Prognosis method to predict small-sized breast cancer affected by fibrocystic disease
https://doi.org/10.20538/1682-0363-2017-1-13-19
Abstract
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.
About the Authors
S. A. Velichko
Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)
Russian Federation
Russian Federation
DM, Professor, Principal Researcher, Imaging Department,
12/а, Savinuh Str., Tomsk, 634028
E. M. Slonimskaya
Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)
Russian Federation
Russian Federation
DM, Professor, Head of General Oncology Department,
12/а, Savinuh Str., Tomsk, 634028
I. G. Frolova
Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)
Russian Federation
Russian Federation
DM, Professor, Head of Diagnostic Imaging Department,
12/а, Savinuh Str., Tomsk, 634028
D. G. Bukharin
Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)
Russian Federation
Russian Federation
PhD, Diagnostic Imaging Department,
12/а, Savinuh Str., Tomsk, 634028
A. V. Doroshenko
Tomsk Cancer Research Institute, Tomsk National Research Medical Center (TNRMC), Russian Academy of Sciences (RAS)
Russian Federation
Russian Federation
PhD, General Oncology Department,
12/а, Savinuh Str., Tomsk, 634028
References
1. Rozhkova N.I. Luchevay diagnostica v mammologii [Diagnostic imaging of the breast]: rucovodstvo dla vrachey [Manual for Physicians]. М: Spezizdat Publ., 2014: 128 (in Russian).
2. Odintsova I.N. Epidimiologiy raca molochnoy gelezu v regione Sibiri i Dalnego Vostoca [Epidemiology of breast cancer in the region of Siberia and Russian Far East] // DSc thesis. Tomsk, 2011: 42 (in Russian).
3. Chissov V.I., Starinskiy V.V., Petrova G.V. Novoobrazovaniay v Rossii (zabolevaemost I smertnost) [Cancer in Russia (incidence and mortality)]. M.: Center of information technologies and epidemiological studies in the field of oncology Publ., 2012: 268 (in Russian).
4. Colin C., Prince V., Valette P.J. Can mammographic assessments lead to concider density as a risk factor for breast cancer? // Eur. J. Radiol. 2013; 82 (3): 404–411.
5. Smetherman D., Fathi Gowharji L. Clinical images: Radial scar of the breast // Ochsner J. 2015; 15 (3): 219–222.
6. Korzhenkova G.P. Verificaziay nepalpiruemuh obrazovaniy molochnoy gelezu na dooperazionnom etape [Verification of non-palpable breast lesions in preoperative period] // Radiolodiya – Practica – Radiology – Practice. 2013; 2: 14–16 (in Russian).
7. Koa K., Hsua H., Yub J.-Ch. et al. Non-mass-like breast lesions at ultrasonography: Feature analysis and BI-RADS assessment // Eur. J. Radiol. 2015; 84 (1): 1–194.
8. Bukharin D.G., Velichko S.A., Slonimskaya E.M., Frolova I.G., Doroshenko A.V., Tolmachev I.V. Patent № 2547802 Sposob prognozirovaniay risca vuyavleniya maluh form raca molochnoy gelezu na fone fibrozno-cistoznoy bolezni [The method for predicting the risk of small size breast cancer occurring concurrently with fibrocystic disease], 2015 (in Russian).
Review
For citations:
Velichko S.A., Slonimskaya E.M., Frolova I.G., Bukharin D.G., Doroshenko A.V. Prognosis method to predict small-sized breast cancer affected by fibrocystic disease. Bulletin of Siberian Medicine. 2017;16(1):13-19. (In Russ.) https://doi.org/10.20538/1682-0363-2017-1-13-19
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