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Advances in medical imaging has seen the incorporation of various new modalities and sequences into the clinical routine; becoming invaluable tools in patient management. Exploring further, beyond what the eye sees, algorithms can be applied to medical images that can measure informative metrics from tumour volumes and suspicious masses.

Quantitative imaging is an ever-expanding and evolving field based on the extraction of quantifiable features from medical images to be applied in predictive modelling. Quantitative imaging provides clinically relevant metrics that inform on patient diagnosis and prognosis, monitor disease progression and treatment response, and determine the best choice of therapy. Due to the high volume of data that can be extracted from medical images, methods are currently being developed to process and analyse this data so that they may be optimally incorporated into patient care.

The forefront of research into quantitative imaging aims to identify robust imaging features that are accurate, precise, and clinically valid. These features can be incorporated into the clinical workflow, improving understanding in the underlying physiological processes of imaged disease. Utilizing as much information from medical images as possible opens the pathway for researchers to discover new and efficient technologies that can predict important changes in a patient’s disease status faster and with greater accuracy.