A prospective evaluation of breast thermography enhanced by a novel machine learning technique for screening breast abnormalities in a general population of women presenting to a secondary care hospital - Bansal, Richa; Collison, Sathiakar; Krishnan, Lakshmi; Aggarwal, Bharat; Vidyasagar, Mathukumalli; Kakileti, Siva Teja; Manjunath, Geetha (Frontiers in Artificial Intelligence, 2023)
Objective: Artificial intelligence enhanced breast thermography is being evaluated as an ancillary modality in the evaluation of breast disease. The objective of this study is to evaluate clinical performance of Thermalytix, a CE-marked AI-based thermal imaging test in comparison with conventional mammography. Methods: A prospective, comparative study performed between 15 December 2018 and 06 January 2020 evaluated the performance of Thermalytix in 459 women with both dense and non-dense breast tissue. Both symptomatic and asymptomatic women, aged 30 to 80 years, presenting to hospital underwent Thermalytix followed by 2-D mammography and appropriate confirmatory investigations to confirm malignancy. The radiologist interpreting mammograms and technician using Thermalytix tool were blinded to the others' findings. The statistical analysis was performed by a third party. Results: 687 women were recruited and 459 women fulfilled inclusion criteria. 21 malignancies were detected (21/459, 4.6%). Overall sensitivity of Thermalytix was 95.24% (95% CI, 76.18-99.88) and specificity 88·58% (95% CI, 85.23-91.41). In those with dense breasts (n=168, 36.6%), sensitivity was 100% (95% CI, 69.15-100) and specificity 81.65% (95% CI, 74.72-87.35). Among these 168 women, 37 women (22%) were reported as BI-RADS 0 on mammograms; in this subset, the sensitivity of Thermalytix was 100% (95% CI, 69.15-100) and specificity 77.22% (95% CI, 69.88-83.50). Conclusion: Thermalytix has shown acceptable sensitivity and specificity when compared with mammography in the overall patient population. Thermalytix outperformed mammography in dense breasts and those reported as BI-RADS 0.