Integrating fluorescent nanomaterials such as CdSe/ZnS quantum dots (QDs) or carbon quantum dots (CQDs) into tissue engineering scaffolds enables real-time, non-invasive monitoring of scaffold degradation and cell infiltration. This approach leverages the photostability and tunable emission properties of these nanomaterials, particularly in the near-infrared II (NIR-II) window (1000–1700 nm), where tissue autofluorescence and scattering are minimized. By embedding these probes within the scaffold matrix, researchers can track structural changes and cellular activity without invasive sampling, providing longitudinal data that correlates with traditional histological analysis.

CdSe/ZnS QDs offer high quantum yields and narrow emission bands, making them suitable for precise signal quantification. When incorporated into polymeric or hydrogel scaffolds, their surface chemistry must be optimized to prevent aggregation and ensure even distribution. For example, carboxyl or amine-functionalized QDs can be conjugated to scaffold polymers like poly(lactic-co-glycolic acid) (PLGA) or collagen via covalent bonding. The NIR-II emission of CdSe/ZnS QDs is achieved through careful shell engineering, such as tuning the ZnS shell thickness to shift the emission beyond 1000 nm. This allows deep-tissue imaging with minimal signal attenuation.

Carbon quantum dots, on the other hand, provide advantages such as lower toxicity and broader biocompatibility. CQDs can be synthesized from natural precursors like citric acid or chitosan, yielding surface functional groups that facilitate integration into scaffolds. Their emission in the NIR-II range is achieved through doping with heteroatoms like nitrogen or sulfur, which modifies the electronic structure. Unlike CdSe/ZnS QDs, CQDs exhibit excitation-dependent emission, requiring optimized excitation wavelengths for NIR-II tracking.

Signal quantification algorithms are critical for translating fluorescence data into meaningful metrics of scaffold degradation and cell infiltration. Time-resolved fluorescence intensity measurements can distinguish between probe release due to degradation and signal quenching from cellular uptake. For CdSe/ZnS QDs, ratiometric analysis using two emission peaks (e.g., 800 nm and 1200 nm) corrects for depth-dependent signal loss. Machine learning algorithms, such as convolutional neural networks, have been applied to deconvolve overlapping signals from multiple probes or autofluorescence. These models are trained on ground-truth data from controlled degradation experiments, where scaffold mass loss and porosity changes are correlated with fluorescence decay rates.

For CQDs, lifetime imaging microscopy (FLIM) provides additional resolution, as their fluorescence lifetime changes with local microenvironmental conditions like pH or enzymatic activity. This allows differentiation between intact scaffold regions and areas undergoing hydrolysis or cell-mediated remodeling. Algorithms incorporating principal component analysis (PCA) can separate these lifetime shifts from background noise, improving the accuracy of degradation tracking.

Correlation with histology validates the fluorescence-based measurements. In studies using PLGA scaffolds loaded with CdSe/ZnS QDs, fluorescence signal decay rates matched mass loss measurements from gravimetric analysis, with Pearson coefficients exceeding 0.9. Similarly, CQD-integrated hydrogels showed linear relationships between signal intensity and cell density counts from DAPI staining. Cross-validation with immunohistochemistry (e.g., collagen staining for ECM deposition) further confirms that fluorescence trends reflect biological processes rather than probe leakage or photobleaching.

The NIR-II window is particularly advantageous for tracking cell infiltration in thick scaffolds or in vivo. In one study, CdSe/ZnS QDs embedded in a 3 mm-thick silk fibroin scaffold allowed visualization of fibroblast migration over 14 days, with signal penetration depths up to 5 mm achieved at 1300 nm emission. CQDs in alginate gels enabled monitoring of macrophage infiltration in murine models, with signal-to-background ratios 3-fold higher than in the NIR-I window.

Challenges remain in standardizing quantification protocols across different scaffold materials and probe types. Batch-to-batch variability in QD synthesis or CQD doping levels can affect signal calibration. Additionally, long-term stability studies are needed to ensure that fluorescence signals remain predictive over weeks or months, especially in dynamic physiological environments.

In summary, CdSe/ZnS QDs and CQDs provide robust tools for non-invasive scaffold monitoring when integrated with advanced signal processing and histological validation. Their NIR-II compatibility, combined with tailored algorithms, offers a powerful framework for understanding scaffold remodeling and cell interactions in real time. Future work should focus on universal calibration standards and multi-modal imaging approaches to further enhance correlation accuracy.