In 2025, an estimated 316,950 U.S. women will be diagnosed with invasive breast cancer, with a growing number under the age of 40. All told: one in eight American women will face breast cancer in her lifetime.

Sobering statistics, yes. But there's a more hopeful story unfolding at the same time. Survival rates have surged 40% since the '90s — a testament to massive strides made in early detection and treatment. As patient volumes rise and workforce shortages persist, next-generation mammography technology and an emphasis on personalized care are changing what it means to face a breast cancer diagnosis.

“Provider priorities have expanded beyond cancer detection to address a broader range of patient needs,” said Mark Horvath, president of breast and skeletal health solutions at Hologic. “We’re glad to see that breast density education is becoming a more common conversation."
Growing awareness around breast density is part of the broader emphasis on assessing each patient based on their individual needs, including the adoption of diagnostic tools such as contrast-enhanced mammography.

“Providers are increasingly focused on delivering personalized, efficient care,” said Pooja Pathak, vice president and general manager of mammography at GE HealthCare, “despite staffing shortages, which continue to add complexity.”

These shortages are also accelerating the integration of one of the most transformative innovations in mammography: artificial intelligence.

AI as the new copilot
Perhaps in no other area of radiology has AI made the kind of strides it has in breast imaging. It is the central force reshaping breast imaging workflows; prioritizing cases, automating acquisition, and enhancing interpretation. For providers facing overwhelming caseloads and burnout, this evolution is seen as a game-changer.

“The workforce crisis in radiology is real and urgent,” says Horvath, underscoring the mounting supply-demand imbalance in healthcare facilities. “AI can play a key role in addressing staffing constraints."

Pathak likens AI to a co-pilot, helping to reduce clinician burnout while minimizing the risk of missed diagnoses. GE HealthCare, she explains, is incorporating AI into its mammography systems to streamline interpretation, boosting both sensitivity and specificity. “This enhances diagnostic accuracy and enables radiologists and technologists to focus on higher-priority tasks.”

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