Fig 1.
Experimental setup of a transport assay for measurements of drug concentration distributions in tissue.
(A) A custom-made tissue chamber was placed on a heated motorized stage in order to maintain the diffusion experiment at 37°C. Measurements were acquired using a water-immersion objective. (B) A schematic cross-sectional view of the sample chamber, showing the components of the chamber.
Fig 2.
Effects of scattering and spherical aberration on axial resolution and sampling depth.
(A) Relationship between the confocal RS true sampling depth, z, and the nominal depth or the stage position, zstage. (B) Relationship between the axial resolution (full-width at half-maximum, FWHM) of the confocal RS subsystem and z. The water immersion objective provided a significant improvement in resolution compared to the dry objective lens [24] for measuring biological tissue. Least-squares fits (solid lines) reveal that both relationships are approximately linear over this range. The dashed lines represent 95% confidence intervals for the fits.
Fig 3.
Representative least-squares fit of a Raman spectrum of tenofovir -gel treated tissue from a typical experiment.
The tissue was incubated under tenofovir gel in the transport chamber. The spectrum was decomposed by ordinary least squares fitting with basis spectra of tenofovir, gel, and tissue in order to yield the underlying spectral contribution of each component.
Fig 4.
Schematic of drug transport model for tissue transport assay.
DEP, DST, ΦEP/G and ΦST/EP were derived from fitting experimental data with the model.
Fig 5.
A calibration curve of tenofovir in homogenized tissue for determination of absolute tenofovir concentration.
Each data point represents mean ± SE of 5 measurements, except for the control (0%) and 0.45% data points, which represent means of 4 and 6 measurements, respectively (complete data are available in the S1 Table). Error bars are invisible when smaller than the symbols. We observed a strong linear dilution response (R2 ≥ 0.99, P <0.0001) for concentrations of tenofovir in the tissue. The root mean squared error of prediction (RMSEP) represents the limit of detection (i.e., the prediction accuracy of tenofovir concentration in tissue).
Fig 6.
Co-registered confocal RS and OCT measurements of a tenofovir gel—Treated tissue specimen in a diffusion chamber.
(A) Spectra are normalized by the mean intensity across all wavenumbers. Tenofovir peak intensities (I) decreased with depth into the tissue, while the tissue band intensities (e.g., at 1440–1450 cm-1 –representing CH2 band of lipid and protein [40]) remained relatively constant. The spectral changes due to varying amount of collagen content between epithelium and stroma appeared in the amide-3 band region (1200–1400 cm-1, II). Spectra are offset for clarity of presentation. (B) A well-defined epithelial layer was observed, supported by the stroma. The gel was transparent and did not exhibit scattering; thus it appeared dark in the OCT image. The Raman spectral changes observed at a depth of approximately 100 microns are consistent with the location of the basement membrane identified by OCT.
Fig 7.
A representative spatiotemporal concentration profile of tenofovir in tissue.
The thicknesses of the epithelium (hEP), the stroma (hST), and the gel overlayer (hG) were 104 μm, 3387 μm, and 1078 μm, respectively. (A) Tenofovir concentration distributions obtained from multiple depth scans. Each data point represents a measurement at a different time and depth. (B) Tenofovir concentration distributions fitted with a drug diffusion model to derive fundamental transport parameters. Best fit parameters were: DEP = 5.04 x 10−8 cm2/s, DST = 4.14 x 10−7 cm2/s, ΦEP/G = 0.57, and ΦST/EP = 1.01. Data are displayed in two different viewing angles with the best-fit surface that describes tenofovir concentration distributions in the tissue.
Table 1.
Transport parameters derived from six independent tissue diffusion experiments—Each experiment used a different tissue sample (n = 6).