Nor should exams be limited by accessibility, Pathak emphasizes. GE HealthCare, she says, is leveraging mobile imaging units and AI-driven triage tools to extend coverage into underserved regions. “Improving accessibility as well as comfort is central to our innovation strategy.” Pathak points to the company’s Senographe Pristina platform, including Pristina Via, designed with patient input to reduce anxiety and physical discomfort. Features like ergonomic design and patient-assisted compression are central to this effort, she says.

“Our goal is to make mammography not just more accurate, but more personalized, so patients feel seen, heard, and cared for,” Pathak says.


Improvements aside, barriers to access persist, particularly among women ages 40 to 49, who are increasingly skipping routine screenings. “We’re seeing an uptick in later-stage cancers being diagnosed,” Murray says. “We’re not finding them as early.” She also notes the rise in metastatic disease, a trend she finds troubling. “Given how far we’ve come, I sometimes look at the data and think, ‘wow, we still have a long way to go.’”

Still, Murray remains optimistic about the future of breast imaging, especially with contrast-enhanced mammography (CEM). “CEM is functional imaging,” she explains. “It improves sensitivity and specificity over traditional mammography, and in some cases, it may even rival breast MRI.” She anticipates broader adoption of CEM, particularly in rural areas with limited access to MRI.

While tomosynthesis was once considered a solution for dense breast tissue, it hasn’t fully replaced the need for MRI or ultrasound. CEM, she says, fills that gap, offering a more accessible and effective alternative for early breast cancer detection.

The future of breast imaging
Early detection certainly remains the goal, but experts Mark Horvath, Pooja Pathak, Christie Devine, and Christine Murray all see the future of breast imaging shifting toward prevention and personalization.

Pathak envisions a future of multimodal imaging—combining mammography, ultrasound, MRI, and molecular diagnostics, all powered by AI to create personalized risk profiles. Devine predicts that decision support tools will integrate genetics, breast density, and prior imaging to refine screening recommendations. “We’ve already seen the use of decision support tools outside of breast imaging, and this trend is set to grow in the field,” she says.

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