Breath Test to Enable Early Detection of Breast Cancer

Mammograms often fail to detect breast cancer in women with dense breast tissue, missing up to 60% of cases due to reduced image clarity. Breath analytics has the potential to allow for timely detection of disease which may benefit healthcare providers in identifying health issues early, which will lead to more efficient use of healthcare resources, and more importantly, saving lives. Now, a breath-based diagnostic test aims to improve early breast cancer detection through a simple, non-invasive breath sample.

The novel technology developed by Breathe BioMedical (Moncton, NB, Canada) captures alveolar breath — the air exhaled from the deepest part of the lungs — using sorbent tubes that follow industry-standard collection methods. These samples are then analyzed using a proprietary high-sensitivity spectrometer that detects compounds at parts-per-trillion levels. The collected data is processed using advanced machine learning algorithms to identify biomarker patterns specific to breast cancer. The first large multi-center observational collection protocol study is now assessing whether unique breath signatures can reliably distinguish between women with and without breast cancer, particularly in those with dense breast tissue who are at higher diagnostic risk.

Researchers will compare the breath profiles of women with dense breasts with breast cancer and those without breast cancer, with the goal of identifying disease-specific patterns that can be leveraged to facilitate breast cancer detection. The U.S. screening population includes around 70 million women, and nearly half have dense breast tissue, where mammography’s sensitivity can drop to 40%. By adding breath-based screening, the trial aims to offer a safe, cost-effective adjunct that complements traditional methods. Data collected in this trial will also be used to further refine Breathe BioMedical’s AI models for broader diagnostic use.

“It is well understood that mammography alone is insufficient in detecting breast cancer for women with dense breast tissue, creating the need for accurate, and cost-effective adjunctive detection tools,” said Bill Dawes, CEO of Breathe BioMedical. “This data collection initiative will expand our existing data inventory, allowing us to evaluate our machine learning models across a broader and more diverse population. It also provides an opportunity to further refine these models to enhance their predictive accuracy.”

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