Dataset for optical coherence tomography for label-free cell viability measurements in 3D tissue engineering scaffolds

Description

In the field of tissue engineering, 3D scaffolds and cells are often combined to yield constructs that are used as therapeutics to repair or restore tissue function in patients. Viable cells are often required to achieve the intended mechanism of action for the therapy, where the live cells may build new tissue or may release factors that induce tissue regeneration. Thus, there is a need to reliably measure cell viability in 3D scaffolds as a quality attribute of a tissue-engineered medical product. Here, we developed a noninvasive, label-free, 3D optical coherence tomography (OCT) method to rapidly (2.5 min) image large sample volumes (1 mm) to assess cell viability and distribution within scaffolds. OCT imaging was assessed using a model scaffold-cell system consisting of a polysaccharide-based hydrogel seeded with human Jurkat cells. Four test systems were used: hydrogel seeded with live cells, hydrogel seeded with heat-shocked or fixed dead cells and hydrogel without any cells. Time series OCT images demonstrated changes in the time-dependent speckle patterns due to refractive index (RI) variations within live cells that were not observed for pure hydrogel samples or hydrogels with dead cells. The changes in speckle patterns were used to generate live-cell contrast by image subtraction. In this way, objects with large changes in RI were binned as live cells. Using this approach, on average, OCT imaging measurements counted 326 ± 52 live cells per 0.288 mm for hydrogels that were seeded with 288 live cells (as determined by the acridine orange-propidium iodide cell counting method prior to seeding cells in gels). Considering the substantial uncertainties in fabricating the scaffold-cell constructs, such as the error from pipetting and counting cells, a 13% difference in the live-cell count is reasonable. Additionally, the 3D distribution of live cells was mapped within a hydrogel scaffold to assess the uniformity of their distribution across the volume. Our results demonstrate a real-time, noninvasive method to rapidly assess the spatial distribution of live cells within a 3D scaffold that could be useful for assessing tissue-engineered medical products.

Resources

Name Format Description Link
57 Figure 1. Human Jurkat cells. Brightfield images of live, dead and dead (heat-shocked) Jurkat cells. Cell viability was determined via acridine orange and propidium iodide (AOPI) staining. https://data.nist.gov/od/ds/mds2-2596/Figure1.zip
48 Figure 2. Experimental setup for OCT imaging. (A) Diagram of assay system where Jurkat cells were encapsulated in polysaccharide hydrogels (PSH) for measurements of cell viability. The diagram is drawn roughly to scale. (B) OCT imaging of samples inside an 8-well strip; (C) OCT brightfield camera image of the Live-Gel sample, where the red square encloses the observation area; (D) PSH samples in an 8-well strip, the dashed black line overlays the concave meniscus; (E) 3D volumetric OCT image (1.00 mm × 1.00 mm × 1.05 mm) of the Live-Gel sample outlined in red in panel (C). https://data.nist.gov/od/ds/mds2-2596/Figure2.tif
53 Figure 3. ATP concentration assesses cell viability for each treatment. ATP cell viability assay showed that the ATP concentration does not drop when the samples are held at ambient conditions (80 min outside the incubator at ambient conditions, 23 ºC). https://data.nist.gov/od/ds/mds2-2596/Figure3.xlsx
57 Figure 4. Dynamic speckle. OCT xz cross-sectional images of Gel-Only, Dead-Gel-Fixed, Dead-Gel-Heat and Live-Gel samples. The total intensity of four-pixel regions (2 pixels x 2 pixels) in the center of the objects was plotted over time. The images were captured every 5 sec for 3 min. Cropped regions of two Live-Gel OCT images at ti = 0 and tf = 2.5 min later resulted in the difference image that shows that the speckle pattern differed in ti and tf images. https://data.nist.gov/od/ds/mds2-2596/Figure4.zip
53 Figure 6. Live-cell object counts in four different treatments. The total number of live cells counted in Gel-Only, Dead-Gel-Fixed, Dead-Gel-Heat and Live-Gel samples in V=0.288 mm3 volume. https://data.nist.gov/od/ds/mds2-2596/Figure6.xlsx
53 Figure 7. Three-dimensional spatial distribution of the counted objects. Distribution of live-cell object centroids found in Gel-Only, Dead-Gel-Fixed, Dead-Gel-Heat and Live-Gel samples (V = 0.288 mm3) in experiment 5. The top of the hydrogel was at the depth of 0?mm and depths greater than 0 mm are within the hydrogel. https://data.nist.gov/od/ds/mds2-2596/Figure7.xlsx
53 Figure 8. Object density as a function of depth (z) in a hydrogel for four different treatments. Live-cell object count and position within a hydrogel in Gel-Only, Dead-Gel-Fixed, Dead-Gel-Heat, and Live-Gel samples (experiment 5). The mean counts were calculated for corresponding four replicates for four different treatments. https://data.nist.gov/od/ds/mds2-2596/Figure8.xlsx
48 Figure 5. Raw OCT image volumes are processed for 3D object counting in Fiji. The representative frame of Live-Gel image volume is shown here. Raw volume (A) is cropped at the top and bottom to eliminate visibly out-of-focus regions. The gaussian blurring of cropped volume (B) creates a ?background? image of the hydrogel (C). Subtracting the background from the cropped volume results in (D), with the diminished intensity of the nebulous structures relative to the cells. The morphological opening operation (see Table 1, line b) preferentially highlights small objects in (E), which is then thresholded to set all but the highest intensity pixels to zero in (F). Scale bars, 100 µm. https://data.nist.gov/od/ds/mds2-2596/Figure5.tif

Tags

  • label-free-imaging
  • non-invasive-imaging
  • cell-viability
  • 3d-imaging
  • optical-coherence-tomography
  • tissue-engineered-scaffolds

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