In vivo human choroidal thickness measurements: evidence for diurnal fluctuations

Abstract

Purpose: The authors applied partial coherence interferometry (PCI) to estimate the thickness of the human choroid in vivo and to learn whether it fluctuates during the day.

Methods: By applying signal processing techniques to existing PCI tracings of human ocular axial length measurements, a signal modeling algorithm was developed and validated to determine the position and variability of a postretinal peak that, by analogy to animal studies, likely corresponds to the choroidal/scleral interface. The algorithm then was applied to diurnal axial eye length datasets.

Results: The postretinal peak was identified in 28% of subjects in the development and validation datasets, with mean subfoveal choroidal thicknesses of 307 and 293 microm, respectively. Twenty-eight of 40 diurnal PCI datasets had at least two time points with identifiable postretinal peaks, yielding a mean choroidal thickness of 426 microm and a mean high-low difference in choroidal thickness of 59.5 +/- 24.2 microm (range, 25.9-103 microm). The diurnal choroidal thickness fluctuation was larger than twice the SE of measurement (24.5 microm) in 16 of these 28 datasets. Axial length and choroidal thickness tended to fluctuate in antiphase.

Conclusions: Signal processing techniques provide choroidal thickness estimates in many, but not all, PCI datasets of axial eye measurements. Based on eyes with identifiable postretinal peaks at more than one time in a day, choroidal thickness varied over the day. Because of the established role of the choroid in retinal function and its possible role in regulating eye growth, further development and refinement of clinical methods to measure its thickness are warranted.

Figure 1

PCI axial length data showing optimum visualization of the four PCI peaks at the posterior wall of a representative human eye in a signal-averaged waveform. The likely anatomic correlates of the peaks are P1 (inner limiting membrane), P2 (consistent internal retinal peak, perhaps at the outer limiting membrane), P3 (Bruch membrane/RPE interface), and P4 (choroidal/scleral signal). The ambiguity of the location of P4 in this figure illustrates the difficulty of obtaining a precise measurement for P4 given the low signal-to-noise ratio. The noise at the P4 peak precludes simple identification of P4 as the largest peak deep to the RPE. Here the P4 label is placed over the location of P4, as identified by the algorithm. The same problem complicates the curve fitting (see Fig. 3).

Figure 2

Signal-averaged PCI axial length data from three subjects.

Figure 3

Example of a 3-Gaussian curve fit to the signal-averaged and filtered P4-P3 complex. The subject’s waveform (dashed line) has been fit (solid line) with 3 Gaussian curves (gray lines). The leftmost Gaussian (no. 3) is fit to the P4 component of the P4-P3 complex.

Figure 4

Signal-averaged waveform from six time points in a typical diurnal dataset, in this instance for the right eye of subject 2 on testing day 2. The intensity and morphology of P4 varies with each time point. This figure exemplifies how difficult it is to examine the signal-averaged waveform at any single time point and to identify the location of P4. Examining all six time points simultaneously allowed us to more easily identify P4. Dotted lines and solid lines indicate the positions of P3 and P4, respectively, as identified by the P4 algorithm. Note that the waveform from 1 PM showed no apparent P4 on the signal-averaged waveform, but the P4 algorithm identified a P4 for this time point likely because certain bootstrapped subsets of data contained a P4.

Figure 5

(A, A′) Examples from subjects with significant changes in axial length (P3) in whom choroidal thickness fluctuations (P4-P3) are in antiphase with axial length fluctuations. (B) Data from a subject in whom no significant change in axial length was observed and whose choroidal thickness showed little fluctuation over the day. (C, C′) Sample data from subjects with significant changes in axial length and in whom the choroidal thickness fluctuations are in antiphase with the axial length fluctuations for all but one time point (circled). (D) This is the only dataset in which the axial length showed significant change but the choroidal thickness changed little, indicating that choroidal thickness did not account for the observed fluctuations in axial length. (E, E′) Both subjects showed no significant change in axial length, and the choroidal thickness had a mean difference of 2× the SE_measurement, indicating that it likely changed over the course of the day.