Abhinav K. Jha, PhD, assistant professor of radiology and biomedical engineering at Washington University in St. Louis, aims to develop a new framework to evaluate quantitative imaging (QI) methods without a gold standard thanks to a grant from the National Institutes of Health.
According to Jha, QI offers exciting new possibilities in improving disease diagnosis and therapy; however, to clinically evaluate the reliability of QI measurement methods, a gold standard is needed — a process that can be time-consuming, expensive and unreliable.
But with the four-year, $1.83 million NIH grant, Jha, his collaborators and members of the Computational Medical Imaging Lab will measure the efficacy of this no-gold-standard evaluation tool in evaluating different tumor segmentation methods. Specifically, they will measure the volumetric features from a type of PET scan used to detect metabolically active malignant lesions in patients with stage 3 non-small cell lung cancer.
Read more from the McKelvey School of Engineering.