Assessment of the extent of microcalcifications to predict the size of a ductal carcinoma in situ: comparison between tomosynthesis and conventional mammography

Radiological Underestimation of Tumor Size as a Relevant Risk Factor for Positive Margin Rate in Breast-Conserving Therapy of Pure Ductal Carcinoma In Situ (DCIS)

Background: Radiological underestimation of the actual tumor size is a relevant problem in reaching negative margins in ductal carcinoma in situ (DCIS) associated with microcalcifications in breast-conserving therapy (BCT). The aim of this study is to evaluate whether the radiological underestimation of tumor size has an influence on the histopathological margin status. Methods: Patients who underwent BCT with preoperatively diagnosed pure DCIS were included (pooled analysis of two trials). Multiple factors were analysed regarding radiological underestimation ≥10 mm. Radiological underestimation was defined as mammographic minus histological tumor size in mm. Results: Positive margins occurred in 75 of 189 patients. Radiological underestimation ≥10 mm was an independent influencing factor (OR 5.80; 95%CI 2.55−13.17; p < 0.001). A radiological underestimation was seen in 70 patients. The following parameters were statistically significant associated with underestimation: pleomorphic microcalcifications (OR 3.77; 95%CI 1.27−11.18), clustered distribution patterns (OR 4.26; 95%CI 2.25−8.07), and mammographic tumor sizes ≤20 mm (OR 7.47; 95%CI 3.49−15.99). Only a mammographic tumor size ≤20 mm was an independent risk factor (OR 6.49; 95%CI 2.30−18.26; p < 0.001). Grading, estrogen receptor status, and comedo necrosis did not influence the size estimation. Conclusion: Radiological underestimation is an independent risk factor for positive margins in BCT of DCIS associated with microcalcifications predominantly occurring in mammographic small tumors.

Radiomic Applications on Digital Breast Tomosynthesis of BI-RADS Category 4 Calcifications Sent for Vacuum-Assisted Breast Biopsy

Background: A fair amount of microcalcifications sent for biopsy are false positives. The study investigates whether quantitative radiomic features extracted from digital breast tomosynthesis (DBT) can be an additional and useful tool to discriminate between benign and malignant BI-RADS category 4 microcalcification. Methods: This retrospective study included 252 female patients with BI-RADS category 4 microcalcifications. The patients were divided into two groups according to micro-histopathology: 126 patients with benign lesions and 126 patients with certain or possible malignancies. A total of 91 radiomic features were extracted for each patient, and the 12 most representative features were selected by using the agglomerative hierarchical clustering method. The binary classification task of the two groups was carried out by using four different machine-learning algorithms (i.e., linear support vector machine (SVM), radial basis function (RBF) SVM, logistic regression (LR), and random forest (RF)). Accuracy, sensitivity, sensibility, and the area under the curve (AUC) were calculated for each of them. Results: The best performance was achieved using the RF classifier (AUC = 0.59, 95% confidence interval 0.57–0.60; sensitivity = 0.56, 95% CI 0.54–0.58; specificity = 0.61, 95% CI 0.59–0.63; accuracy = 0.58, 95% CI 0.57–0.59). Conclusions: DBT-based radiomic analysis seems to have only limited potential in discriminating benign from malignant microcalcifications.

Can digital breast tomosynthesis improve identification of malignant calcifications?

Digital breast tomosynthesis (DBT) is an emerging imaging tool for both the screening and diagnosis of breast cancers. However, the use of DBT in diagnosis of calcifications remains ambiguous. In this study, we investigated DBT findings that might help differentiate between benign and malignant calcifications. We enrolled 256 subjects and evaluated 303 breasts with grouped or segmental calcifications. All imaging examinations were performed using two-directional full-field digital mammography (FFDM) and DBT. We divided subjects into two groups, namely, "dense" and "fatty," based on the quantity of breast tissue and evaluated whether the growth of cancer causes increased the density overlapping with calcifications. Increased overlapping density was significantly associated with malignant calcifications (p < 0.001), and the identification of increased density was more accurate using DBT than using FFDM. Furthermore, we used DBT to evaluate whether segmental calcifications were continuous or discontinuous. Significantly more malignant than benign calcifications were associated with a continuous distribution (p = 0.035). Increased density overlapping with grouped calcifications was significantly associated with invasive cancers (p = 0.017). The findings of this study suggest that DBT improves the ability to differentiate between benign and malignant calcifications.

Leveraging the variable natural history of ductal carcinoma in situ (DCIS) to select optimal therapy

PURPOSE

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive ductal carcinoma. The authors sought to discuss the evidence suggesting that not all DCIS will progress to invasive disease if left untreated.

RESULTS

Four lines of evidence align to suggest that not all of this in-situ disease progresses to invasive cancer: its prevalence on screening mammography, studies of missed diagnoses, incidental findings in autopsy specimens, and large retrospective reviews of those treated with excision alone.

CONCLUSION

A clearer understanding of the variable history of DCIS coupled with advances in genomic profiling of the disease holds the promise of reducing widespread over-treatment of this non-invasive cancer. Additionally, identification of higher risk of recurrence subsets may select patients for whom more aggressive treatment may be appropriate.

Factors affecting the concordance of radiologic and pathologic tumor size in breast carcinoma

Background

Radiologic assessment of tumor size is an integral part of the work-up for breast carcinoma. With improved radiologic equipment, surgical decision relies profoundly upon radiologic/clinical stage. We wanted to see the concordance between radiologic and pathologic tumor size to infer how accurate radiologic/clinical staging is.

Materials and methods

The surgical pathology and ultrasonography reports of patients with breast carcinoma were reviewed. Data were collected for 406 cases. Concordance was defined as a size difference within ±2 mm.

Results

The difference between radiologic and pathologic tumor size was within ±2 mm in 40.4% cases. The mean radiologic size was 1.73 ± 1.06 cm. The mean pathologic size was 1.84 ± 1.24 cm. A paired t-test showed a significant mean difference between radiologic and pathologic measurements (0.12 ± 1.03 cm, p = 0.03). Despite the size difference, stage classification was the same in 59.9% of cases. Radiologic size overestimated stage in 14.5% of cases and underestimated stage in 25.6% of cases. The concordance rate was significantly higher for tumors ≤2 cm (pT1) (51.1%) as compared to those greater than 2 cm (≥pT2) (19.7%) (p < 0.0001). Significantly more lumpectomy specimens (47.5%) had concordance when compared to mastectomy specimens (29.8%) (p < 0.0001). Invasive ductal carcinoma had better concordance compared to other tumors (p = 0.02).

Conclusion

Mean pathologic tumor size was significantly different from mean radiologic tumor size. Concordance was in just over 40% of cases and the stage classification was the same in about 60% of cases only. Therefore, surgical decision of lumpectomy versus mastectomy based on radiologic tumor size may not always be accurate.