Quo Vadis, Molecular Imaging?

MI probes based on biologicals: format defines and impacts not only pharmacokinetics but also development time, costs, and level of effort for clinical translation. Fab fragments = antigen-binding fragments; scFv = single-chain variable fragment.

Scheme illustrating main sites of accumulation and elimination of diagnostic nanomaterials. This is simplistic view; composition of materials and their interaction with body components may cause different properties in individual cases. Color intensities of human shapes (top row) indicate overall body distribution. (Left) Diagnostic agents smaller than albumin can be renally eliminated and thus usually have short blood half-life and intracorporal persistence. They rapidly overcome biologic barriers, leading to low unspecific accumulation and low background for targeted imaging applications (bottom row). (Middle) Some materials can leave vasculature but are not renally eliminated. They usually show smaller distribution volume but longer body persistence and MPS uptake (liver, spleen, and lymph nodes are shown as an example) and can have long blood half-lives. Diagnostically, these materials can be used for EPR prediction, for MPS staining, and as theranostic drug delivery systems. Antibodies, as considerably small nanosystems (∼12 nm for IgG), also fall into this class. Because of their still-sufficient tissue penetration capabilities, they are frequently used as molecular diagnostic agents, which is reasonable if long intervals between injection and imaging are acceptable in clinical workflow. (Right) Microbubbles can be used as ultrasound contrast agents. Microbubbles remain strictly intravascular and favorably enable vascular visualization and intravascular MI. They are being explored for their capability of locally promoting drug delivery and as carriers of drugs and genes. Gray underlays in bottom row indicate distribution in and penetration of materials into tissue compartments. BV = blood vessel; IS = interstitial space; SPION = superparamagnetic iron oxide nanoparticles; TC = target cell. (Modified clip art from Servier medical art database [https://smart.servier.com/].)

Currently, MI aims mostly at extracting one or a few key biomarkers, whereas radiomics aims to achieve diagnostic precision from integrating multiple features extracted from functional and morphologic imaging data. However, multiple features could be extracted from MI data to enhance its diagnostic accuracy. Integrating imaging features with other diagnostic data (e.g., from physical examinations, electrophysiology, clinical chemistry, and omics) leads to comprehensive diagnostics, where artificial intelligence supports decision making based on learning from large data collections. There is a great need to understand and validate output of artificial intelligence–based decision support systems. Systems biology modeling and generation of virtual disease models will become important. These models will profit from MI of key parameters of pathologic processes and inversely provide indications for developing new MI probes. (Modified clip art from Servier medical art database [https://smart.servier.com/].)