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ABSTRACT: To evaluate the diagnostic approach and criteria for intraductal papillary neoplasms of breast.
According to the criteria of 2003 WHO classification, 187 cases of intraductal papillary neoplasm of breast were identified and enrolled into the study. The clinical and histologic features were reviewed and immunohistochemical study for CD10, p63, CK14, CK5/6, CK7, MGB1 and p53 were carried out on 53 cases.
Amongst the 187 cases studied, there were 128 cases of intraductal papilloma, 16 cases of atypical intraductal papilloma and 43 cases of intraductal papillary carcinoma. They showed a spectrum of morphologic features including epithelial and stromal hyperplasia and secondary changes. The expression of myoepithelial markers, including CD10 and p63, significantly decreased in ascending order from intraductal papillomas, atypical intraductal papillomas and intraductal papillary carcinomas (P < 0.001). The expression of basal cell markers, including CK5/6 and CK14, showed a mosaic pattern in benign lesions and significantly decreased or was absent in atypical and carcinomatous lesions (P < 0.001). In contrast, the luminal cell marker CK7 expressed in the three groups with no statistically significant difference (P = 0.06). On the other hand, the expression of MGB1 in intraductal papillary carcinomas was much lower than that in the other two groups (P = 0.002 and P = 0.007). The staining for p53 was negative in all of the three groups.
Intraductal papillary neoplasms of breast represent a heterogeneous group of lesions with various morphologic appearances. Correlation with immunostaining results for myoepithelial markers, basal-type cytokeratins and luminal epithelial markers are helpful in arriving at a definitive diagnosis.
Zhonghua bing li xue za zhi Chinese journal of pathology 11/2011; 40(11):726-31.
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ABSTRACT: To investigate the relationship between Ki67 expression and tumor response to neoadjuvant chemotherapy with anthracyclines plus taxanes in breast cancer.
From January 2008 to June 2009, 129 patients with primary breast invasive ductal cancer received neoadjuvant chemotherapy with anthracyclines plus taxanes. The expression of Ki67 in the tumor tissues was determined by using immunohistochemistry with core needle biopsy specimens prior to the chemotherapy. The tumor response to the chemotherapy was evaluated by dynamic enhanced MRI based on RECIST2000 criteria, pathologic response was assessed according to Miller-Payne grading system, and the clinical comprehensive response was evaluated based on MRI combined with pathologic response.
Dynamic enhanced MRI classified 87 cases (67.4%) as effective. According to the Miller-Payne grading system, 99 cases (76.7%) were ranged effective. One hundred and ten cases (85.5%) were recognized as clinically comprehensive effective. The effective rates of neoadjuvant chemotherapy in patients with a Ki67 expression >10% evaluated by the above-mentioned three standards were 73.2%, 81.4% and 89.7%, respectively; and those in patients with a Ki67 expression < or = 10% were 50.0%, 62.5% and 71.9%, respectively. Compared with patients with a Ki67 expression < or = 10%, the patients with a Ki67 expression >10% had better response rates determined by all the three standards (P values were 0.020, 0.030 and 0.010, respectively). The Ki67 expression in the tumor tissue was linearly correlated with clinically comprehensive response on the Linear-Linear association analysis.
There is a statistic association between Ki67 expression and tumor response to the neoadjuvant chemotherapy with anthracyclines plus taxanes in breast cancer, and the patients with a higher expression of Ki67 has a better tumor response to the chemotherapy.
Zhonghua wai ke za zhi [Chinese journal of surgery] 03/2010; 48(6):450-3.
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International Conference on Machine Learning and Cybernetics, ICMLC 2010, Qingdao, China, July 11-14, 2010, Proceedings; 01/2010
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ABSTRACT: The aim of this study is to investigate the changes of expression of estrogen receptors (ER), progesterone receptors (PR), Her-2, Ki-67 and histological grade after neoadjuvant chemotherapy in breast cancer.
Sixty-seven patients with histopathalogically confirmed breast cancer by core needle biopsy received neoadjuvant chemotherapy. The effect of neoadjuvant chemotherapy was assessed according to the criteria of the Japanese Breast Cancer Society: non-effective (G1), mildly effective (G2), moderately effective (G3), markedly effective (G4) and completely effective (G5). All pathological slides were retrospectively reviewed. Immunohistochemical staining (EnVision method) was used to detect the expression of ER and PR, Her-2 and Ki-67. The pre- and post-neoadjuvant chemotherapy status of tumor histological grade, ER and PR, Her-2 and Ki-67 expression in the 49 cases were compared.
The effect of neoadjuvant chemotherapy was assessed in 67 patients. There were 5 cases (7.5%) in G1, 19 in G2 (28.4%), 20 in G3 (29.9%), 17 in G4 (25.4%) and 6 in G5 (9.0%), respectively. PR positive rate was 71.4% after chemotherapy versus 91.8% before chemotherapy, with a statistically significant reduction (P = 0.021). However, the ER and Her-2 expression before and after neoadjuvant chemotherapy was stable. Of the patients with invasive ductal carcinoma, 28.6% had histological grade change after neoadjuvant chemotherapy, and 85.7% of patients decreased one grade. The proportion of histological grade change in the G1, G2, G3, G4 were 0, 5.9%, 41.2% and 54.5%, respectively (P = 0.013). The average rate of Ki-67 expression decreased from 28.3% pre-chemotherapy to 11.0% post-chemotherapy (P = 0.011). After the neoadjuvant chemotherapy, the Ki-67 expression rate decreased by > 10%, > 20%, > 30%, > 40% and > 50% in 3 groups (G1 and G2, group G3, group G4 and G5) showed a tendency to be increased, with a significant difference (P < 0.05).
PR expression in breast cancer decreases after neoadjuvant chemotherapy, while ER and Her-2 expressions remain stable. After neoadjuvant chemotherapy, the histological grade and proliferation index are decreased and correlated with the response to chemotherapy. Therefore, histological grade and proliferation index may be effective complementary factors in assessment of the effectiveness of neoadjuvant chemotherapy.
Zhonghua zhong liu za zhi [Chinese journal of oncology] 11/2009; 31(11):858-62.
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Emerging Intelligent Computing Technology and Applications, 5th International Conference on Intelligent Computing, ICIC 2009, Ulsan, South Korea, September 16-19, 2009. Proceedings; 01/2009
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ABSTRACT: Reporting a rare case with Kimura's disease and angiolymphoid hyperplasia with eosinophilia (ALHE), who also has nephrotic syndrome resulting from minimal change glomerulopathy.
Histological manifestations, immunohistochemical staining, immunofluorescence staining, and electron microscope were performed.
One 37-year-old male patient with recurrent erythra, cutaneous node, painless cervical lymph node enlargement and nephrotic syndrome in 5 years. It's confirmed through biopsies that the subcutaneous node is ALHE, the cervical lymph node is kimura disease, and renal lesion is minimal change glomerulopathy.
Kimura disease and ALHE may be different features of the same disease, and may complicate glomerulopathy.
Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences 09/2008; 40(4):405-7.
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ABSTRACT: In this paper, an on-line signature verification system exploiting local and global information using two-stage fusion is presented. At the first stage, global information is extracted as 13-dimensional vector and recognized by majority classifiers, and then local information is extracted as time functions of various dynamic properties and recognized by BP neural network classifier. By fusing global and local information and introducing an enhanced dynamic time warping algorithm and a normalized feature measure, our method obtained an average EER of 4.02% on public database SVC2004 (first signature verification competition 2004) Task2 compared to 6.90% the first place at SVC2004.
Machine Learning and Cybernetics, 2008 International Conference on; 08/2008
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ABSTRACT: This paper considers the combination of face and gait biometrics from the same walking sequence to carry out gender recognition. A camera is capturing the side view of a person, while another camera is placed to record the face of the same person at the front view. After these videos are acquired, we extract the silhouette images from the gait videos and normalized frame images decomposed from the face videos. Then, for face classification, we introduce PCA to reduce the image dimension and SVM to classify gender, for gait classification, we divide the silhouette into seven parts and extract features from each and also employ SVM to classify gender. On the decision level, the sum rule is applied to implement the fusion of these two classification results. The final fusion results show an improvement on correct classification rate.
Machine Learning and Cybernetics, 2008 International Conference on; 08/2008
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ABSTRACT: Vein pattern is used as biometric feature in recent 20 years and It attracts much attention from 2000. A complete vein pattern recognition system contains three key procedures, vein image collection, vein pattern segment and feature extraction. In this paper, we adopt low-cost collection devices and discuss all the three parts in details. First a novel image collection way is proposed, which could enhance the contrast. Then a denoising algorithm using wavelets thresholding based on Besov norm regularization is discussed. This algorithm could remove the high noise while do not hurt the contrast. Finally, two novel robust features specially designed for vein pattern are put forward. Experimental results show that our system is as successful as traditional high-price system. In conclusion, our research makes using low-cost devices to recognize vein patterns possible.
Machine Learning and Cybernetics, 2008 International Conference on; 08/2008
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ABSTRACT: In this paper, a neural network based algorithm is used in the intrusion detection. Moreover, we propose a fusion method combine several neural network classifiers. Experimental results show that the proposed method is an encouraging intrusion detection manner.
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on; 12/2007
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ABSTRACT: In this paper, we propose a method to examine whether a walking person is carrying objects using the width of human body contour. First we concentrate on the detection of the moving people contour and then human contour width is projected to the feature space for training a classifier. We introduce principal component analysis for dimension reduction and support vector machine to classify the carrying object status. If the status is true, the carrying object region is figured out by analyzing human contour shape. We utilize the outmost vertex from human contour to track the carrying object such as a rucksack or luggage. The experimental results demonstrate that our approach is encouraging.
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on; 12/2007
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ABSTRACT: Face recognition is one of the most successful applications in biometric authentication. However, methods reported in the literature are far from perfect and deteriorate ungracefully where lighting condition cannot be controlled. This paper presents a new robust method for face recognition under near infrared lighting condition based on AdaBoost Gabor features with linear discriminant analysis classification (ALGabor), which solves the problems produced by variations of illumination rightly, since the NIR images are insensitive to variations of environmental lighting, and Gabor wavelets can extract adequate features form the images. To gain the qualified NIR images, a device has been designed. Gabor wavelets are used to extract the features form the NIR images. Although Gabor feature vectors often have very high dimensions, a classifier has been trained using the AdaBoost algorithm to select the most representative feature. Compared with the huge number of features produced by typical Gabor wavelets, the classifier in this paper only selects hundreds of features, which saves computation and time cost significantly. The comparison between the results of the method in this paper and several classic algorithms proves the effectiveness of the proposed method.
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on; 12/2007
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ABSTRACT: Automatic signature verification has been an intense research area because of the social and legal acceptance and widespread use of written signatures. It is still a challenging issue because of "small sample size " problem as well as large intra-class variations and, when considering forgeries, small inter-class variations. In order to solve these problems, we propose a two-stage fusion method to get high accuracy. At first, an EDTW (enhanced dynamic time warping) algorithm and a normalized feature measure are proposed to build a classifier based on local features. The former enhances the separability between genuine and forgery signatures, while the latter approaches the problem as a two-class pattern recognition problem, which make it possible to use training signatures as many as possible. However, local method is time and resource consuming, so we then design another classifier based on global features using majority voting rule. We fuse the global and local method by two-sage serial strategy to build an on-line signature verification system. Experimental results on SVC2004 TASK2 show good performance of our system.
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on; 12/2007
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ABSTRACT: In this paper, we propose a novel algorithm for gait recognition. Binarized silhouette of a motion object is first segmented from color image, and then, spatio-temporal (XYT) volume is constructed by using these binarized silhouettes, and cut at knee and hip height. Next, energy images are extracted by projecting these three individual XYT volumes onto X-T plane, respectively. Fourier transform is employed as a processing step to achieve translation invariant for the silhouette sequences which are captured from the subjects walk in different speed. Then three frequency-domain feature vectors are fused. AdaBoost is used to select a small set of critical features from all of the features. Nearest neighbor and support vector machine (SVM) classifier are finally executed to produce final decision, respectively. The experiments are carried on one of the largest public gait database: the CASIA database. The experimental results show that the proposed algorithm is efficient for human gait recognition, and achieves competitive performance.
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on; 12/2007
