Sung Ui Shin

Comparative evaluation of average glandular dose and breast cancer detection between single-view digital breast tomosynthesis (DBT) plus single-view digital mammography (DM) and two-view DM: correlation with breast thickness and density

AbstractObjectivesTo compare the average glandular dose (AGD) and diagnostic performance of mediolateral oblique (MLO) digital breast tomosynthesis (DBT) plus cranio-caudal (CC) digital mammography (DM) with two-view DM, and to evaluate the correlation of AGD with breast thickness and density.MethodsMLO and CC DM and DBT images of both breasts were obtained in 149 subjects. AGDs of DBT and DM per exposure were recorded, and their correlation with breast thickness and density were evaluated. Paired data of MLO DBT plus CC DM and two-view DM were reviewed for presence of malignancy in a jack-knife alternative free-response ROC (JAFROC) method.ResultsThe AGDs of both DBT and DM, and differences in AGD between DBT and DM (ΔAGD), were correlated with breast thickness and density. The average JAFROC figure of merit (FOM) was significantly higher on the combined technique than two-view DM (P = 0.005). In dense breasts, the FOM and sensitivity of the combined technique was higher than that of two-view DM (P = 0.003) with small ΔAGD.ConclusionsMLO DBT plus CC DM provided higher diagnostic performance than two-view DM in dense breasts with a small increase in AGD.Key Points• DBT has higher diagnostic performance and potential to overcome limitations of DM. • Dose differences (DBT-DM, ΔAGD) were inversely correlated with breast thickness and density. • Figure of merit of MLO-DBT/CC-DM was higher than that of two-view DM. • In dense breasts, MLO-DBT/CC-DM provides better diagnostic performance with a small AGD increase.

The adaptive computer-aided diagnosis system based on tumor sizes for the classification of breast tumors detected at screening ultrasound

HighlightsAn adaptive filtering is introduced into a computer‐aided diagnosis (CAD) system to highlight the characteristic of breast tumors detected in screening ultrasound (US).The adaptive filtering enhances the CAD system to emphasize the meaningfulness of tumor size, allows a new regularization technique to be embedded, and increasing the classification accuracy.For the classification between malignant and benign tumors with two kinds of tumor size (Symbol1 cm and Symbol1 cm), especially in the tumors larger or equal to 1 cm, the proposed CAD was more robust than conventional CAD. Symbol. No caption available. Symbol. No caption available.The CAD system using various quantitative US features would provide a promising diagnostic suggestion for classifying the breast tumors detected at screening US images. Abstract Screening ultrasound (US) is increasingly used as a supplement to mammography in women with dense breasts, and more than 80% of cancers detected by US alone are 1 cm or smaller. An adaptive computer‐aided diagnosis (CAD) system based on tumor size was proposed to classify breast tumors detected at screening US images using quantitative morphological and textural features. In the present study, a database containing 156 tumors (78 benign and 78 malignant) was separated into two subsets of different tumor sizes (Symbol1 cm and Symbol1 cm) to explore the improvement in the performance of the CAD system. After adaptation, the accuracies, sensitivities, specificities and Az values of the CAD for the entire database increased from 73.1% (114/156), 73.1% (57/78), 73.1% (57/78), and 0.790 to 81.4% (127/156), 83.3% (65/78), 79.5% (62/78), and 0.852, respectively. In the data subset of tumors larger than 1 cm, the performance improved from 66.2% (51/77), 68.3% (28/41), 63.9% (23/36), and 0.703 to 81.8% (63/77), 85.4% (35/41), 77.8% (28/36), and 0.855, respectively. The proposed CAD system can be helpful to classify breast tumors detected at screening US.

Replacing single-view mediolateral oblique (MLO) digital mammography (DM) with synthesized mammography (SM) with digital breast tomosynthesis (DBT) images: Comparison of the diagnostic performance and radiation dose with two-view DM with or without MLO-DBT

OBJECTIVES To evaluate the diagnostic performance and radiation dose of single view cranio-caudal (CC) digital mammography (DM) plus mediolateral oblique (MLO) digital breast tomosynthesis (DBT) combined with synthesized mammography (SM) in comparison with two-view DM with or without DBT. MATERIAL AND METHODS This study was approved by our institutional review board, and informed consent was obtained from 130 women. Paired two-view DM and single MLO-DBT with SM images were acquired, and four independent retrospective reading sessions of different combinations of DM, SM and DBT were performed for the presence of malignant tumors using jackknife alternative free-response receiver operator curve (JAFROC) methods. The diagnostic performances and average glandular dose (AGD) were compared between different combinations of DM, SM and DBT. RESULTS Of 159 lesions in 130 patients, 27 were malignant. When using MLO-DBT with SM instead of MLO-DM, a significantly higher sensitivity (P=0.016) and specificity (P=0.012) were noted than with two-view DM, and comparable figure of merit (FOM), sensitivity, and specificity to two-view DM with DBT were noted. The mean AGD of CC-DM plus MLO-DBT with SM was 5.78mGy±1.06 per patient, which was significantly lower than that with two-view DM with MLO-DBT (8.45mGy±1.32; P <0.001) and slightly higher than that with two-view DM (5.30mGy±0.63). CONCLUSIONS The combined use of CC-DM plus MLO-DBT with SM showed higher sensitivity and specificity to two-view DM with a smaller AGD increment and comparable diagnostic performance to that of two-view DM with MLO-DBT with a significantly lower mean AGD.

Gene expression profiling of calcifications in breast cancer

We investigated the gene expression profiles of calcifications in breast cancer. Gene expression analysis of surgical specimen was performed using Affymetrix GeneChip® Human Gene 2.0 ST arrays in 168 breast cancer patients. The mammographic calcifications were reviewed by three radiologists and classified into three groups according to malignancy probability: breast cancers without suspicious calcifications; breast cancers with low-to-intermediate suspicious calcifications; and breast cancers with highly suspicious calcifications. To identify differentially expressed genes (DEGs) between these three groups, a one-way analysis of variance was performed with post hoc comparisons with Tukey’s honest significant difference test. To explore the biological significance of DEGs, we used DAVID for gene ontology analysis and BioLattice for clustering analysis. A total of 2551 genes showed differential expression among the three groups. ERBB2 genes are up-regulated in breast cancers with highly suspicious calcifications (fold change 2.474, p < 0.001). Gene ontology analysis revealed that the immune, defense and inflammatory responses were decreased in breast cancers with highly suspicious calcifications compared to breast cancers without suspicious calcifications (p from 10−23 to 10−8). The clustering analysis also demonstrated that the immune system is associated with mammographic calcifications (p < 0.001). Our study showed calcifications in breast cancers are associated with high levels of mRNA expression of ERBB2 and decreased immune system activity.

Association between US features of primary tumor and axillary lymph node metastasis in patients with clinical T1–T2N0 breast cancer

Background Most patients with early-stage breast cancer have clinically negative lymph nodes (LNs). However, 15–20% of patients have axillary nodal metastasis based on the sentinel LN biopsy. Purpose To assess whether ultrasound (US) features of a primary tumor are associated with axillary LN metastasis in patients with clinical T1–T2N0 breast cancer. Material and Methods This retrospective study included 138 consecutive patients (median age = 51 years; age range = 27–78 years) who underwent breast surgery with axillary LN evaluation for clinically node-negative T1–T2 breast cancer. Three radiologists blinded to the axillary surgery results independently reviewed the US images. Tumor distance from the skin and distance from the nipple were determined based on the US report. Association between US features of a breast tumor and axillary LN metastasis was assessed using a multivariate logistic regression model after controlling for clinicopathologic variables. Results Of the 138 patients, 28 (20.3%) had nodal metastasis. At univariate analysis, tumor distance from the skin (P = 0.019), tumor size on US (P = 0.023), calcifications (P = 0.036), architectural distortion (P = 0.001), and lymphovascular invasion (P = 0.049) were associated with axillary LN metastasis. At multivariate analysis, shorter skin-to-tumor distance (odds ratio [OR] = 4.15; 95% confidence interval [CI] = 1.01–16.19; P = 0.040) and masses with associated architectural distortion (OR = 3.80; 95% CI = 1.57–9.19; P = 0.003) were independent predictors of axillary LN metastasis. Conclusion US features of breast cancer can be promising factors associated with axillary LN metastasis in patients with clinically node-negative early-stage breast cancer.

Computer-aided prediction model for axillary lymph node metastasis in breast cancer using tumor morphological and textural features on ultrasound

BACKGROUND AND OBJECTIVES Axillary lymph node (ALN) status is a key indicator in assessing and determining the treatment strategy for patients with newly diagnosed breast cancer. Previous studies suggest that sonographic features of a primary tumor have the potential to predict ALN status in the preoperative staging of breast cancer. In this study, a computer-aided prediction (CAP) model as well as the tumor features for ALN metastasis in breast cancers were developed using breast ultrasound (US) images. METHODS A total of 249 malignant tumors were acquired from 247 female patients (ages 20-84 years; mean 55 ± 11 years) to test the differences between the non-metastatic (130) and metastatic (119) groups based on various features. After applying semi-automatic tumor segmentation, 69 quantitative features were extracted. The features included morphology and texture of tumors inside a ROI of breast US image. By the backward feature selection and linear logistic regression, the prediction model was constructed and established to estimate the likelihood of ALN metastasis for each sample collected. RESULTS In the experiments, the texture features showed higher performance for predicting ALN metastasis compared to morphology (Az, 0.730 vs 0.667). The difference, however, was not statistically significant (p-values > 0.05). Combining the textural and morphological features, the accuracy, sensitivity, specificity, and Az value achieved 75.1% (187/249), 79.0% (94/119), 71.5% (93/130), and 0.757, respectively. CONCLUSIONS The proposed CAP model, which combines textural and morphological features of primary tumor, may be a useful method to determine the ALN status in patients with breast cancer.

Detection of noncalcified breast cancer in patients with extremely dense breasts using digital breast tomosynthesis compared with full-field digital mammography

OBJECTIVE: To evaluate the tumour visibility and diagnostic performance of digital breast tomosynthesis (DBT) in patients with noncalcified T1 breast cancer. METHODS: Medical records of 106 females with noncalcified T1 invasive breast cancer who underwent DBT and full-field digital mammography (FFDM) between January 2012 and December 2014 were retrospectively reviewed. To assess tumour visibility (score 1-3), all DBT and FFDM images were reviewed by two radiologists blinded to clinicopathological information. A reference standard was established by an unblinded consensus review of all images. Clinicopathological and imaging variables were analysed based on tumour visibility. After adding 159 negative controls, the diagnostic performance of DBT + FFDM was compared with that of FFDM. RESULTS: The tumour visibility was significantly higher through DBT + FFDM (2.5 vs 1.8; p = 0.002) than FFDM alone. Breast composition was the independent variable for tumour visibility through DBT + FFDM (extremely dense; odds ratio, 0.02; p < 0.001). Sensitivity (p = 0.642), specificity (p = 0.463), positive-predictive value (p = 0.078), and negative-predictive value (p = 0.072) of DBT + FFDM were not significantly superior to those of FFDM in 55 females with extremely dense breast composition, whereas specificity (p = 0.002) and positive-predictive value (p < 0.001) were significantly higher in 210 females with other breast compositions. CONCLUSION: Addition of DBT to FFDM showed no significant increase in the tumour visibility and diagnostic performance in patients with noncalcified T1 cancer in extremely dense breasts. ADVANCES IN KNOWLEDGE: Addition of DBT to FFDM did not further improve the detection of noncalcified early breast cancers in females with extremely dense breasts.

Detection of axillary lymph node recurrence in patients with personal history of breast cancer treated with sentinel lymph node biopsy (SLNB): results of postoperative combined ultrasound and mammography screening over five consecutive years

Background Sentinel lymph node biopsy (SLNB) has been accepted as the standard treatment for axillary evaluation for invasive breast cancer with a clinically negative axilla and the low rate of recurrence after SLNB was reported. Purpose To evaluate the performance of screening ultrasound (US) for breast and axillary recurrence detection in breast cancer patients who underwent SLNB. Material and Methods We identified 2807 examinations of 562 breast cancer patients who underwent SLNB and received annual screening US combined with mammography (MG) for five years. The cancer detection rate, recall rate, and positive predictive value (PPV3) of biopsies in breasts and breast plus axillae were calculated separately. Results During the five-year follow-up period, 21 patients had recurrences of breast cancer (9.8 per 1000 person-year; 95% confidence interval [CI] = 6.0–14.9), including three axillary recurrences (1.4 per 1000 person-year; 95% CI = 0.3–4.1). Screening breast US detected 12 breast cancers. The axillary scanning detected none of the axillary recurrences, but yielded 11.8 recalls per 1000 US screenings; the PPV3 for the breast and breast plus axillae were 18.3% and 15.1%, respectively. Conclusion Axillary recurrence was very rare in patient who underwent SLNB; additional axillary scanning did not provide axillary recurrence detection, but only increased the number of false-positive recalls and biopsies.