Response Evaluation to Neoadjuvant Chemotherapy in Breast Cancer Patients: Sequential Dynamic Contrast-Enhanced MRI Using Computer-Aided Detection

Purpose@#We evaluated whether there is an association between sequential changes in kinetic profiles by computer-aided detection (CAD) during neoadjuvant chemotherapy (NAC) and pathologic complete response (pCR) and residual cancer burden (RCB) in dynamic contrast-enhanced MRI (DCE-MRI) of patients with invasive breast cancer. @*Materials and Methods@#This retrospective study involved 51 patients (median age, 48 years; range, 33–60 years) who underwent pre-, interim-, and post-NAC DCE-MRIs at 3 T. The tumor size and CAD-generated kinetic profiles (peak enhancement and delayed enhancement [persistent, plateau, and washout] components) were measured. Percentage changes in pre- and interim-NAC (ΔMRI value1) and pre- and post-NAC (ΔMRI value2) were compared between pCR and non-pCR cases, and according to RCB. Receiver operating characteristic curve analysis was performed to evaluate the association between pCR and MRI parameters (including CAD-generated kinetic profiles). @*Results@#The pCR rate was 19.6% (10/51). There were statistically significant differences in Δtumor size2 (p < 0.01), Δpeak enhancement2 (p = 0.01), Δpersistent2 (p = 0.01), Δplateau2 (p = 0.02), and Δwashout2 (p = 0.03) between pCR and non-pCR. ΔTumor size2 provided very good diagnostic accuracy for pCR (cut-off, -90%; area under the curve, 0.88). There were differences in Δtumor size2, Δpeak enhancement2, Δplateau2, and Δwashout2 between RCB classes (p < 0.01). @*Conclusion@#DCE-MRI using CAD has the potential for predicting pCR and RCB classes.

Breast Cancer after Radiation Therapy in a Patient with Li-Fraumeni Syndrome:A Case Report

Li-Fraumeni syndrome (LFS) is an inherited autosomal-dominant tumor-predisposition disorder caused by germline mutations in the TP53 tumor suppressor gene. Since patients with LFS are likely to develop therapy-related cancers, radiation therapy should be avoided if breast cancer is found in these individuals. Herein, we present a case of secondary breast cancer in an LFS patient after radiation and chemotherapy for the first diagnosed breast sarcoma.

Bladder Cancer Metastasis to the Breast in a Male Patient: Imaging Findings on Mammography and Ultrasonography

Male breast cancer is rare, accounting for approximately 1% of breast cancers. Metastasis from extra-mammary malignancy to the breast in men is extremely rare. The most common primary tumors that metastasize to the breast in male are prostate, lung, stomach, colorectal cancer, melanoma, and sarcoma. To our knowledge, only a few cases of bladder cancer presenting with metastasis to the male breast have been reported, and metastasis with infiltration rather than mass is extremely rare. We report imaging findings on mammography and ultrasonography in a 59-year-old male with bladder cancer metastatic to the breast.

Digital Breast Tomosynthesis as a Breast Cancer Screening Tool for Women with Gynecologic Cancer

Purpose@#The purpose of our study was to evaluate digital breast tomosynthesis as a breast cancer screening modality for women with gynecologic cancer. @*Materials and Methods@#This retrospective study included patients with underlying gynecologic malignancies who underwent screening digital breast tomosynthesis for breast cancer. The cancer detection rate, recall rate, sensitivity, specificity, and positive predictive value (PPV) were calculated. PPV1 was defined as the percentage of all positive screening exams that have a tissue diagnosis of cancer within a year. PPV2 was defined as the percentage of all diagnostic exams (and Breast Imaging Reporting and Data System category 4, 5 from screening setting) with a recommendation for tissue diagnosis that have cancer within a year. PPV3 was defined as the percentage of all known biopsies actually performed that resulted in a tissue diagnosis of cancer within the year. For each case of screen-detected cancer, we analyzed the age, type of underlying gynecologic malignancy, breast density, imaging features, final Breast Imaging Reporting and Data System assessment, histologic type, T and N stages, molecular subtype, and Ki-67 index. @*Results@#Among 508 patients, 7 with breast cancer were identified after a positive result. The cancer detection rate was 13.8 per 1000 screening exams, and the recall rate was 17.9%. The sensitivity was 100%, and the specificity was 83.2%. The false negative rate was 0 per 1000 exams. The PPV1, PPV2, and PPV3 were 7.7, 31.8, and 31.8, respectively. @*Conclusion@#Digital breast tomosynthesis may be a promising breast cancer screening modality for women with gynecologic cancer, based on the high cancer detection rate, high sensitivity, high PPV, and high detection rate of early-stage cancer observed in our study.

Small Breast Cancer (≤ 5 mm): Ultrasonographic Features and Clinical and Pathological Characteristics

PURPOSE@#To identify differences in ultrasonography (US) feature, clinical and pathological characteristics including immunohistochemical characteristics between small breast cancer (pathologic size ≤ 5 mm) and large breast cancer (> 5 mm).@*MATERIALS AND METHODS@#A total of 528 invasive breast cancer lesions in 475 patients were included. US features with clinical and pathological characteristics were evaluated according to pathologic size. US Breast Imaging-Reporting and Data System findings and final assessments were recorded for each lesion. Standard references were based on surgical pathologies.@*RESULTS@#Of 528 invasive breast cancer lesions, 62 were small breast cancers. Small breast cancers showed a higher rate of oval, round shape, parallel orientation; circumscribed margin; and iso/solid and cystic echo pattern, with no posterior feature. The final assessment of category 4 was also a dominant factor in small breast cancer. Early stage, asymptomatic state, and extensive ductal carcinoma in situ component were associated with small breast cancers.@*CONCLUSION@#Our results show that small breast cancers have less suspicious US features than large breast cancers.

Invasive Lobular Carcinoma: Detection and Multiplicity with Multimodalities / 이화의대지

OBJECTIVES: We aimed to compare the diagnostic performances of digital mammography (DM), digital breast tomosynthesis (DBT), ultrasound (US), magnetic resonance imaging (MRI), breast specific gamma imaging (BSGI) and/or positron emission tomography/computed tomography (PET/CT) for the detection of invasive lobular carcinoma (ILC). METHODS: Index ILCs and multifocal/multicentric (multiple) ILCs were analyzed using various imaging modalities. The final surgical pathology was regarded as the reference standard. The detection rate for index cancers and the diagnostic performance for multiple ILCs per breast were evaluated. RESULTS: Seventy-eight ILCs in 76 women were enrolled. Twenty-six breasts had multiple ILCs. DM (n=72), DBT (n=15), US (n=77), MRI (n=76), BSGI (n=50), and /or PET/CT (n=74) were performed. For index cancer, the detection rate was 100% for DBT, US, and MRI. For multiple ILCs, the sensitivity was 100% for DBT and MRI (P<0.001). The diagnostic accuracy for multiple ILCs were 73.3% for DBT and 73.0% for PET/CT (P=0.460). CONCLUSION: DBT was the most accurate imaging modality for both index and multiple ILCs. PET/CT was also valuable for multiple ILCs, whereas DM and BSGI showed relatively low diagnostic performances. DBT and PET/CT have promising roles in the diagnosis of multiple ILCs.

Computer-aided detection system for masses in automated whole breast ultrasonography: development and evaluation of the effectiveness

PURPOSE: The aim of this study was to evaluate the performance of a proposed computer-aided detection (CAD) system in automated breast ultrasonography (ABUS). METHODS: Eighty-nine two-dimensional images (20 cysts, 42 benign lesions, and 27 malignant lesions) were obtained from 47 patients who underwent ABUS (ACUSON S2000). After boundary detection and removal, we detected mass candidates by using the proposed adjusted Otsu's threshold; the threshold was adaptive to the variations of pixel intensities in an image. Then, the detected candidates were segmented. Features of the segmented objects were extracted and used for training/testing in the classification. In our study, a support vector machine classifier was adopted. Eighteen features were used to determine whether the candidates were true lesions or not. A five-fold cross validation was repeated 20 times for the performance evaluation. The sensitivity and the false positive rate per image were calculated, and the classification accuracy was evaluated for each feature. RESULTS: In the classification step, the sensitivity of the proposed CAD system was 82.67% (SD, 0.02%). The false positive rate was 0.26 per image. In the detection/segmentation step, the sensitivities for benign and malignant mass detection were 90.47% (38/42) and 92.59% (25/27), respectively. In the five-fold cross-validation, the standard deviation of pixel intensities for the mass candidates was the most frequently selected feature, followed by the vertical position of the centroids. In the univariate analysis, each feature had 50% or higher accuracy. CONCLUSION: The proposed CAD system can be used for lesion detection in ABUS and may be useful in improving the screening efficiency.

Dose Reduction in Automatic Optimization Parameter of Full Field Digital Mammography: Breast Phantom Study / 한국유방암학회지

PURPOSE: We evaluated the impact of three automatic optimization of parameters (AOP) modes of digital mammography on the dose and image quality. METHODS: Computerized Imaging Reference Systems phantoms were used. A total of 12 phantoms with different thickness and glandularity were imaged. We analyzed the average glandular dose (AGD) and entrance surface exposure (ESE) of 12 phantoms imaged by digital mammography in three modes of AOP; namely standard mode (STD), contrast mode (CNT), and dose mode (DOSE). Moreover, exposure factors including kVp, mAs, and target/filter combination were evaluated. To evaluate the quality of the obtained digital image, two radiologists independently counted the objects of the phantoms. RESULTS: According to the AOP modes, the score of masses and specks was sorted as CNT>STD=DOSE. There was no difference in the score of fiber among the three modes. The score of image preference was sorted as CNT>STD>DOSE. The AGD, ESE, and mAs were sorted as CNT>STD>DOSE. The kVp was sorted as CNT=STD>DOSE. The score of all test objects in the phantom image was on a downtrend with increasing breast thickness. The score of masses was different among the three groups; 20-21%>30%>50% glandularity. The score of specks was sorted as 20-21%=30%>50% glandularity. The score of fibers was sorted as 30%>20-21%=50% glandularity. The score of image preference was not different among the three glandularity groups. The AGD, ESE, kVp, and mAs were correlated with breast thickness, but not correlated with glandularity. CONCLUSION: The DOSE mode offers significant improvement (19.1-50%) in dose over the other two modes over a range of breast thickness and breast glandularity with acceptable image quality. Owning knowledge of the three AOP modes may reduce unnecessary radiation exposure by utilizing the proper mode according to its purpose.

Head and Neck Vascular Lesions: Characterization of the Flow Pattern by the Use of Three-Phase CT

OBJECTIVE: This study was designed to evaluate the usefulness of three-phase CT to characterize the hemodynamics of vascular lesions in the head and neck area. MATERIALS AND METHODS:We analyzed vascular malformations of head and neck regions in 21 patients with the use of three-phase CT, including pre-contrast phase, vascular phase (scan delay: 20-35 seconds after intravenous contrast material injection) and equilibrium phase (scan delay: 3-5 minutes) imaging. The flow characteristic of each lesion was determined and categorized as either a high- or a low-flow lesion according to findings on selective arteriography and/or direct puncture venography. The CT number was acquired from two areas in a vascular lesion, sorted by the enhancement pattern: area 1, a highly enhanced area seen on the vascular phase; area 2, a delayedly enhanced area seen on the equilibrium phase. The CT numbers of each phase were compared between high- and low-flow lesions with use of the unpaired t-test. The flow patterns of high- and low-flow lesions were analyzed by assessment of time-density curves of three phase CT. RESULTS: High-flow lesions were detected in nine patients and low-flow lesions were detected in 12 patients. On the vascular phase, the CT number of areas 1 and 2 of high-flow lesions was significantly higher than for low-flow lesions (p < 0.05). Contrary to early peaks seen in time-density curves of high-flow lesions, low-flow lesions showed a delayed peak. CONCLUSION: Three-phase CT seems to be a valuable non-invasive method to differentiate a high-flow lesion from a low flow lesion of head and neck vascular lesions.