Dec. 9, 2021—Roche announced the launch of three research use only automated digital pathology algorithms, uPath Ki-67 (30-9), uPath ER (SP1), and uPath PR (1E2) image analysis for breast cancer.
uPath Ki-67 (30-9) image analysis, uPath ER (SP1) image analysis, and uPath PR (1E2) image analysis for breast cancer use pathologist-trained deep learning algorithms to enable quick calculation of Ki-67, ER, and PR tumor cell nuclei positivity. This includes a whole slide analysis workflow with automated pre-computing of the slide image prior to pathologist assessment and a clear visual overlay highlighting tumor cells with and without nuclear staining.
“Roche is committed to the expansion of digital pathology solutions to address unmet medical needs and breast cancer diagnostics is a key opportunity area. Innovations like image analysis algorithms have the potential to impact patient care by increasing the information available to pathologists and enhancing diagnostic confidence,” Jill German, head of Roche Diagnostics Pathology Customer Area, said in a press statement.
The three image analysis algorithms are intended for use with the company’s high medical value assays and slides stained on a BenchMark Ultra using UltraView DAB detection kit and are ready to use and integrated within Roche’s uPath software and Navify digital pathology, the cloud version of uPath.