• Title/Summary/Keyword: Breast masses

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BreastLight Apparatus Performance in Detection of Breast Masses Depends on Mass Size

  • Shiryazdi, Seyed Mostafa;Kargar, Saeed;Taheri-Nasaj, Hossein;Neamatzadeh, Hossein
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.3
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    • pp.1181-1184
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    • 2015
  • Background: Accurate measurement of breast mass size is fundamental for treatment planning. We evaluated performance of BreastLight apparatus in detection breast of masses with this in mind. Materials and Methods: From July 2011 to September 2013, a total of 500 women referred to mammography unit in Yazd, Iran for screening were recruited to this study. Performance of BreastLight in detection breast masses regard their sizeing, measured with clinical breast examination (CBE), mammography and sonography, was assessed. Sonographic and mammography examinations were performed according to breast density among women in two groups of women younger (n=105) and older (n=395) than 30 years. Size correlations were performed using Spearman rho analysis. Differences between mass size as assessed with the different methods (mammography, sonography, and clinical examination) and the BreastLight detection were analyzed using $X^2$-trend test. Results: Performance of the BreastLight in detection of lesions smaller than or equal to 1 cm assessed by CBE, mammography and sonography was 4.4%,7.7% and 12.5% and for masses larger than 4 cm was 65%, 100% and 57.1%, respectively. The performance of BreastLight in detection was significantly increased with larger masses (p<0.001). Conclusions: We conclude that clinical measurement of breast cancer size is as accurate as that from mammography or ultrasound. Accuracy can be improved by the use of a simple formula of both clinical and mammographic measurements.

A Prospective Study on the Value of Ultrasound Microflow Assessment to Distinguish Malignant from Benign Solid Breast Masses: Association between Ultrasound Parameters and Histologic Microvessel Densities

  • Ah Young Park;Myoungae Kwon;Ok Hee Woo;Kyu Ran Cho;Eun Kyung Park;Sang Hoon Cha;Sung Eun Song;Ju-Han Lee;JaeHyung Cha;Gil Soo Son;Bo Kyoung Seo
    • Korean Journal of Radiology
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    • v.20 no.5
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    • pp.759-772
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    • 2019
  • Objective: To investigate the value of ultrasound (US) microflow assessment in distinguishing malignant from benign solid breast masses as well as the association between US parameters and histologic microvessel density (MVD). Materials and Methods: Ninety-eight breast masses (57 benign and 41 malignant) were examined using Superb Microvascular Imaging (SMI) and contrast-enhanced US (CEUS) before biopsy. Two radiologists evaluated the quantitative and qualitative vascular parameters on SMI (vascular index, morphology, distribution, and penetration) and CEUS (time-intensity curve analysis and enhancement characteristics). US parameters were compared between benign and malignant masses and the diagnostic performance was compared between SMI and CEUS. Subgroup analysis was performed according to lesion size. The effect of vascular parameters on downgrading Breast Imaging Reporting and Data System (BI-RADS) category 4A masses was evaluated. The association between histologic MVD and US parameters was analyzed. Results: Malignant masses were associated with a higher vascular index (15.1 ± 7.3 vs. 5.9 ± 5.6), complex vessel morphology (82.9% vs. 42.1%), central vascularity (95.1% vs. 59.6%), penetrating vessels (80.5% vs. 31.6%) on SMI (all, p < 0.001), as well as higher peak intensity (37.1 ± 25.7 vs. 17.0 ± 15.8, p < 0.001), slope (10.6 ± 11.2 vs. 3.9 ± 4.2, p = 0.001), area (1035.7 ± 726.9 vs. 458.2 ± 410.2, p < 0.001), hyperenhancement (95.1% vs. 70.2%, p = 0.005), centripetal enhancement (70.7% vs. 45.6%, p = 0.023), penetrating vessels (65.9% vs. 22.8%, p < 0.001), and perfusion defects (31.7% vs. 3.5%, p < 0.001) on CEUS (p ≤ 0.023). The areas under the receiver operating characteristic curve (AUCs) of SMI and CEUS were 0.853 and 0.841, respectively (p = 0.803). In 19 masses measuring < 10 mm, central vascularity on SMI was associated with malignancy (100% vs. 38.5%, p = 0.018). Considering all benign SMI parameters on the BI-RADS assessment, unnecessary biopsies could be avoided in 12 category 4A masses with improved AUCs (0.500 vs. 0.605, p < 0.001). US vascular parameters associated with malignancy showed higher MVD (p ≤ 0.016). MVD was higher in malignant masses than in benign masses, and malignant masses negative for estrogen receptor or positive for Ki67 had higher MVD (p < 0.05). Conclusion: US microflow assessment using SMI and CEUS is valuable in distinguishing malignant from benign solid breast masses, and US vascular parameters are associated with histologic MVD.

Combination of Quantitative Parameters of Shear Wave Elastography and Superb Microvascular Imaging to Evaluate Breast Masses

  • Eun Ji Lee;Yun-Woo Chang
    • Korean Journal of Radiology
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    • v.21 no.9
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    • pp.1045-1054
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    • 2020
  • Objective: This study aimed to evaluate the diagnostic value of combining the quantitative parameters of shear wave elastography (SWE) and superb microvascular imaging (SMI) to breast ultrasound (US) to differentiate between benign and malignant breast masses. Materials and Methods: A total of 200 pathologically confirmed breast lesions in 192 patients were retrospectively reviewed using breast US with B-mode imaging, SWE, and SMI. Breast masses were assessed based on the breast imaging reporting and data system (BI-RADS) and quantitative parameters using the maximum elasticity (Emax) and ratio (Eratio) in SWE and the vascular index in SMI (SMIVI). The area under the receiver operating characteristic curve (AUC) value, sensitivity, specificity, accuracy, negative predictive value, and positive predictive value of B-mode alone versus the combination of B-mode US with SWE or SMI of both parameters in differentiating between benign and malignant breast masses was compared, respectively. Hypothetical performances of selective downgrading of BI-RADS category 4a (set 1) and both upgrading of category 3 and downgrading of category 4a (set 2) were calculated. Results: Emax with a cutoff value of 86.45 kPa had the highest AUC value compared to Eratio of 3.57 or SMIVI of 3.35%. In set 1, the combination of B-mode with Emax or SMIVI had a significantly higher AUC value (0.829 and 0.778, respectively) than B-mode alone (0.719) (p < 0.001 and p = 0.047, respectively). B-mode US with the addition of Emax, Eratio, and SMIVI had the best diagnostic performance of AUC value (0.849). The accuracy and specificity increased significantly from 68.0% to 84.0% (p < 0.001) and from 46.1% to 79.1% (p < 0.001), respectively, and the sensitivity decreased from 97.6% to 90.6% without statistical loss (p = 0.199). Conclusion: Combining all quantitative values of SWE and SMI with B-mode US improved the diagnostic performance in differentiating between benign and malignant breast lesions.

A Study of CBIR(Content-based Image Retrieval) Computer-aided Diagnosis System of Breast Ultrasound Images using Similarity Measures of Distance (거리 기반 유사도 측정을 통한 유방 초음파 영상의 내용 기반 검색 컴퓨터 보조 진단 시스템에 관한 연구)

  • Kim, Min-jeong;Cho, Hyun-chong
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.8
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    • pp.1272-1277
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    • 2017
  • To assist radiologists for the characterization of breast masses, Computer-aided Diagnosis(CADx) system has been studied. The CADx system can improve the diagnostic accuracy of radiologists by providing objective information about breast masses. Morphological and texture features were extracted from the breast ultrasound images. Based on extracted features, the CADx system retrieves masses that are similar to a query mass from a reference library using a k-nearest neighbor (k-NN) approach. Eight similarity measures of distance, Euclidean, Chebyshev(Minkowski family), Canberra, Lorentzian($F_2$ family), Wave Hedges, Motyka(Intersection family), and Cosine, Dice(Inner Product family) are evaluated by ROC(Receiver Operating Characteristic) analysis. The Inner Product family measure used with the k-NN classifier provided slightly higher performance for classification of malignant and benign masses than those with the Minkowski, $F_2$, and Intersection family measures.

Automated Breast Ultrasound: Interobserver Agreement, Diagnostic Value, and Associated Clinical Factors of Coronal-Plane Image Features

  • Guoxue Tang;Xin An;Huiling Xiang;Lixian Liu;Anhua Li;Xi Lin
    • 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.

Foreign Body Granulomas of the Breast Presenting as Bilateral Spiculated Masses

  • Boo-Kyung Han;Yeon Hyeon Choe;Young-Hyeh Ko;Seok-Jin Nam;Jung-Hyun Yang
    • Korean Journal of Radiology
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    • v.2 no.2
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    • pp.113-116
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    • 2001
  • In Asia, mammography following the injection of foreign materials into the breasts for cosmetic augmentation is frequently seen and diagnosis based on the typical radiologic findings is straightforward. We report the unusual radiologic findings in two patients with foreign body granulomas caused by injected foreign materials and discovered incidentally during screening work up. The mammographic findings were bilateral, hyperdense, spiculated masses, with occasional microcalcification, and at sonography, markedly hypoechoic, spiculated solid masses, located near the pectoralis muscle and partly extending into it, were observed. These radiologic findings mimicked malignancy.

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Improvement of Sparse Representation based Classifier using Fisher Discrimination Dictionary Learning for Malignant Mass Detection (피셔 분별 사전학습을 이용해 개선된 Sparse 표현 기반 악성 종괴 검출)

  • Kim, Seong Tae;Lee, Seung Hyun;Min, Hyun-Seok;Ro, Yong Man
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.558-565
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    • 2013
  • Mammography, the process of using X-ray to examine the woman breast, is the one of the effective tools for detecting breast cancer at an early state. In screening mammogram, Computer-Aided Detection(CAD) system helps radiologist to diagnose cases by detecting malignant masses. A mass is an important lesion in the breast that can indicate a cancer. Due to various shapes and unclear boundaries of the masses, detecting breast masses is considered a challenging task. To this end, CAD system detects a lot of regions of interest including normal tissues. Thus it is important to develop the well-organized classifier. In this paper, we propose an enhanced sparse representation (SR) based classifier using Fisher discrimination dictionary learning. Experimental results show that the proposed method outperforms the existing support vector machine (SVM) classifier.

Relapsed Acute Myeloid Leukemia Presenting as Multiple Breast Masses: A Case Report (유방의 다발성 결절로 발현한 급성 골수성 백혈병 재발의 건: 증례 보고)

  • Pamela Sung;Jong Yoon Lee;A Jung Chu
    • Journal of the Korean Society of Radiology
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    • v.84 no.2
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    • pp.454-459
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    • 2023
  • Hematologic malignancy of the breast is very rare. Here, we report a case of relapsed acute myeloid leukemia (AML) presenting as multiple breast masses. A 77-year-old female visited an outpatient clinic reporting palpable masses in both breasts. She had a medical history of AML, which showed complete remission after nine cycles of chemotherapy. On mammography and ultrasonography, there were multiple masses correlated with her palpable symptoms accompanied by enlarged lymph nodes. Core needle biopsy immunohistochemistry (IHC) results indicated AML and blastic plasmacytoid dendritic cell neoplasm. AML was confirmed using bone marrow biopsy. Although very rare, when a patient with a history of hematologic malignancy presents a palpable mass in the breast, clinicians should conduct proper tissue analysis, including IHC stating for leukemic markers, to guide appropriate diagnosis and treatment.

An Automatic Breast Mass Segmentation based on Deep Learning on Mammogram (유방 영상에서 딥러닝 기반의 유방 종괴 자동 분할 연구)

  • Kwon, So Yoon;Kim, Young Jae;Kim, Gwang Gi
    • Journal of Korea Multimedia Society
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    • v.21 no.12
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    • pp.1363-1369
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    • 2018
  • Breast cancer is one of the most common cancers in women worldwide. In Korea, breast cancer is most common cancer in women followed by thyroid cancer. The purpose of this study is to evaluate the possibility of using deep - run model for segmentation of breast masses and to identify the best deep-run model for breast mass segmentation. In this study, data of patients with breast masses were collected at Asan Medical Center. We used 596 images of mammography and 596 images of gold standard. In the area of interest of the medical image, it was cut into a rectangular shape with a margin of about 10% up and down, and then converted into an 8-bit image by adjusting the window width and level. Also, the size of the image was resampled to $150{\times}150$. In Deconvolution net, the average accuracy is 91.78%. In U-net, the average accuracy is 90.09%. Deconvolution net showed slightly better performance than U-net in this study, so it is expected that deconvolution net will be better for breast mass segmentation. However, because of few cases, there are a few images that are not accurately segmented. Therefore, more research is needed with various training data.

Assessing the Potential of Thermal Imaging in Recognition of Breast Cancer

  • Zadeh, Hossein Ghayoumi;Haddadnia, Javad;Ahmadinejad, Nasrin;Baghdadi, Mohammad Reza
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.18
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    • pp.8619-8623
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    • 2016
  • Background: Breast cancer is a common disorder in women, constituting one of the main causes of death all over the world. The purpose of this study was to determine the diagnostic value of the breast tissue diseases by the help of thermography. Materials and Methods: In this paper, we applied non-contact infrared camera, INFREC R500 for evaluating the capabilities of thermography. The study was conducted on 60 patients suspected of breast disease, who were referred to Imam Khomeini Imaging Center. Information obtained from the questionnaires and clinical examinations along with the obtained diagnostic results from ultrasound images, biopsies and thermography, were analyzed. The results indicated that the use of thermography as well as the asymmetry technique is useful in identifying hypoechoic as well as cystic masses. It should be noted that the patient should not suffer from breast discharge. Results: The accuracy of asymmetry technique identification is respectively 91/89% and 92/30%. Also the accuracy of the exact location of identification is on the 61/53% and 75%. The approach also proved effective in identifying heterogeneous lesions, fibroadenomas, and intraductal masses, but not ISO-echoes and calcified masses. Conclusions: According to the results of the investigation, thermography may be useful in the initial screening and supplementation of diagnostic procedures due to its safety (its non-radiation properties), low cost and the good recognition of breast tissue disease.