ABSTRACT
INTRODUCTION: Machine learning in computer-assisted diagnostics improves sensitivity of image analysis and reduces time and effort for interpretation. Compared to standard mammograms, a thermal scan is easily scalable and is a safer screening tool. We evaluate the performance of Thermalytix (an automated thermographic screening algorithm) compared with other standard breast cancer screening modalities. METHODS: A prospective multicentre study was conducted to assess the non-inferiority of sensitivity of Thermalytix (test device) to that of standard modalities in detecting malignancy in subjects who show possible symptoms of suspected breast cancer. Standard screening modalities and Thermalytix were obtained and interpreted independently in a blinded fashion. A receiver operating characteristic (ROC) curve was constructed to identify the best cut-off point, non-inferiority margin of ≥10% to demonstrate the non-inferiority. RESULTS: We recruited 258 symptomatic women who first underwent a thermal scan, followed by mammogram and/or ultrasound. At Youden's Index of ROC curve, the test device had a sensitivity of 82.5% (95% CI 73.2 to 91.9) and specificity of 80.5% (95% CI 75.0 to 86.1) as compared with diagnostic mammogram, which had sensitivity of 92% (95% CI 80.7 to 97.8) and specificity of 45.9% (95% CI 34.3 to 57.9) when BI-RADS 3 (Breast Imaging-Reporting and Data System) was considered as test-positive. The overall area under the curve (AUC) was 0.845. For women aged <45 years, the test device had a sensitivity and specificity of 87.0% (95% CI 66.4 to 97.2) and 80.6% (95% CI 72.9 to 86.9), respectively. For women aged ≥45 years, the sensitivity and specificity were 80.5% (95% CI 65.1 to 91.2) and 86.5% (95% CI 78.0 to 92.6, respectively). CONCLUSION: We evaluated Thermalytix, a new AI-based modality for detecting breast cancer. The high AUC in both women under 45 years and above 45 years shows the potential of Thermalytix to be a supplemental diagnostic modality for all ages. Further evaluation on larger sample size is needed. TRIAL REGISTRATION NUMBER: CTRI/2017/10/0 10 115.
