Optimization of pharmacological interventions in the guinea pig animal model-a new approach to calculate the perilymph volume of the scala tympani

Abstract

Objective: The guinea pig serves as a well-established animal model for inner ear research, offering valuable insights into the anatomy, physiology, and therapeutic interventions of the auditory system. However, the heterogeneity of results observed in both in-vivo experiments and clinical studies poses challenges in understanding and optimizing pharmacotherapy outcomes. This heterogeneity may be due to individual differences in the size of the guinea pig cochlea and thus in the volume of the scala tympani (ST), which can lead to different drug concentrations in the ST, a fact that has been largely overlooked thus far. To address this issue, we aimed to develop an approach for calculating the individual volume of perilymph within the ST before and after cochlear implant insertion.

Method: In this study, high-resolution μCT images of a total of n = 42 guinea pig temporal bones were used to determine the volume of the ST. We compared fresh, frozen, and fixed tissues from both colored and albino strains to evaluate the potential influence of tissue condition and strain on the results.

Results: Our findings demonstrate a variability in mean ST volume with a relative standard deviation (RSD) of 14.7%, comparable to studies conducted with humans (range RSD: 5 to 20%). This indicates that the guinea pig cochlea exhibits similar variability to that of the human cochlea. Consequently, it is crucial to consider this variability when designing and conducting studies utilizing the guinea pig as an animal model. Furthermore, we successfully developed a tool capable of estimating ST volume without the need for manual segmentation, employing two geometric parameters, basal diameter (A) and width (B) of the cochlea, corresponding to the cochlear footprint. The tool is available for free download and use on our website.

Conclusion: This novel approach provides researchers with a valuable tool to calculate individual ST volume in guinea pigs, enabling more precise dosing strategies and optimization of drug concentrations for pharmacotherapy studies. Moreover, our study underscores the importance of acknowledging and accounting for inter-individual variability in animal models to enhance the translational relevance and applicability of research outcomes in the field of inner ear investigations.

Keywords: cochlear implantation; cochlear modeling; drug delivery; electrode coating; individualized implantation; pharmacokinetics.

Figure 1

Images of the segmentation of a fresh (A) and a frozen (B) guinea pig cochlea using COMET (Lexow et al., 2016, 2018). The red bars represent the midmodiolar axis, yellow points indicate the shape of the ST. In (A), the arrow points on the lateral wall tissue which can be well distinguished from the ST. Images (C) and (D) are from scans performed in vivo directly after cochlear implantation. (C) Segmentation of lateral wall and electrode array in 3D slicer. (D) Corresponding measurement of electrode insertion depth (EID) and insertion angle (IA) in a projected view. The image includes a sketch of the electrode array dimensions, illustrating the length (5 mm), the tip (0.3 mm) and basal (0.6 mm) diameter.

Figure 2

Comparison of the cross-sectional ST area (mean, min and max) over cochlear length of the present study (n = 42 ears, from n = 26 animals) compared to data reported by Fernandez [n = 6 ears, from 3 animals (Fernàndez, 1952)], Thorne et al. [n = 3 (Thorne et al., 1999)] and Salt [n = 1 (Salt, 2023)]. The 1st, 2nd, and 3rd cochlear turns are indicated.

Figure 3

(A) Individual profiles of ST volume over cochlear angle for all specimens of the five different groups with color code: dark red Alb. fresh (n = 10), indigo Alb. frozen (n = 6), yellow Alb. PFA (n = 8), teal Col. fresh (n = 6) and grey Col. frozen (n = 12). (B) Individual ST volume profiles normalized to the mean value at 360°, corresponding mean profile and logarithmic fit. (C) Distribution of individual ST basal diameters A and widths B. (D) Correlation analysis of basal turn length (BTL) computed with the ECA method [with input parameters A and B] (Schurzig et al., 2018b) and the corresponding ST volume at 360°. The constants for the line of best fit determined with the linear regression are V = 1.38 *BTL – 8.36.

Figure 4

Differences in cochlea anatomy for all specimens of the five different groups with color code: dark red Alb. fresh (n = 10), indigo Alb. frozen (n = 6), yellow Alb. PFA (n = 8), teal Col. fresh (n = 6) and grey Col. frozen (n = 12). Black diamonds indicate outliers, black bar above boxplot indicates statistically significant differences, ** p < 0.01, *** p < 0.001. (A) Basal diameter A, (B) basal width B, (C) basal turn length (BTL) computed with the ECA method, with input parameters A and B (Schurzig et al., 2018b) and (D) corresponding ST volume at 360°.

Figure 5

Volume approximation errors (dV) of the 3 derived models (mean, log, scaling) at different angular locations. The mean and log approaches show in part significantly higher deviations than the log model.

Figure 6

(A) Correlation of electrode insertion depth (EID) and insertion angle (IA) for different implant insertion sites (cochleostomy and round window approach). (B) Deviations of predicted and postoperatively measured IAs. (C) Cross-sectional view of a guinea pig CI array (in black) with a 50 μm coating (in red). (D) CI array volume of array alone (black) and with the 50 μm coating (red) dependent on the EID.

Figure 7

Screenshot of the developed software tool. On the left, the user can define the “cochlear dimensions” for computation of the individual ST volume, which is displayed relative to the mean profile ±1 SD of the present study (top left graph). The tool also requires the “CI dimensions” and “Insertion properties,” based on which the array model is generated (bottom left graph) and the remaining perilymph volume inside the ST is computed (top and bottom right graphs). The corresponding volumes are displayed in the right column of the user interface.