**1. Introduction**

A significant portion of recent advancements in the field of tissue engineering (TE) has focused on design, developing, and characterization of new biomaterials that can be used as tissue mimics to model a variety of diseases in vitro, or as implants to repair or regenerate damaged tissues in vivo [1–3]. Further, the advent of new automated additive manufacturing techniques, such as 3D printing and bioprinting, together with computer-aided design (CAD) modeling, have allowed for higher throughput biofabrication of 3D scaffolding systems with increasing structural and functional complexities to be used in patient-specific TE and precision medicine applications [4–8]. Thus, it is vital to design and utilize effective imaging and tracking methods to closely monitor the scaffolds following implantation in the patient's body [9,10]. These techniques should enable noninvasive, real-time examination of properties including the graft stability and position, biomaterial-tissue interactions (e.g., biocompatibility, degradation, and integration with host tissue), blood perfusion (angiogenesis), and function (e.g., contractile function of a cardiac patch). To achieve this goal, imaging techniques with minimal invasiveness as well high penetration depth and high resolution are required to provide a clear contrast between the embedded biological materials and the surrounding tissue structure, thus generating a complete picture covering morphological, physiological, and molecular processes [11].

New advancements in medical imaging have been made to address different challenges in the TE field, ranging from the design to production processes of tissues and organs, as well as clinical implantation and implementation (Figure 1) [10,12]. These imaging systems often follow a common process of exciting the targeted samples with an energy source like electromagnetic radiation, light, or sound, or a combination of those sources, to generate a response in the form of emitted, transmitted or reflected signal which can then be captured through different detector designs for analysis [10]. Furthermore, specific techniques also require contrast agents or sample labeling methods to enhance the signal-to-noise ratio [13]. As a result, different methods would have distinct advantages and disadvantages with respect to the penetration depth, image temporal and spatial resolution, as well as the effect of the exciting source and contrast/labeling agen<sup>t</sup> on the biological target(s) (Table 1). Thus, it is important that the techniques are selected carefully and tailored to fulfill the specific application requirements.

**Figure 1.** Schematic illustration for the role of imaging in tissue engineering (TE) applications at different levels: scaffold design using computer-aided design (CAD), cellular scaffolds in in vitro applications, preclinical application through implantation in animal models, and clinical application in humans.

In this review, we detail the different medical imaging techniques used in TE applications. These methods include: computed tomography (CT), magnetic resonance imaging (MRI), magnetic particle imaging (MPI), ultrasound, photoacoustic imaging, different optical methods (fluorescence spectroscopy, bioluminescence, and optical coherence tomography), and multimodal imaging (Table 1). These methods have been widely applied in the different areas of TE for investigating the morphological structures of the scaffold structures as well as studying the viability of the different cellular constructs [11]. The Main focus will be on delineating how the general principle of operation and recent advancements in the imaging methods can aid the researchers in the field to select the most effective imaging methods for their in vivo studies.


**Table 1.** List of non-invasive imaging methods, their resolution and depth, costs, external material usage, information type as well as applications in TE ranging from imaging scaffolds (with or without cells), and preclinical and clinical applications.
