Prospective Blinded evaluation of Thermalytix, an artificial intelligence-enhanced breast thermal imaging software, correlated with radiologist-interpreted mammograms: Results of an exploratory study in Zambia
Mwale, M.; Nteeni, M.; Mwaba, P.; Chipampe, M.
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BackgroundWhile mammography is commonly used for breast cancer detection, its widespread implementation in resource-constrained nations is challenging. Artificial intelligence-based Thermalytix is a low-cost, portable, radiation-free, automated test for breast cancer detection in women of all ages. Although used in India, the efficacy of Thermalytix has not been tested in an African population. ObjectivesTo assess the agreement and correlation coefficient of Thermalytix output with radiologist-reported mammography, in a Zambian tertiary care population. MethodologyIn October 2023, 169 women were evaluated with both Thermalytix and standard mammography at Maina Soko Military Hospital at Lusaka. Thermalytix uses advanced machine learning algorithms to interpret breast thermal scans and generates a quantitative score indicating the likelihood of malignancy. All women underwent both tests, with results blinded both ways. Subsequently the Spearman correlation coefficient and level of agreement between Thermalytix output and BIRADs scoring from radiologist-interpreted mammography was calculated. Results144 women with complete data were analysed in this report, with median age of 50 years (53.5% postmenopausal, 65.3% asymptomatic). Six women were assessed as mammography test positive and 138 as mammography negative; in these, the correlation between Thermalytix and mammography using Spearman test of rank correlation was 0.9 [very strong], and using the US FDA recommended test of agreement, positive agreement was obtained in 83.3%. ConclusionDemonstrating a very strong correlation and level of agreement with mammography, along with its good sensitivity, specificity and negative predictive value in previous clinical trials, Thermalytix has the potential to be an additional tool in the early detection of breast cancer in Zambia.
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