A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening
Abstract In resource-constrained countries like India, mammography-based breast screening is challenging to implement. This state-wide study, funded by the Government of Punjab, evaluated the use of Thermalytix, a low-cost, radiation-free AI tool, for breast cancer screening. Community health worker...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-024-01368-2 |
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| author | Karthik Adapa Ashu Gupta Sandeep Singh Hitinder Kaur Abhinav Trikha Ajoy Sharma Kumar Rahul |
| author_facet | Karthik Adapa Ashu Gupta Sandeep Singh Hitinder Kaur Abhinav Trikha Ajoy Sharma Kumar Rahul |
| author_sort | Karthik Adapa |
| collection | DOAJ |
| description | Abstract In resource-constrained countries like India, mammography-based breast screening is challenging to implement. This state-wide study, funded by the Government of Punjab, evaluated the use of Thermalytix, a low-cost, radiation-free AI tool, for breast cancer screening. Community health workers, trained to raise awareness, mobilized women aged 30 and above for screening. Thermalytix triaged women into five risk categories based on thermal images, with high-risk women recalled for diagnostic imaging. Over 18 months, 15,069 women were screened across 183 locations in Punjab. The median age was 41 years, and 69.9% were asymptomatic. Of 460 women testing positive (recall rate 3.1%), 268 underwent follow-up imaging, and 27 were confirmed with breast cancer, yielding a detection rate of 0.18%. The positive predictive value of biopsy performed was 81.81%, and the median diagnostic interval was 21 days, with therapy initiation within 30 days. The study demonstrates the potential of Thermalytix for effective population-level breast cancer screening in low-resource settings. |
| format | Article |
| id | doaj-art-23ed30fd063b431698a3553939fc3537 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-23ed30fd063b431698a3553939fc35372025-01-05T12:47:20ZengNature Portfolionpj Digital Medicine2398-63522025-01-018111110.1038/s41746-024-01368-2A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screeningKarthik Adapa0Ashu Gupta1Sandeep Singh2Hitinder Kaur3Abhinav Trikha4Ajoy Sharma5Kumar Rahul6Department of Health and Family Welfare, Government of PunjabDepartment of Health and Family Welfare, Government of PunjabDepartment of Health and Family Welfare, Government of PunjabDepartment of Health and Family Welfare, Government of PunjabDepartment of Health and Family Welfare, Government of PunjabDepartment of Health and Family Welfare, Government of PunjabDepartment of Health and Family Welfare, Government of PunjabAbstract In resource-constrained countries like India, mammography-based breast screening is challenging to implement. This state-wide study, funded by the Government of Punjab, evaluated the use of Thermalytix, a low-cost, radiation-free AI tool, for breast cancer screening. Community health workers, trained to raise awareness, mobilized women aged 30 and above for screening. Thermalytix triaged women into five risk categories based on thermal images, with high-risk women recalled for diagnostic imaging. Over 18 months, 15,069 women were screened across 183 locations in Punjab. The median age was 41 years, and 69.9% were asymptomatic. Of 460 women testing positive (recall rate 3.1%), 268 underwent follow-up imaging, and 27 were confirmed with breast cancer, yielding a detection rate of 0.18%. The positive predictive value of biopsy performed was 81.81%, and the median diagnostic interval was 21 days, with therapy initiation within 30 days. The study demonstrates the potential of Thermalytix for effective population-level breast cancer screening in low-resource settings.https://doi.org/10.1038/s41746-024-01368-2 |
| spellingShingle | Karthik Adapa Ashu Gupta Sandeep Singh Hitinder Kaur Abhinav Trikha Ajoy Sharma Kumar Rahul A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening npj Digital Medicine |
| title | A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening |
| title_full | A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening |
| title_fullStr | A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening |
| title_full_unstemmed | A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening |
| title_short | A real world evaluation of an innovative artificial intelligence tool for population-level breast cancer screening |
| title_sort | real world evaluation of an innovative artificial intelligence tool for population level breast cancer screening |
| url | https://doi.org/10.1038/s41746-024-01368-2 |
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