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This study aims to evaluate a thermophysics-based AI approach for detecting premalignant and malignant breast lesions.

Breast cancer screening is heating up: A novel thermophysics-based AI modality for screening subjects with BIRADS 4 or 5 mammograms.

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This study aims to evaluate a thermophysics-based AI approach for detecting premalignant and malignant breast lesions.
Prospective pilot study with 14 patients having BI-RADS 4 or 5 breast lesions.
Ultra-high sensitivity infrared imaging was combined with a physics-informed neural network for analysis.
Tumor presence was predicted and validated against gold standard mammography and histology results.
The AI neural network achieved 100% sensitivity and specificity for detecting premalignant and malignant lesions.
All three cases of invasive ductal carcinoma, three ductal carcinoma in situ, and two atypical ductal hyperplasia were accurately identified.
Histologically benign lesions were correctly not identified as heat sources by the AI system.

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Pilot study shows AI-enhanced infrared imaging can accurately detect breast lesions in high-risk patients, suggesting improved screening methods.

Darwish et al. (2026) studied this question.

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Pilot study shows AI-enhanced infrared imaging can accurately detect breast lesions in high-risk patients, suggesting improved screening methods.