• 제목/요약/키워드: Breast masses

검색결과 74건 처리시간 0.021초

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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    • 제16권3호
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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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    • 제20권5호
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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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    • 제21권9호
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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.

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

  • 김민정;조현종
    • 전기학회논문지
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    • 제66권8호
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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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    • 제21권5호
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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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    • 제2권2호
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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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피셔 분별 사전학습을 이용해 개선된 Sparse 표현 기반 악성 종괴 검출 (Improvement of Sparse Representation based Classifier using Fisher Discrimination Dictionary Learning for Malignant Mass Detection)

  • 김성태;이승현;민현석;노용만
    • 한국멀티미디어학회논문지
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    • 제16권5호
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    • pp.558-565
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    • 2013
  • X-ray를 이용한 여성의 유방암 검사인 유방조영술은 유방암의 초기 단계에서의 진단을 위한 효과적인 방법이다. 컴퓨터 지원 검출(CAD) 시스템은 유방조영술을 통한 진단 시 의사가 놓치기 쉬운 유방암의 징후인 종괴의 검출을 도와 유방암 진단율을 높이는 수단이다. 종괴는 다양한 모양을 지니며 경계가 뚜렷하지 않기 때문에 검출이 어렵고 결과적으로 비-종괴 영역을 포함한 많은 수의 종괴 후보영역이 CAD 시스템에서 검출된다. 따라서 CAD 시스템 설계 시 검출된 많은 수의 종괴 후보영역으로부터 실제 악성 종괴 영역을 분류할 수 있도록 우수한 성능의 분류기가 요구된다. 본 논문에서는 피셔 분별 사전학습을 통해 개선된 Sparse 표현(SR) 기반 분류방법을 제안한다. 개선된 SR 기반 분류기가 기존의 CAD 시스템에서 주로 사용되어온 Support Vector Machine (SVM) 분류기 보다 우수함을 비교실험을 통해 확인했다.

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

  • 성지연;이종윤;추아정
    • 대한영상의학회지
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    • 제84권2호
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    • pp.454-459
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    • 2023
  • 유방을 침범하는 혈액종양은 굉장히 드물게 보고되었다. 우리는 유방의 다발성 결절로써 재발한 급성 골수성 백혈병의 증례를 보고하고자 한다. 77세 여자 환자가 양측 유방의 촉지되는 다발성 결절로 외래를 내원하였다. 환자는 급성 골수성 백혈병(acute myeloid leukemia; 이하 AML)으로 진단받고 9차례의 항암치료 이후 완전 관해가 된 병력이 있었다. 유방 촬영과 유방 초음파에서 환자의 촉지성 병변이 영상의학적으로 확인되었으며 액와부 림프절 종대도 동반되었다. 총생검으로 얻은 검체는 면역화학염색을 통해 AML과 blastic plasmacytoid dendritic cell neoplasm의 형태를 보였으며 추후 진행한 골수 생검에서 AML로 확인되었다. 이렇듯 굉장히 드물지만, 혈액암의 병력을 가진 환자가 유방의 촉지성 종괴로 내원하였다면 담당의는 적절한 조직검사 및 면역화학검사로 정확한 진단을 하여 환자가 적절한 치료를 받도록 해야 한다.

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

  • 권소윤;김영재;김광기
    • 한국멀티미디어학회논문지
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    • 제21권12호
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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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    • 제16권18호
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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.