Dynamic In Vivo Imaging
Dynamic In Vivo Imaging - Related Videos
02:42
In Vivo Two-Photon Imaging of Microglial Dynamics in the Mouse Hippocampus
0 Views •
2025
Source: Kamei, R., et. al., In Vivo Chronic Two-Photon Imaging of Microglia in the Mouse Hippocampus. J. Vis. Exp. (2022)The video demonstrates the setup and imaging process for in vivo two-photon microscopy of microglial dynamics in the hippocampal CA1 (Cornu ammonis 1) and dentate gyrus, ensuring optimal optical alignment and structural integrity assessment.
08:15
Tracking Dynamics of Muscle Engraftment in Small Animals by In Vivo Fluorescent Imaging
0 Views •
Cited by 4 •
2009
We describe an in vivo fluorescence imaging protocol to monitor muscle regeneration by GFP-labeled myoblasts after transplantation into skeletal muscles of both healthy and dystrophic mice. This protocol can be adapted to study muscle regeneration by transplantation of other types of cells and in other muscular conditions as well.
11:02
In vivo Bioluminescence Imaging of Tumor Hypoxia Dynamics of Breast Cancer Brain Metastasis in a Mouse Model
0 Views •
Cited by 16 •
2011
Bioluminescence imaging of hypoxia inducible factor-1α activity is applied to monitor intracranial tumor hypoxia development in a breast cancer brain metastasis mouse model.
12:09
A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics
0 Views •
Cited by 14 •
2013
We describe a novel in vivo imaging technique that couples fluorescent chimeric mice with intracranial windows and high-resolution 2-photon microscopy. This imaging platform aids studies of dynamic changes in brain tissue and microvasculature, at a single-cell level, following pathological insults and is adaptable to assess intracranial drug delivery and distribution.
12:48
In Vivo Dynamics of Retinal Microglial Activation During Neurodegeneration: Confocal Ophthalmoscopic Imaging and Cell Morphometry in Mouse Glaucoma
0 Views •
Cited by 29 •
2015
Microglia activation and microgliosis are key responses to chronic neurodegeneration. Here, we present methods for in vivo, long-term visualization of retinal CX3CR1-GFP+ microglial cells by confocal ophthalmoscopy, and for threshold and morphometric analyses to identify and quantify their activation. We monitor microglial changes during early stages of age-related glaucoma.
FAQs
The instrument records signals that reveal biological structures or activity, while the choice between endogenous signals and introduced contrast agents determines what can be visualized. Repeated measurements then show changes such as cell movement, tissue deformation, blood flow, or biomaterial integration. This combination links measurable biological events to their location and progression within living tissue.
Endogenous signals allow imaging to rely on properties already present in the organism, whereas introduced contrast agents provide an additional means of making selected structures or processes visible. Their use expands the types of biological information that can be captured. In bioengineering studies, this distinction helps align the imaging strategy with the tissue, implant, or therapeutic cell being evaluated.
A single image shows spatial organization at one point, but time-resolved imaging reveals how that organization changes. Tracking successive observations can distinguish movement from a static position, deformation from a fixed shape, and integration from simple proximity. These temporal patterns support quantitative modeling and provide a more realistic assessment of biological responses to engineered materials or interventions.
Because measurements can be collected while tissue remains in the organism, the approach preserves observation of ongoing biological behavior rather than limiting analysis to an endpoint. Researchers can follow processes such as implant integration or disease-related change over time. This continuity helps connect an intervention with its evolving outcome and reduces reliance on a single final tissue state.
A study first identifies the structure or process to monitor, then pairs an appropriate imaging instrument with either an endogenous signal or an introduced contrast agent. Researchers acquire observations over time and examine spatial changes, such as movement, deformation, flow, or integration. The resulting measurements can then support quantitative analysis, modeling, and evaluation of the intervention.
Researchers use it when performance depends on changes that unfold within living tissue. For engineered tissues, imaging can follow structural or functional behavior; for implants, it can monitor integration and tissue response. Repeated observations provide evidence about how the construct or device behaves over time, helping researchers assess outcomes more directly than a single endpoint measurement.
The approach can track therapeutic cells and reveal how biological systems respond to an intervention over time. Depending on the measured signal, observations may include cell movement, tissue deformation, blood flow, or biomaterial integration. These data help relate spatial behavior to treatment outcomes, improve experimental design, and support models of disease progression or therapeutic response.