factors associated with histologic underestimation, patients' age, symptoms, lesion size, B-mode US findings, and quantitative SWE parameters were compared according to the histologic upgrade after surgery using the chi-square test, Fisher's exact test, or independent t-test. The independent factors for predicting histologic upgrade were evaluated using multivariate logistic regression analysis.

RESULTS

The underestimation rate was 28.3% (28/99) in total, 25.0% (10/40) in high-risk lesions, and 30.5% (18/59) in DCIS. All elasticity values of the upgrade group were significantly higher than those of the non-upgrade group (P<0.001). On multivariate analysis, the mean (Odds ratio [OR]=1.021, P=0.001), maximum (OR=1.015, P=0.008), and minimum (OR=1.028, P=0.001) elasticity values were independently associated with histologic underestimation. The patients' age, lesion size, and final assessment category on US of the upgrade group were higher than those of the non-upgrade group (P=0.046 for age; P=0.021 for lesion size; P=0.030 for US category), but these were not independent predictors of histologic underestimation on multivariate analysis.

CONCLUSION

Breast lesion stiffness quantitatively measured by SWE could be helpful to predict the underestimation of malignancy in US-guided 14-gauge CNB.

Sentinel Lymph Node Biopsy Should Be Included with the Initial Surgery for High-Risk Ductal Carcinoma-In-Situ

Background. A proportion of those diagnosed preoperatively with ductal carcinoma-in-situ (DCIS) will be histologically upgraded to invasive carcinoma. Repeat surgery for sentinel lymph node (SLN) biopsy will be required if it had not been included with the initial surgery. We reviewed the outcome of SLN biopsy performed with the initial surgery based on a preoperative diagnosis of DCIS and aimed to identify patients at risk of histological upgrade. Methods. Retrospective review of 294 consecutive female patients diagnosed with DCIS was performed at our institute from January 1, 2001, to December 31, 2008. Results. Of the 294 patients, 132 (44.9%) underwent SLN biopsy together with the initial surgery. The SLN was positive for metastases in 5 patients, all of whom had tumours that were histologically upgraded. Histological upgrade also occurred in 43 of the 127 patients (33.9%) in whom the SLN was negative for metastases. On multivariate analysis, histological upgrade was more likely if a mass was detected on mammogram, if the preoperative diagnosis was obtained with core biopsy and if microinvasion was reported in the biopsy. Conclusion. Patients in whom a preoperative diagnosis of DCIS is likely to be upgraded to invasive carcinoma will benefit from SLN biopsy being performed with the initial surgery.