Lunit AI software proves early breast cancer detection, reduced workload for radiologists

Lunit said it published a study showing that using Lunit Insight MMG, its AI image analysis solution for mammography, can increase the likelihood of early breast cancer diagnosis and significantly reduce the workload of physicians.

The study, conducted in collaboration with researchers from various universities in Turkey, including Acibadem Mehmet Ali Aydinlar University, Marmara University, Namik Kemal University, and Istanbul University, analyzed over 22,621 mammograms from 8,825 women taken from 2009 to 2019.

Utilizing Lunit INSIGHT MMG, the research aimed to assess its proficiency in early cancer detection within a breast cancer screening program.

As a result, the study found that when AI was used as a triage tool in the breast cancer screening workflow, it reduced physician workload by about 69.5 percent while improving triage accuracy by about 30.5 percent.

The study further revealed that the Lunit INSIGHT MMG identified 51.72 percent of interval cancers and 50 percent of cancers missed by traditional screening.

Additionally, the study illustrated that using Lunit INSIGHT MMG as a second reader could expedite the diagnosis by an average of nearly 30 months compared to traditional screening methods.

"This study not only reaffirms Lunit INSIGHT MMG's efficacy in detecting breast cancer early but also illuminates its impact on operational efficiency and economic value within healthcare systems," Lunit CEO Suh Beom-suk said. "For years, most of the conversation around AI in medical diagnostics has centered on its medical efficacy."

However, this research showcases how AI can streamline workflows, reduce the radiological burden, and potentially offer significant cost and time savings, Suh added.

Suh stressed that the company plans to harness these dual benefits of AI to enhance medical outcomes while also driving economic efficiency.

The study results were published in European Radiology.