Martin Vallières, PhD
Postdoctoral Fellow,
Medical Physics Unit, McGill University,
Cedar Cancer Centre, Montréal Canada

ABSTRACT:

It is now recognized that intratumoral heterogeneity is associated with more aggressive tumor phenotypes leading to poor patient outcomes. Medical imaging plays a central role in related investigations, as radiological images are routinely acquired during cancer management. Nowadays, the rise of computational power allows for the exploitation of a large number of quantitative features and has led to a new incarnation of computer-aided diagnosis: “radiomics,” which refers to the characterization of tumor phenotypes via the extraction of high dimensional mineable data – for example, morphological, intensity-based, and textural features – from medical images and whose subsequent analysis aims at supporting clinical decision making.

Better standardization, transparency and sharing practices are however required in the radiomics community in order to improve the quality and reproducibility of published studies and to achieve faster clinical translation. In this talk, emphasis will be put on the presentation of the standardized radiomics workflow defined by the Image Biomarker Standardisation Initiative (IBSI), a group of more than 64 researchers from 22 institutions in 8 countries. Since 2016, the IBSI has put efforts into standardizing both the computation of radiomics features and the image processing steps required before feature extraction. The workflow for computing radiomics features is in fact complex and involves many steps such as image interpolation, re-segmentation and discretization. Overall, the standardized workflow of the IBSI along with consensual benchmark values could serve as a calibration tool for radiomics investigations. This talk will thus go deep into the specifics of radiomics methods (applied to PET, CT and MR imaging) in order to provide attendees with the necessary knowledge for benchmarking their own software according to IBSI standards.