Prognosis method to predict small-sized breast cancer affected by fibrocystic disease
The purpose of the study is to develop an effective radiological symptom-complex of small-sized breast cancer affected by fibrocystic breast disease by using multivariate statistical methods.Materials and methods. Radiological findings of small-sized breast cancer affected by fibrocystic mastopathy...
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| Format: | Article |
| Language: | English |
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Siberian State Medical University (Tomsk)
2017-04-01
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| Series: | Бюллетень сибирской медицины |
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| Online Access: | https://bulletin.ssmu.ru/jour/article/view/769 |
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| author | S. A. Velichko E. M. Slonimskaya I. G. Frolova D. G. Bukharin A. V. Doroshenko |
| author_facet | S. A. Velichko E. M. Slonimskaya I. G. Frolova D. G. Bukharin A. V. Doroshenko |
| author_sort | S. A. Velichko |
| collection | DOAJ |
| description | The purpose of the study is to develop an effective radiological symptom-complex of small-sized breast cancer affected by fibrocystic breast disease by using multivariate statistical methods.Materials and methods. Radiological findings of small-sized breast cancer affected by fibrocystic mastopathy were analyzed in 100 patients with histologically verified diagnosis.Results. It was revealed that the conventional approach to the analysis of mammograms based on the detection of the primary, secondary and indirect mammographic signs of small-sized breast cancer is not effective enough - the sensitivity of mammography is only 62%. Fibrocystic disease and moderate-to-severe sclerosing adenosis make small-sized breast cancer hard to visualize by mammography. The detailed analysis of mammograms allowed us to identify the additional manifestations of small-sized breast cancer affected by mastopathy. The computer program allowing us to evaluate the risk of small-size breast cancer and the diagnostic algorithm for detecting small size breast cancer with sensitivity of 92% were developed. |
| format | Article |
| id | doaj-art-53b39dffb13b47ecbbe43c1a0a61980f |
| institution | DOAJ |
| issn | 1682-0363 1819-3684 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | Siberian State Medical University (Tomsk) |
| record_format | Article |
| series | Бюллетень сибирской медицины |
| spelling | doaj-art-53b39dffb13b47ecbbe43c1a0a61980f2025-08-20T03:21:42ZengSiberian State Medical University (Tomsk)Бюллетень сибирской медицины1682-03631819-36842017-04-01161131910.20538/1682-0363-2017-1-13-19617Prognosis method to predict small-sized breast cancer affected by fibrocystic diseaseS. A. Velichko0E. M. Slonimskaya1I. G. Frolova2D. G. Bukharin3A. V. Doroshenko4Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)The purpose of the study is to develop an effective radiological symptom-complex of small-sized breast cancer affected by fibrocystic breast disease by using multivariate statistical methods.Materials and methods. Radiological findings of small-sized breast cancer affected by fibrocystic mastopathy were analyzed in 100 patients with histologically verified diagnosis.Results. It was revealed that the conventional approach to the analysis of mammograms based on the detection of the primary, secondary and indirect mammographic signs of small-sized breast cancer is not effective enough - the sensitivity of mammography is only 62%. Fibrocystic disease and moderate-to-severe sclerosing adenosis make small-sized breast cancer hard to visualize by mammography. The detailed analysis of mammograms allowed us to identify the additional manifestations of small-sized breast cancer affected by mastopathy. The computer program allowing us to evaluate the risk of small-size breast cancer and the diagnostic algorithm for detecting small size breast cancer with sensitivity of 92% were developed.https://bulletin.ssmu.ru/jour/article/view/769breast cancermammographymammographic signs of small size breast cancerfibrocystic disease |
| spellingShingle | S. A. Velichko E. M. Slonimskaya I. G. Frolova D. G. Bukharin A. V. Doroshenko Prognosis method to predict small-sized breast cancer affected by fibrocystic disease Бюллетень сибирской медицины breast cancer mammography mammographic signs of small size breast cancer fibrocystic disease |
| title | Prognosis method to predict small-sized breast cancer affected by fibrocystic disease |
| title_full | Prognosis method to predict small-sized breast cancer affected by fibrocystic disease |
| title_fullStr | Prognosis method to predict small-sized breast cancer affected by fibrocystic disease |
| title_full_unstemmed | Prognosis method to predict small-sized breast cancer affected by fibrocystic disease |
| title_short | Prognosis method to predict small-sized breast cancer affected by fibrocystic disease |
| title_sort | prognosis method to predict small sized breast cancer affected by fibrocystic disease |
| topic | breast cancer mammography mammographic signs of small size breast cancer fibrocystic disease |
| url | https://bulletin.ssmu.ru/jour/article/view/769 |
| work_keys_str_mv | AT savelichko prognosismethodtopredictsmallsizedbreastcanceraffectedbyfibrocysticdisease AT emslonimskaya prognosismethodtopredictsmallsizedbreastcanceraffectedbyfibrocysticdisease AT igfrolova prognosismethodtopredictsmallsizedbreastcanceraffectedbyfibrocysticdisease AT dgbukharin prognosismethodtopredictsmallsizedbreastcanceraffectedbyfibrocysticdisease AT avdoroshenko prognosismethodtopredictsmallsizedbreastcanceraffectedbyfibrocysticdisease |