Risk of breast cancer based on thermal tomography characteristics

BACKGROUND: There is no uniform standard for the diagnosis of breast lesions by thermal tomography (TT). This study aimed to widely analyse the predictive value of TT in patients with breast cancer and establish a uniform standard for the diagnosis of breast lesions. METHODS: We retrospectively analysed data from women who suffered from non-inflammatory unilateral single breast lesion and underwent TT from January 2014 to July 2016. Changes in TT parameters were correlated with the pathologic diagnosis, and its predictive value was assessed. RESULTS: A total of 407 patients underwent TT examinations during the study period, including 196 subsequently diagnosed with breast cancer. Several characteristics were found to be significantly correlated with breast cancer: age ≥60 years [odds ratio (OR) =109.296, P<0.001], age ≥35 and <60 years (OR =25.720, P<0.001), q-r curve as an angle of 30°–45° (OR =14.895, P<0.001), ΔTs (surface temperature difference between the neoplastic side and the healthy side) ≥0.65 °C (OR =4.129, P<0.001), ΔTn (nipple temperature difference between the neoplastic side and the healthy side) ≥0.45 °C (OR =2.683, P=0.006), isotherm asymmetry (OR =2.297, P=0.035), and vascular plentiful (OR =3.333, P=0.004). Q value as a novel predictive indicator based on the multiple predictor modelling improved the diagnostic rate for breast cancer, and the accuracy in this study was up to 86.7%. CONCLUSIONS: Age, q-r curve, ΔTs, ΔTn, isotherm, and vascular features were independent predictors of breast cancer. Q value could be used to assess the risk of breast cancer as an additional diagnostic tool for breast cancer screening and diagnosis.