Quantitative Imaging and Imaging Biomarkers: The Search for Generalizability in Radiology.

T development of medical imaging for the accurate diagnosis and treatment of a broad range of disease entities is a continued overarching vision in radiology with ever moving targets. As such, novel and further refined imaging modalities and techniques have greatly entered and enhanced the clinical arena in many settings. However, most of a radiologist’s work has been focused on visually assessing images for deviations from “normal,” which is encrypted after many years of clinical training in mind. While these approaches have proven beneficial for many decades, the complexity of modern medicine, in which also subtle differences in morphologic and functional differences over time play a central role, clearly requires to extract quantitative, reproducible, and generalizable information from images in an effort to further improve diagnostic and therapeutic decision making.1 Often, these parameters are termed imaging biomarkers, adequately highlighting the biological role of imaging information. In the current issue of the journal, we are delighted to feature 6 important contributions to the field, both from the cardiovascular and pulmonary domains. In a comprehensive overview, Muscogiuri et al2 review the role of T1 mapping of the myocardium, including a perspective on its clinical value. One of the most obvious imaging biomarkers—the left ventricular size—in the context of nongated computed tomography (CT) is being reviewed by Torres et al.3 From a technology assessment perspective, Dual-Energy CT has emerged as a novel technique, particularly suited to quantify iodine uptake in tissues. Nakahara et al4 studied the accuracy of Dual-Energy–based iodine maps of the myocardium in comparison with SPECT. Similarly, CT-based derivation of fractional flow reserve of the coronary arteries holds promise to overcome the purely morphologic information in coronary CT, and its status quo is being reviewed by Benton et al.5 In a very interesting analysis, Mortani et al6 investigated the prognostic value of CT-based biomarkers of lung transplants for functional capacity. Finally, quantitative pulmonary parameters in IPF and NSIP also portray survival-relevant information, which is elegantly shown in a study by De Giacomi et al.7 These are all exciting fields of quantitative imaging research, and the evolution of imaging biomarkers over the last couple of years has been impressive; however, there are also challenges along the way, which hamper its broader clinical diffusion today. First, it is obvious that standardization as part of the image acquisition process is critical. The plethora of vendors and their specific and partially market-oriented developments, the traditional way that radiology exams are ordered, planned, and performed locally, and the clear need for individualized diagnostic planning, induces a significant barrier of heterogeneity. Second, implementation of postprocessing software solutions in established clinical pathways is complex but is essential to quantitative imaging. Workflow-oriented solutions and pipelines will be critical to allow for a broad adoption in clinical routine. Third, similar to laboratory medicine, generalizability in quantitative imaging is key. As long as obtained parameters, such as T1 values of the myocardium, are institution-specific or vendor-specific and not comparable against a standard reference, a broader applicability by clinicians will not be accomplished. All of this requires a multidisciplinary, vendor-inclusive effort, presumably mediated by the professional societies, such as QIBA or EIBALL. In fact, such an effort may be worthwhile and urgent, as this will set the baseline for more novel developments, such as the implementation of deep-learning and artificial intelligence in practice, which will predictably impact on the way we practice radiology substantially.