• Asian Pacific Journal of Cancer Prevention
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• v.15 no.7
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• pp.3179-3183
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• 2014

Background: The purpose of study was to evaluate radiologic or clinical features of breast cancer undergoing ultrasound (US)-guided 14G core needle biopsy (CNB) and analyze the differences between underestimated and accurately diagnosed groups. Materials and Methods: Of 1,898 cases of US-guided 14G CNB in our institute, 233 cases were proven to be cancer by surgical pathology. The pathologic results from CNB were invasive ductal carcinoma (IDC) (n=157), ductal carcinoma in situ (DCIS) (n=40), high-risk lesions in 22 cases, and benign in 14 cases. Among high-risk lesions, 7 cases of atypical ductal hyperplasia (ADH) were reported as cancer and 11 cases of DCIS were proven IDC in surgical pathology. Some 29 DCIS cases and 157 cases of IDC were correctly diagnosed with CNB. The clinical and imaging features between underestimated and accurately diagnosed breast cancers were compared. Results: Of 233 cancer cases, underestimation occurred in 18 lesions (7.7%). Among underestimated cancers, CNB proven ADH (n=2) and DCIS (n=11) were diagnosed as IDC and CNB proven ADH (n=5) were diagnosed at DCIS finally. Among the 186 accurately diagnosed group, the CNB results were IDC (n=157) and DCIS (n=29). Comparison of underestimated and accurately diagnosed groups for BI-RADS category, margin of mass on mammography and US and orientation of lesion on US revealed statistically significant differences. Conclusions: Underestimation of US-guided 14G CNB occurred in 7.7% of breast cancers. Between underestimated and correctly diagnosed groups, BI-RADS category, margin of the mass on mammography and margin and orientation of the lesions on US were different.

• Korean Journal of Radiology
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• v.21 no.5
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• pp.550-560
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• 2020

Objective: To evaluate the interobserver agreement, diagnostic value, and associated clinical factors of automated breast ultrasound (ABUS) coronal features in differentiating breast lesions. Materials and Methods: This study enrolled 457 pathologically confirmed lesions in 387 female (age, 46.4 ± 10.3 years), including 377 masses and 80 non-mass lesions (NMLs). The unique coronal features, including retraction phenomenon, hyper- or hypoechoic rim (continuous or discontinuous), skipping sign, and white wall sign, were defined and recorded. The interobserver agreement on image type and coronal features was evaluated. Furthermore, clinical factors, including the lesion size, distance to the nipple or skin, palpability, and the histological grade were analyzed. Results: Among the 457 lesions, 296 were malignant and 161 were benign. The overall interobserver agreement for image type and all coronal features was moderate to good. For masses, the retraction phenomenon was significantly associated with malignancies (p < 0.001) and more frequently presented in small and superficial invasive carcinomas with a low histological grade (p = 0.027, 0.002, and < 0.001, respectively). Furthermore, continuous hyper- or hypoechoic rims were predictive of benign masses (p < 0.001), whereas discontinuous rims were predictive of malignancies (p < 0.001). A hyperechoic rim was more commonly detected in masses more distant from the nipple (p = 0.027), and a hypoechoic rim was more frequently found in large superficial masses (p < 0.001 for both). For NMLs, the skipping sign was a predictor of malignancies (p = 0.040). Conclusion: The coronal plane of ABUS may provide useful diagnostic value for breast lesions.

• Investigative Magnetic Resonance Imaging
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• v.17 no.3
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• pp.207-214
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• 2013

Purpose : To evaluate the MRI findings of breast cancer with BRCA mutation. Materials and Methods: We collected information of the breast cancer patients who underwent the test for BRCA gene mutation as well as preoperative breast MRI from January 2007 to December 2010. A total of 185 patients were enrolled; 33 of these patients had BRCA mutations and 152 patients did not. Among them, a total of 231 breast cancers were detected. Images of the 47 breast cancers with BRCA mutation and of the 184 breast cancers without mutations were evaluated to compare the morphologic and enhancement features on MRI. Results: With MR imaging, there were no significant difference in morphologic characteristic between two groups. However, enhancement pattern in the group with BRCA mutation were more likely to have persistent enhancement (p < 0.233), and LN metastasis was more common in breast cancers without BRCA mutation. Breast cancers with BRCA 2 mutation tend to show more persistent enhancement pattern than BRCA 1 mutation. Conclusion: In breast cancer patients with BRCA mutation, MRI didn't show significant difference in morphologic characteristics, however breast cancers with BRCA gene mutation carriers tend to have benign morphologic features on MRI, such as Type 1 kinetic curve enhancement.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.620-631
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• 2022

Purpose This study aimed to investigate the diagnostic performance of features suggestive of nodal metastasis on preoperative MRI in patients with invasive breast cancer. Materials and Methods We retrospectively reviewed the preoperative breast MRI of 192 consecutive patients with surgically proven invasive breast cancer. We analyzed MRI findings of axillary lymph nodes with regard to the size, long/short ratio, cortical thickness, shape and margin of the cortex, loss of hilum, asymmetry, signal intensity (SI) on T2-weighted images (T2WI), degree of enhancement in the early phase, and enhancement kinetics. Receiver operating characteristic (ROC) analysis, chi-square test, t test, and McNemar's test were used for statistical analysis. Results Increased shorter diameter, uneven cortical shape, increased cortical thickness, loss of hilum, asymmetry, irregular cortical margin, and low SI on T2WI were significantly suggestive of metastasis. ROC analysis revealed the cutoff value for the shorter diameter and cortical thickness as 8.05 mm and 2.75 mm, respectively. Increased cortical thickness (> 2.75 mm) and uneven cortical shape showed significantly higher sensitivity than other findings in McNemar's test. Irregular cortical margins showed the highest specificity (100%). Conclusion Cortical thickness > 2.75 mm and uneven cortical shape are more sensitive parameters than other findings, and an irregular cortical margin is the most specific parameter for predicting axillary metastasis in patients with invasive breast cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1907-1910
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• 2012

Background: Breast cancer is the most prevalent cancer and the fifth cause of cancer death in Iranian women. Early detection and treatment are important for appropriate management of this disease. Mammography and ultrasonography are used for screening and evaluation of symptomatic cases and the main diagnostic test for breast cancer is pathological. In this study we evaluated mammography and ultrasonography as diagnostic tools. Methods: In this cross-sectional study 384 mammography and ultrasonography reports for 255 women were assessed, divided into benign and malignant groups. Suspected cases were referred for pathology evaluation. The radiologic and pathologic reports were compared and also comparison was performed based on age groups (more and less than 50 years old), history of breastfeeding and gravidity. Statistical analysis was performed by SPSS. Results: The mean ages of malignant and benign cases were $49{\pm}11.6$ and $43{\pm}11.2$ years, respectively. Sensitivity and specificity for mammography were 73% and 45%, respectively. Sensitivity and specificity for ultrasonography were 69% and 49%, respectively. There were statistical differences between specificity of mammography in patients based on factors such as history of gravidity, breastfeeding and sensitivity in patients equal or more than 50 years old and less. Conclusion: Factors affecting different results in mammography and ultrasonography reports were classified into three groups, consisting of skill, experience and training of medical staff, and setting of instruments. It is recommended that health managers in developing countries pay attention the quality of setting and man power more than current status. Policy-makers and managers must establish guidelines regarding breast imaging in Iran.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.632-643
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• 2020

Purpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008-0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.420-426
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• 2022

Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3213-3218
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• 2012

When patients with advanced breast cancer (ABC) are treated with neoadjuvant chemotherapy (NACT), efficacy is monitored by the extent of tumor shrinkage. Since their publication in 1981, World Health Organization (WHO) guidelines have been widely practiced in clinical trials and oncologic practice, for standardized tumor response evaluation. With advances in cancer treatment and tumor imaging, a simpler criterion based on one-dimensional rather than bi-dimensional (WHO) tumor measurement, named Response Evaluation Criteria in Solid Tumors (RECIST) was introduced in 2000. Both approaches have four response categories: complete response, partial response, stable disease and progressive disease (PD). Bi-dimensional measurement data of 151 patients with ABC were analysed with WHO and RECIST criteria to compare their response categories and inter criteria reproducibility by Kappa statistics. There was 94% concordance and 9/151 patients were recategorized with RECIST including 6/12 PD cases. RECIST therefore under-estimates and delays diagnosis of PD. This is undesirable because it may delay or negate switch over to alternate therapy. Analysis was repeated with a new criteria named RECIST-Breast (RECIST-B), with a lower threshold for PD (${\geq}10%$ rather than ${\geq}20%$ increase of RECIST). This showed higher concordance of 97% with WHO criteria and re-categorization of only 4/151 patients (1/12 PD cases). RECIST-B criteria therefore have advantages of both ease of measurement and calculations combined with excellent concordance with WHO criteria, providing a practical clinical tool for response evaluation and offering good comparison with past and current clinical trials of NACT using WHO guidelines.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.482-491
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• 2005

In this paper, we proposed the microcalcification detection algorithm which is based on wavelet transform and automatic thresholding method in the X-ray mammographic images. Digital X-ray imaging system is essential equipment in the field diagnosis and is widely used in the various fields such as chest, fracture of a bone, and dental correction. Especially, digital X-ray mammographic imaging is known as the most important method to diagnose the breast cancer, many researches to develop the imaging system are processing in country. In this paper, we proposed a microcalcifications detection algorithm necessary in the early phase of breast cancer diagnosis and showed that a algorithm could effectively detect microcalfication and could aid diagnosis-radiologist.

• Investigative Magnetic Resonance Imaging
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• v.19 no.1
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• pp.56-61
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• 2015

Adenosarcoma of the uterus is a rare biphasic tumor containing benign glandular epithelial and malignant mesenchymal components. The tumor has been reported to be associated with antiestrogen therapy, particularly tamoxifen, but there have been a few case reports with MRI. We present two cases of MRI findings of uterine adenosarcoma after antiestrogen therapy, tamoxifen and toremifene in breast cancer patients. The tumor presents as a large polypoid mass occupying the endometrial cavity, and may protrude into the vagina. On MRI, the tumor typically shows solid components with scattered small cysts and heterogeneous enhancement. These findings are not significantly different from conventional adenosarcoma.