Data Harmonization to Address the Non-biological Variances in Radiomic Studies

Taking steps to reduce bias and variation in clinical data is particularly important in multicenter trials. Integrating clinical characteristics acquired from images obtained using different scanners and different methods is essential for this purpose. The goal of such combinations is to strengthen stability and guarantee the reliability of data interpretations. In this chapter, we will focus on learning and exploring the best practices for improving image quality and content for modern biomedical and clinical applications. Harmonization of data is based on a central principle: reducing variability and bias introduced by non-biological variables. These may include things like the current state of the patient as well as the specifications of the acquisition equipment and techniques used. These external factors may have a significant impact on the repeatability and consistency of radiomics features and must be taken into account. In this chapter, we will not only summarize the most common kinds of non-biological differences but also discuss the methods currently in use to bring these differences into alignment. In addition, we will provide predictions about probable future research directions in this dynamic field.