Sunday, November 28 | 10:30 a.m.-11:30 a.m. | SSNMMI01-3 | Room N226
Researchers will discuss in this Sunday session how applying radiomics and machine learning to FDG-PET/MRI can noninvasively assess nodal status and treatment planning for breast cancer patients.
Dr. Valeria Romeo, PhD, from the University of Naples in Italy will present findings from a study her team directed that included 74 patients with 82 total breast cancer lesions and axillary lymph nodes. The patients also underwent simultaneous breast F-18 FDG PET/MRI.
Out of the eight radiomics models the team developed, the one that had radiomics features extracted from dynamic contrast-enhanced images, antibody-drug conjugates, and PET images showed the highest accuracy for predicting lymph node status.
So, how accurate was this method, and what did it show in terms of specificity and sensitivity? Find out more on Sunday.
