Demonstration of a longitudinal concentration gradient along scala tympani by sequential sampling of perilymph from the cochlear apex

Abstract

Local applications of drugs to the inner ear are increasingly being used to treat patients' inner ear disorders. Knowledge of the pharmacokinetics of drugs in the inner ear fluids is essential for a scientific basis for such treatments. When auditory function is of primary interest, the drug's kinetics in scala tympani (ST) must be established. Measurement of drug levels in ST is technically difficult because of the known contamination of perilymph samples taken from the basal cochlear turn with cerebrospinal fluid (CSF). Recently, we reported a technique in which perilymph was sampled from the cochlear apex to minimize the influence of CSF contamination (J. Neurosci. Methods, doi: 10.1016/j.jneumeth.2005.10.008 ). This technique has now been extended by taking smaller fluid samples sequentially from the cochlear apex, which can be used to quantify drug gradients along ST. The sampling and analysis methods were evaluated using an ionic marker, trimethylphenylammonium (TMPA), that was applied to the round window membrane. After loading perilymph with TMPA, 10 1-muL samples were taken from the cochlear apex. The TMPA content of the samples was consistent with the first sample containing perilymph from apical regions and the fourth or fifth sample containing perilymph from the basal turn. TMPA concentration decreased in subsequent samples, as they increasingly contained CSF that had passed through ST. Sample concentration curves were interpreted quantitatively by simulation of the experiment with a finite element model and by an automated curve-fitting method by which the apical-basal gradient was estimated. The study demonstrates that sequential apical sampling provides drug gradient data for ST perilymph while avoiding the major distortions of sample composition associated with basal turn sampling. The method can be used for any substance for which a sensitive assay is available and is therefore of high relevance for the development of preclinical and clinical strategies for local drug delivery to the inner ear.

Fig. 1

Schematic of the unwound cochlea before and during fluid sampling from the cochlear apex. Prior to sampling (upper panel), a concentration gradient of drug exists along scala tympani (ST). When the apex is perforated, the fluid efflux collected in a capillary is initially from apical regions (1). The fluid volume lost from the cochlea is replaced by CSF entering the basal turn of ST through the cochlear aqueduct (CA). Subsequent samples (2–4) contain fluid that originated from progressively more basal regions of ST, up to the point where the sample contains a significant amount of CSF. Further samples (not shown) increasingly contain CSF that has “rinsed through” ST.

Fig. 2

Summary of the TMPA concentrations of 10 fluid samples taken sequentially from the cochlear apex. In the left and middle panels, each curve is a different experiment, shown with different symbols. In all curves, the initial sample had low concentration, reflecting its apical origins, increasing to a peak concentration at the fourth or fifth sample, representing fluid from more basal regions. Data are shown for experiments in which TMPA was applied without round window membrane (RWM) manipulation (left panel) and following RWM permeabilization (middle panel), which resulted in higher absolute perilymph concentrations of TMPA. Note that the left and middle panels have different concentration scales. The right panel shows the mean curves (bars indicate SD) for both groups after amplitude normalization.

Fig. 3

Simulation of sampling from the cochlear apex. In each row, the longitudinal gradient of substance along ST (left panel) is compared with the 10 simulated samples obtained for that profile (right panel). Different application conditions were used to produce four different gradients from steep gradient (upper row) to none (lower row).

Fig. 4

Interpretation of apical sample concentrations in one experiment (ASP12) using the finite element simulator. (A) Experimental sample data compared with concentrations derived by simulation. (B) The scala tympani profile that existed just before sampling in the simulation. The basal and apical concentrations of this profile were 1739 and 0.0019 μM, respectively, indicating a basal–apical gradient of 9.4 × 10⁵, which is 5.97 log units. (C) Concentrations of the “volume segments” corresponding to the first four samples prior to the volume movements associated with sampling. The calculated segment concentrations show that the concentration gradient along scala tympani is steeper than the samples suggest. (D) Schematic representation of the volume segments of scala tympani (shown here uncoiled) that comprise the first four samples. The parameters fitted in the simulation were as follows: round window permeability = 14 × 10⁻⁸ m/s; scala tympani clearance half time = 40 min; volume flow = 1 nL/min, apically directed; compartment parallel to scala tympani area = 0.3 mm², accessibility 0.3 re. free diffusion. The volumes in μL for the 10 samples with collection times in seconds shown in parentheses were as follows: 1.06 (18); 1.04 (17); 1.05 (22); 1.04 (21); 1.02 (18); 1.04 (20); 1.06 (24); 1.06 (22); 1.05 (19).

Fig. 5

Concentration profiles along scala tympani (ST) for the eight experiments derived by finite element simulation of each experiment. Left: Concentration profiles shown on a linear scale. Right: The same data, amplitude normalized (setting maximum to 100) and plotted on a logarithmic scale. The basal–apical gradient (in log units) is specified on each curve.

Fig. 6

Analysis of samples using curve fitting. Sample concentrations are plotted based on the location in the cochlea of the sample midpoint. The sample number is shown above each symbol. Basal turn concentrations were corrected for the influence of CSF dilution (open triangles), and a nonlinear function (solid line) was fitted as described in the text. The basal–apical gradient estimated by the fitted curve for this animal was 4.93, which is lower than that estimated by finite-element simulation of the same data (Fig. 4).

Fig. 7

Summary of the basal–apical gradients calculated by different methods. The gradient calculated by the finite-element simulator was a little greater than that derived by curve fitting, although the difference is small relative to the interanimal variation of gradients.