WEDNESDAY, Nov. 9 (HealthDay News) -- A new computer model analyzes microscopic breast cancer images and predicts patient survival better than the pathologists who do the job now, new research suggests.
The computer program "provides information above and beyond what the physician provides, using the same data," said Daphne Koller, a professor of computer science at Stanford University and senior author of the study. The computer model is called Computational Pathologist, or C-Path.
Although the technique needs much more study, it may someday supplement analysis of breast cancer by pathologists, who use a process that has remained largely unchanged for 80 years, said Koller.
With the traditional method, pathologists examine a tumor visually under a microscope and score it according to an established scale. The scores help doctors figure out the type and diversity of the cancer. From that information, they calculate the outlook and course of treatment.
The pathologists' determination relies on three factors: what percent of the tumor is made up of tube-like cells; the diversity of the nuclei in the outer cells; and how often those cells divide.
But the system is subjective, said the study authors, whose computer model found that additional factors may influence survival. The study is published Nov. 9 in Science Translational Medicine.
Using the C-Path image analysis program, Koller's team trained the computer to analyze biopsied breast cancer tissue and to determine the cancer features that matter most and least in predicting survival.
The computer model looked at more than 6,000 cellular factors and found that characteristics of the cells surrounding the cancer -- the cancer's environment -- are also important in predicting survival.
"We found 11 [factors] ultimately that showed the most robust association with survival," said Dr. And
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