An Indian origin scientist along with a team has developed a computer-based model that would help in early breast cancer diagnosis and avoid unnecessary biopsies.
Dr Jagpreet Chhatwal, Dr Elizabeth S. Burnside and Dr Oguzhan Alagoz from University Of Wisconsin School of Medicine, Madison, WI have developed a new technique that would help discriminating benign and malignant breast lesions.
"The computer based model was designed to help the radiologist calculate breast cancer risk based on abnormality descriptors like mass shape; mass margins; mass density; mass size; calcification shape and distribution," said Burnside and Chhatwal, lead authors to the study.
"When the radiologist combined his/her assessment with the computer model the radiologist was able to detect 41 more cancers than when they didn't use the model," they added.
The new computer model is designed to aid a radiologist in breast cancer risk prediction to improve accuracy and reduce variability.
"Our model has the potential to avoid delay in breast cancer diagnosis and reduce the number of unnecessary biopsies, which would benefit many patients," said the authors.
"It may also encourage patients to get more actively involved in the decision-making process surrounding their breast health.
"Though much work remains to be done to validate our system for clinical care, it represents a promising direction that has the potential to substantially improve breast cancer diagnosis," they added.
This study appears in the April issue of the American Journal of Roentgenology.