1.Automated Breast Ultrasound Screening for Dense Breasts
Sung Hun KIM ; Hak Hee KIM ; Woo Kyung MOON
Korean Journal of Radiology 2020;21(1):15-24
Mammography is the primary screening method for breast cancers. However, the sensitivity of mammographic screening is lower for dense breasts, which are an independent risk factor for breast cancers. Automated breast ultrasound (ABUS) is used as an adjunct to mammography for screening breast cancers in asymptomatic women with dense breasts. It is an effective screening modality with diagnostic accuracy comparable to that of handheld ultrasound (HHUS). Radiologists should be familiar with the unique display mode, imaging features, and artifacts in ABUS, which differ from those in HHUS. The purpose of this study was to provide a comprehensive review of the clinical significance of dense breasts and ABUS screening, describe the unique features of ABUS, and introduce the method of use and interpretation of ABUS.]]>
Artifacts
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Breast Neoplasms
;
Breast
;
Early Detection of Cancer
;
Female
;
Humans
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Mammography
;
Mass Screening
;
Methods
;
Risk Factors
;
Ultrasonography
2.Key technologies in digital breast tomosynthesis system:theory, design, and optimization.
Mingqiang LI ; Kun MA ; Xi TAO ; Yongbo WANG ; Ji HE ; Ziquan WEI ; Geofeng CHEN ; Sui LI ; Dong ZENG ; Zhaoying BIAN ; Guohui WU ; Shan LIAO ; Jianhua MA
Journal of Southern Medical University 2019;39(2):192-200
OBJECTIVE:
To develop a digital breast tomosynthesis (DBT) imaging system with optimizes imaging chain.
METHODS:
Based on 3D tomography and DBT imaging scanning, we analyzed the methods for projection data correction, geometric correction, projection enhancement, filter modulation, and image reconstruction, and established a hardware testing platform. In the experiment, the standard ACR phantom and high-resolution phantom were used to evaluate the system stability and noise level. The patient projection data of commercial equipment was used to test the effect of the imaging algorithm.
RESULTS:
In the high-resolution phantom study, the line pairs were clear without confusing artifacts in the images reconstructed with the geometric correction parameters. In ACR phantom study, the calcified foci, cysts, and fibrous structures were more clearly defined in the reconstructed images after filtering and modulation. The patient data study showed a high contrast between tissues, and the lesions were more clearly displayed in the reconstructed image.
CONCLUSIONS
This DBT imaging system can be used for mammary tomography with an image quality comparable to that of commercial DBT systems to facilitate imaging diagnosis of breast diseases.
Algorithms
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Artifacts
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Breast
;
diagnostic imaging
;
Female
;
Humans
;
Mammography
;
methods
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Phantoms, Imaging
;
Radiographic Image Enhancement
;
methods
3.Establishment of a deep feature-based classification model for distinguishing benign and malignant breast tumors on full-filed digital mammography.
Cuixia LIANG ; Mingqiang LI ; Zhaoying BIAN ; Wenbing LV ; Dong ZENG ; Jianhua MA
Journal of Southern Medical University 2019;39(1):88-92
OBJECTIVE:
To develop a deep features-based model to classify benign and malignant breast lesions on full- filed digital mammography.
METHODS:
The data of full-filed digital mammography in both craniocaudal view and mediolateral oblique view from 106 patients with breast neoplasms were analyzed. Twenty-three handcrafted features (HCF) were extracted from the images of the breast tumors and a suitable feature set of HCF was selected using -test. The deep features (DF) were extracted from the 3 pre-trained deep learning models, namely AlexNet, VGG16 and GoogLeNet. With abundant breast tumor information from the craniocaudal view and mediolateral oblique view, we combined the two extracted features (DF and HCF) as the two-view features. A multi-classifier model was finally constructed based on the combined HCF and DF sets. The classification ability of different deep learning networks was evaluated.
RESULTS:
Quantitative evaluation results showed that the proposed HCF+DF model outperformed HCF model, and AlexNet produced the best performances among the 3 deep learning models.
CONCLUSIONS
The proposed model that combines DF and HCF sets of breast tumors can effectively distinguish benign and malignant breast lesions on full-filed digital mammography.
Breast Neoplasms
;
classification
;
diagnostic imaging
;
Deep Learning
;
Diagnosis, Computer-Assisted
;
methods
;
Female
;
Humans
;
Mammography
;
methods
4.Comparison of the Diagnostic Values of Dynamic Enhanced Magnetic Resonance Imaging,Digital Breast Tomosynthesis,and Digital Mammography for Early Breast Cancer.
A Qiao XU ; Xiao Bo WENG ; Jing ZHENG ; Zhi Qing LI ; Xiao Ling WANG ; Sheng Jian ZHANG
Acta Academiae Medicinae Sinicae 2019;41(5):667-672
Objective To compare the values of dynamic enhanced magnetic resonance imaging(DCE-MRI),digital breast tomosynthesis(DBT),and digital mammography(DM)in the early detection and diagnosis of breast cancer.Methods We retrospectively analyzed the clinical and imaging data of 65 cases with early breast cancer confirmed by surgical pathology from June 2017 to December 2018.All patients underwent breast DCE-MRI,DM and DBT before surgery.The receiver operating characteristic(ROC)curves were drawn,with the pathological results as the gold standard,to evaluate the diagnostic performance of different examination methods.The areas under ROC curves(AUCs)were compared using test.The differences among DCE-MRI,DBT and DM in detecting early breast cancer were compared using chi-square test in terms of positive rates,accuracy,sensitivity,and specificity.Pearson correlation analysis was performed to assess the accuracy of these imaging methods in detecting the size of early breast cancer.Results The AUCs of DCE-MRI,DBT,and DM based on the BI-RADS classification for early diagnosis of breast cancer were 0.910,0.832,and 0.700,respectively(=2.132,=0.001);the sensitivity of DCE-MRI,DBT,and DM for early breast cancer was 92.3%,70.8%,and 52.5%,the specificity was 65.0%,85.0%,and 79.3%,and the accuracy was 83.1%,70.8%,and 50.8%,indicating that DCE-MRI(=15.330,=0.0001) and DBT(=5.450,=0.020) had significantly higher diagnostic accuracy than DM.The measurement results of DM,DBT,and DCE-MRI were positively correlated with the pathological measurements(=0.781,=0.847,=0.946;all <0.01). Conclusions DCE-MRI and DBT have higher positive rates and accuracies than DM in detecting early breast cancer.Medical institutions where DCE-MRI is still not available can use DBT to improve the early detection of breast cancer.
Breast
;
diagnostic imaging
;
Breast Neoplasms
;
diagnostic imaging
;
Female
;
Humans
;
Magnetic Resonance Imaging
;
Mammography
;
methods
;
Retrospective Studies
5.Intraoperative Specimen Mammography for Margin Assessment in Breast-Conserving Surgery
Ming JIN ; Ji Young KIM ; Tae Hee KIM ; Doo Kyung KANG ; Se Hwan HAN ; Yongsik JUNG
Journal of Breast Cancer 2019;22(4):635-640
mammography is an effective margin assessment method in Asian women. Thus, 182 patients who underwent breast-conserving surgery (BCS) were evaluated. After wide excision, intraoperative specimen mammography was used to assess margin adequacy. The control group comprised 84 patients who underwent BCS and were evaluated for margin of frozen section during surgery. 61.6% patients had dense breasts and 85.7% of dense breasts could margin assess by intraoperative specimen mammography. There were no significant differences in the incidence of extremely close margins (p = 0.421) and second operation (p = 0.252) between both groups. Significant correlations were found between radiological and histological margins (R² = 0.222, p < 0.05). The frozen section analysis group had longer operative time than the specimen mammography group. The study results show that intraoperative specimen mammography of breast lesions in BCS is useful in identifying margin clearance.]]>
Asian Continental Ancestry Group
;
Breast
;
Breast Neoplasms
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Female
;
Frozen Sections
;
Humans
;
Incidence
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Mammography
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Mastectomy, Segmental
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Methods
;
Operative Time
6.FDG PET/CT and Conventional Imaging Methods in Cancer of Unknown Primary: an Approach to Overscanning
Neslihan CETIN AVCI ; Filiz HATIPOGLU ; Ahmet ALACACIOGLU ; Emine Ebru BAYAR ; Gonca Gul BURAL
Nuclear Medicine and Molecular Imaging 2018;52(6):438-444
PURPOSE: To compare the performance of fluorine-18 fluorodeoxyglucose positron emission tomography and computed tomography (FDG PET/CT) with conventional imaging methods (CIM), including computed tomography (CT), magnetic resonance imaging (MRI), and mammography (MMG) in cancer of unknown primary (CUP).METHODS: A total of 36 patients with CUP, who referred to our clinic for a FDG PET/CTscan, were enrolled in this study. Thirty of the patients were also examined through either diagnostic CT/MRI and/or MMG. The diagnostic performance of both methods for the primary cancer location was analyzed. The results of FDG PET/CT and CIM were compared based on the standard reference of the histopathology and/or clinical and laboratory follow-up.RESULTS: The primary cancer locations were detected in 24 patients (66.6%, 24/36) by FDG PET/CT, whereas CIM identified the locations in 16 patients (53.3%, 16/30). Sensitivity, specificity, PPV, NPV, and accuracy rates of the detection of the primary tumor localizations were as follows: 83, 70, 89, 58, and 79% for FDG PET/CT; 70, 62, 84, 42, and 68% for CIM, respectively. There was no statistical significance between modalities regarding any of the categories in 30 patients.CONCLUSION: FDG PET/CT detected the primary tumors of the patients with CUP more than CIM did. However, the difference between them was not found to be statistically significant. It may be considered that FDG PET/CT scan can be performed as a first-line tool in the initial diagnosis of the patients with CUP and to add radiodiagnostic imaging in selective cases.We conclude that if the first-line examination of a CUP patient has been already performed by a CIM and the result was negative or inconclusive, FDG PET/CT can be considered to avoid unnecessary imaging procedures.
Diagnosis
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Follow-Up Studies
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Humans
;
Magnetic Resonance Imaging
;
Mammography
;
Methods
;
Positron-Emission Tomography
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Positron-Emission Tomography and Computed Tomography
;
Sensitivity and Specificity
7.Imaging Surveillance for Survivors of Breast Cancer: Correlation between Cancer Characteristics and Method of Detection.
A Jung CHU ; Jung Min CHANG ; Nariya CHO ; Woo Kyung MOON
Journal of Breast Cancer 2017;20(2):192-197
PURPOSE: The aim of our study was to investigate the characteristics of primary and recurrent breast cancers and the correlation between cancer subtypes and detection modes. METHODS: Between 2003 and 2013, 147 cases of recurrent breast cancer in 137 women (mean age, 45.30±10.78 years) were identified via an annual clinical examination using radiological studies among 6,169 patients with a breast cancer history (mean follow-up period, 13.26±1.78 years). Clinical, radiological, and pathological findings including immunohistochemistry findings of primary and recurrent cancers were reviewed. The size of the tumor in primary and recurrent cancers, disease-free survival, methods of surgery, and the recurrence detection modalities were analyzed with respect to the breast cancer subtype. RESULTS: Ipsilateral and contralateral in-breast recurrence occurred in 105, 21 had axillary lymph node recurrence, and 21 had chest wall recurrences. The subtypes of the primary cancers were hormone receptor (HR) positive and human epidermal growth factor receptor 2 (HER2) negative (HR+HER2−) in 57, HER2 positive (HER2+) in 39, and triple-negative type in 51, and the recurrent cancers in each subtype showed the same type as the primary cancer in 84.3% of cases. In the in-breast recurrent cancers, the HR+HER2− cancers were most frequently detected using ultrasonography (15/43) followed by mammography (MG) (11/43). The HER2+ recurrent cancers were most commonly detected using MG (14/31, 45.2%), whereas triple-negative type recurrent cancers most commonly presented as symptomatic masses (15/31) (p=0.028). CONCLUSION: Most recurrent breast cancers showed the same cancer subtype as the primary tumor, and recurrent breast cancer subtypes correlated with the detection modality. Imaging surveillance of survivors of breast cancer might be more beneficial in cases of HR+HER2− type breast cancer or HER2+ type breast cancer than in cases of triple-negative type breast cancer.
Breast Neoplasms*
;
Breast*
;
Disease-Free Survival
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Female
;
Follow-Up Studies
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Humans
;
Immunohistochemistry
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Lymph Nodes
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Mammography
;
Methods*
;
Receptor, Epidermal Growth Factor
;
Recurrence
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Survivors*
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Thoracic Wall
;
Ultrasonography
8.Medical auditing of whole-breast screening ultrasonography.
Ultrasonography 2017;36(3):198-203
Since breast ultrasonography (US) has been used as an adjunctive screening modality in women with dense breasts, the need has arisen to evaluate and monitor its possible harm and benefits in comparison with other screening modalities such as mammography. Recently, the fifth edition of the Breast Imaging Reporting and Data System published by the American College of Radiology has suggested auditing methods for screening breast US. However, the method proposed therein is slightly different from how diagnostic performance was calculated in previous studies on screening breast US. In this article, the background and core aspects of medical audits of breast cancer screening will be reviewed to provide an introduction to the medical auditing of screening breast US, with the goal of helping radiologists to understand and identify potential ways to improve outcomes.
Breast
;
Breast Neoplasms
;
Female
;
Humans
;
Information Systems
;
Mammography
;
Mass Screening*
;
Medical Audit*
;
Methods
;
Ultrasonography*
;
Ultrasonography, Mammary
9.Breast Density and Risk of Breast Cancer in Asian Women: A Meta-analysis of Observational Studies.
Journal of Preventive Medicine and Public Health 2016;49(6):367-375
OBJECTIVES: The established theory that breast density is an independent predictor of breast cancer risk is based on studies targeting white women in the West. More Asian women than Western women have dense breasts, but the incidence of breast cancer is lower among Asian women. This meta-analysis investigated the association between breast density in mammography and breast cancer risk in Asian women. METHODS: PubMed and Scopus were searched, and the final date of publication was set as December 31, 2015. The effect size in each article was calculated using the interval-collapse method. Summary effect sizes (sESs) and 95% confidence intervals (CIs) were calculated by conducting a meta-analysis applying a random effect model. To investigate the dose-response relationship, random effect dose-response meta-regression (RE-DRMR) was conducted. RESULTS: Six analytical epidemiology studies in total were selected, including one cohort study and five case-control studies. A total of 17 datasets were constructed by type of breast density index and menopausal status. In analyzing the subgroups of premenopausal vs. postmenopausal women, the percent density (PD) index was confirmed to be associated with a significantly elevated risk for breast cancer (sES, 2.21; 95% CI, 1.52 to 3.21; I2=50.0%). The RE-DRMR results showed that the risk of breast cancer increased 1.73 times for each 25% increase in PD in postmenopausal women (95% CI, 1.20 to 2.47). CONCLUSIONS: In Asian women, breast cancer risk increased with breast density measured using the PD index, regardless of menopausal status. We propose the further development of a breast cancer risk prediction model based on the application of PD in Asian women.
Asian Continental Ancestry Group*
;
Breast Neoplasms*
;
Breast*
;
Case-Control Studies
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Cohort Studies
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Dataset
;
Epidemiology
;
Female
;
Humans
;
Incidence
;
Mammography
;
Methods
;
Publications
;
Risk Factors
10.Features of Undiagnosed Breast Cancers at Screening Breast MR Imaging and Potential Utility of Computer-Aided Evaluation.
Mirinae SEO ; Nariya CHO ; Min Sun BAE ; Hye Ryoung KOO ; Won Hwa KIM ; Su Hyun LEE ; Ajung CHU
Korean Journal of Radiology 2016;17(1):59-68
OBJECTIVE: To retrospectively evaluate the features of undiagnosed breast cancers on prior screening breast magnetic resonance (MR) images in patients who were subsequently diagnosed with breast cancer, as well as the potential utility of MR-computer-aided evaluation (CAE). MATERIALS AND METHODS: Between March 2004 and May 2013, of the 72 consecutive pairs of prior negative MR images and subsequent MR images with diagnosed cancers (median interval, 32.8 months; range, 5.4-104.6 months), 36 (50%) had visible findings (mean size, 1.0 cm; range, 0.3-5.2 cm). The visible findings were divided into either actionable or underthreshold groups by the blinded review by 5 radiologists. MR imaging features, reasons for missed cancer, and MR-CAE features according to actionability were evaluated. RESULTS: Of the 36 visible findings on prior MR images, 33.3% (12 of 36) of the lesions were determined to be actionable and 66.7% (24 of 36) were underthreshold; 85.7% (6 of 7) of masses and 31.6% (6 of 19) of non-mass enhancements were classified as actionable lesions. Mimicking physiologic enhancements (27.8%, 10 of 36) and small lesion size (27.8%, 10 of 36) were the most common reasons for missed cancer. Actionable findings tended to show more washout or plateau kinetic patterns on MR-CAE than underthreshold findings, as the 100% of actionable findings and 46.7% of underthreshold findings showed washout or plateau (p = 0.008). CONCLUSION: MR-CAE has the potential for reducing the number of undiagnosed breast cancers on screening breast MR images, the majority of which are caused by mimicking physiologic enhancements or small lesion size.
Adult
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Aged
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Breast/*pathology
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Breast Neoplasms/*diagnosis/pathology/radiography
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Diagnosis, Computer-Assisted/*methods
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False Negative Reactions
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Female
;
Humans
;
Magnetic Resonance Imaging/*methods
;
Mammography/*methods
;
Middle Aged
;
Retrospective Studies

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