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International Seminars in Surgical Oncology

, 3:8

First Online: 03 April 2006Received: 06 February 2006Accepted: 03 April 2006

Abstract

BackgroundIt is presently well accepted that the breast exhibits a circadian rhythm reflective of its physiology. There is increasing evidence that rhythms associated with malignant cells proliferation are largely non-circadian. Cancer development appears to generate its own thermal signatures and the complexity of these signatures may be a reflection of its degree of development. The limitations of mammography as a screening modality especially in young women with dense breasts necessitated the development of novel and more effective screening strategies with a high sensitivity and specificity. The aim of this prospective study was to evaluate the feasibility of dynamic thermal analysis DTA as a potential breast cancer screening tool.

Methods173 women undergoing mammography as part of clinical assessment of their breast symptoms were recruited prior to having a biopsy. Thermal data from the breast surface were collected every five minutes for a period of 48 hours using eight thermal sensors placed on each breast surface First Warning System FWS, Lifeline Biotechnologies, Florida, USA. Thermal data were recorded by microprocessors during the test period and analysed using specially developed statistical software. Temperature points from each contra-lateral sensor are plotted against each other to form a thermal motion picture of a lesion-s physiological activity. DTA interpretations positive abnormal thermal signature and negative normal thermal signature were compared with mammography and final histology findings.

Results118 68% of participating patients, were found to have breast cancer on final histology. Mammography was diagnostic of malignancy M5 in 55 47%, indeterminate M3, M4 in 54 46% and normal-benign M1, M2 in 9 8% patients. DTA data was available on 160 92.5% participants. Using our initial algorithm, DTA was interpreted as positive in 113 patients and negative in 47 patients. Abnormal thermal signatures were found in 76 72% out of 105 breast cancer patients and 37 of the 55 benign cases. Then we developed a new algorithm using multiple-layer perception and SoftMax output artificial neural networks ANN on a subgroup n = 38 of recorded files. The sensitivity improved to 76% 16-21 and false positives decreased to 26% 7-27

ConclusionDTA of the breast is a feasible, non invasive approach that seems to be sensitive for the detection of breast cancer. However, the test has a limited specificity that can be improved further using ANN. Prospective multi-centre trials are required to validate this promising modality as an adjunct to screening mammography especially in young women with dense breasts.

Electronic supplementary materialThe online version of this article doi:10.1186-1477-7800-3-8 contains supplementary material, which is available to authorized users.

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Author: M Salhab - LG Keith - M Laguens - W Reeves - K Mokbel

Source: https://link.springer.com/



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