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Moon, Woo Kyung,Huang, Yao-Sian,Lo, Chung-Ming,Huang, Chiun-Sheng,Bae, Min Sun,Kim, Won Hwa,Chen, Jeon-Hor,Chang, Ruey-Feng Published for the American Association of Physicis 2015 Medical physics Vol.42 No.6
<P>Triple-negative breast cancer (TNBC), an aggressive subtype, is frequently misclassified as fibroadenoma due to benign morphologic features on breast ultrasound (US). This study aims to develop a computer-aided diagnosis (CAD) system based on texture features for distinguishing between TNBC and benign fibroadenomas in US images.</P>
Chen, Jeon-Hor,Huang, Chiun-Sheng,Chien, Kuang-Che Chang,Takada, Etsuo,Moon, Woo Kyung,Wu, Jeffery H. K.,Cho, Nariya,Wang, Yi-Fa,Chang, Ruey-Feng Wiley (John WileySons) 2009 Medical physics Vol.36 No.11
<P>Breast density has been established as an independent risk factor associated with the development of breast cancer. The terms mammographic density and breast density are often used interchangeably, since most breast density studies are performed with projection mammography. It is known that increase in mammographic density is associated with an increased cancer risk. A sensitive method that allows for the measurement of small changes in breast density may provide useful information for risk management. Despite the efforts to develop quantitative breast density measurements from projection mammograms, the measurements show large variability as a result of projection imaging, differing body position, differing levels of compression, and variation of the x-ray beam characteristics. This study used two separate computer-aided methods, threshold-based and proportion-based evaluations, to analyze breast density on whole breast ultrasound (US) imaging and to compare with the grading results of three radiologists using projection mammography. Thirty-two female subjects with 252 images per case were included in this study. Whole breast US images were obtained from an Aloka SSD-5500 ultrasound machine with an ASU-1004 transducer (Aloka, Japan). Before analyzing breast density, an adaptive speckle reduction filter was used for removing speckle noise, and a robust thresholding algorithm was used to divide breast tissue into fatty or fibroglandular classifications. Then, the proposed approaches were applied for analysis. In the threshold-based method, a statistical model was employed to determine whether each pixel in the breast region belonged to fibroglandular or fatty tissue. The proportion-based method was based on three-dimensional information to calculate the volumetric proportion of fibroglandular tissue to the total breast tissue. The experimental cases were graded by the proposed analysis methods and compared with the ground standard density classification assigned by a majority voting of three experienced breast radiologists. For the threshold-based method, 28 of 32 US test cases and for the proportion-based density classifier, 27 of 32 US test cases were found to be in agreement with the radiologist 'ground standard' mammographic interpretations, resulting in overall accuracies of 87.5% and 84.4%, respectively. Moreover, the concordance values of the proposed methods were between 0.0938 and 0.1563, which were less than the average interobserver concordance of 0.3958. The experiment result showed that the proposed methods could be a reference opinion and offer concordant and reliable quantification of breast density for the radiologist.</P>
Woo Kyung Moon,Yi-Wei Shen,Min Sun Bae,Chiun-Sheng Huang,Jeon-Hor Chen,Ruey-Feng Chang IEEE 2013 IEEE transactions on medical imaging Vol.32 No.7
<P>Automated whole breast ultrasound (ABUS) is an emerging screening tool for detecting breast abnormalities. In this study, a computer-aided detection (CADe) system based on multi-scale blob detection was developed for analyzing ABUS images. The performance of the proposed CADe system was tested using a database composed of 136 breast lesions (58 benign lesions and 78 malignant lesions) and 37 normal cases. After speckle noise reduction, Hessian analysis with multi-scale blob detection was applied for the detection of tumors. This method detected every tumor, but some nontumors were also detected. The tumor likelihoods for the remaining candidates were estimated using a logistic regression model based on blobness, internal echo, and morphology features. The tumor candidates with tumor likelihoods higher than a specific threshold (0.4) were considered tumors. By using the combination of blobness, internal echo, and morphology features with 10-fold cross-validation, the proposed CAD system showed sensitivities of 100%, 90%, and 70% with false positives per pass of 17.4, 8.8, and 2.7, respectively. Our results suggest that CADe systems based on multi-scale blob detection can be used to detect breast tumors in ABUS images.</P>
Moon, Woo Kyung,Chang, Jie-Fan,Lo, Chung-Ming,Chang, Jung Min,Lee, Su Hyun,Shin, Sung Ui,Huang, Chiun-Sheng,Chang, Ruey-Feng Elsevier 2018 Computer methods and programs in biomedicine Vol.154 No.-
<P><B>Abstract</B></P> <P><B>Background and Objective</B></P> <P>Breast density at mammography has been used as markers of breast cancer risk. However, newly introduced tomosynthesis and computer-aided quantitative method could provide more reliable breast density evaluation.</P> <P><B>Methods</B></P> <P>In the experiment, 98 tomosynthesis image volumes were obtained from 98 women. For each case, an automatic skin removal was used and followed by a fuzzy c-mean (FCM) classifier which separated the fibroglandular tissues from other tissues in breast area. Finally, percent of breast density and breast volume were calculated and the results were compared with MRI. In addition, the percent of breast density and breast area of digital mammography calculated using the software Cumulus (University of Toronto, Toronto, ON, Canada.) were also compared with 3-D modalities.</P> <P><B>Results</B></P> <P>Percent of breast density and breast volume, which were computed from tomosynthesis, MRI and digital mammography were 17.37% ± 4.39% and 607.12 cm<SUP>3</SUP> ± 323.01 cm<SUP>3</SUP>, 20.3% ± 8.6% and 537.59 cm<SUP>3</SUP> ± 287.74 cm<SUP>3</SUP>, and 12.03% ± 4.08%, respectively. There were significant correlations on breast density as well as volume between tomosynthesis and MRI (<I>R</I> = 0.482 and <I>R</I> = 0.805), tomosynthesis and breast density with breast area of digital mammography (<I>R</I> = 0.789 and <I>R</I> = 0.877), and MRI and breast density with breast area of digital mammography (<I>R</I> = 0.482 and <I>R</I> = 0.857) (all <I>P</I> values < .001).</P> <P><B>Conclusions</B></P> <P>Breast density and breast volume evaluated from tomosynthesis, MRI and breast density and breast area of digital mammographic images have significant correlations and indicate that tomosynthesis could provide useful 3-D information on breast density through proposed method.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We proposed a quantitative method to estimate breast density and compared tomosynthesis with MRI and digital mammography. </LI> <LI> An automatic skin removal was adopted and a FCM classifier was used to separate the fibroglandular tissues from breast area. </LI> <LI> There were significant correlations between tomosynthesis with MRI and with digital mammography values < . </LI> <LI> Tomosynthesis could provide useful 3-D information on breast density through proposed method. </LI> <LI> We discovered and solved the problem of the different expression of aggregated fibroglandular tissue in different modalities. </LI> </UL> </P>
Ke, Meng-Wei,Jiang, Yan-Nian,Li, Yi-Hung,Tseng, Ting-Yu,Kung, Ming-Shung,Huang, Chiun-Sheng,Cheng, Winston Teng-Kuei,Hsu, Jih-Tay,Ju, Yu-Ten Asian Australasian Association of Animal Productio 2007 Animal Bioscience Vol.20 No.6
Caveolin-1 of the caveolin family of proteins regulates mammary gland development and has been shown to play a contradictory role in breast tumor progression. A specific anti-Caveolin-1 antibody will be useful for functional study of Caveolin-1 in different tissues. In this study, we generated a rabbit polyclonal antibody that specifically recognizes the N-terminal amino acids 50-65 of Caveolin-1. This polyclonal antibody specifically reacted with Caveolin-1 extracted from cells of different species, including human epithelial A431 cells, goat primary mammary epithelial cells and mice fibroblast NIH 3T3 cells, by Western blotting. Endogenous Caveolin-1 protein expressing in cells and normal human tissues was detected by this polyclonal antibody using immunocytofluorescent and immunohistochemical staining, respectively. Furthermore, an apparent decrease in Caveolin-1 expression in tumorous breast and colon tissues was detected by this polyclonal antibody. In conclusion, we have identified amino acids 50-65 of Caveolin-1, which contains an epitope that is specific to Caveolin-1 and is conserved in the human, goat and mouse. In future, this anti-Caveolin-1 antibody can be used to examine the progression of breast and colon cancers and to study functions of Caveolin-1 in human, goat and mouse cells.
Po-Han Lin,Yun-Wen Tien,Wen-Fang Cheng,Ying-Cheng Chiang,Chien-Huei Wu,Karen Yang,Chiun-Sheng Huang 대한부인종양학회 2023 Journal of Gynecologic Oncology Vol.34 No.5
Objective: Genetic high-risk assessment combines hereditary breast, ovarian and pancreatic cancer into one syndrome. However, there is a lack of data for comparing the germline mutational spectrum of the cancer predisposing genes between these three cancers. Methods: Patients who met the criteria of the hereditary breast, ovarian and pancreatic cancer were enrolled and received multi-gene sequencing. Results: We enrolled 730 probands: 418 developed breast cancer, 185 had ovarian cancer, and 145 had pancreatic cancer. Out of the 18 patients who had two types of cancer, 16 had breast and ovarian cancer and 2 had breast and pancreatic cancer. A total of 167 (22.9%) patients had 170 mutations. Mutation frequency in breast, ovarian and pancreatic cancer was 22.3%, 33.5% and 17.2%, respectively. The mutation rate was significantly higher in patients with double cancers than those with a single cancer (p<0.001). BRCA1 and BRCA2 were the most dominant genes associated with hereditary breast and ovarian cancer, whereas ATM was the most prevalent gene related to hereditary pancreatic cancer. Genes of hereditary colon cancer such as lynch syndrome were presented in a part of patients with pancreatic or ovarian cancer but seldom in those with breast cancer. Families with a history of both ovarian and breast cancer were associated with a higher mutation rate than those with other histories. Conclusion: The mutation spectrum varies across the three cancer types and family histories. Our analysis provides guidance for physicians, counsellors, and counselees on the offer and uptake of genetic counseling.