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Etching-enabled extreme miniaturization of graded-index fiber-based optical coherence tomography probes.

ABSTRACT: We introduced and validated a method to miniaturize graded-index (GRIN) fiber-based optical coherence tomography (OCT) probes down to 70???m in diameter. The probes consist in an assembly of single-mode (SM), coreless (CL), and graded-index (GRIN) fibers. We opted for a probe design enabling controlled size reduction by hydrogen fluoride etching. The fabrication approach prevents nonuniform etching for both the GRIN and SM fiber components, while it requires no probe polishing postetching. We found that the miniaturized probes present insignificant loss of sensitivity (?1??dB) compared to their thicker (125???m) counterparts. We also showed that their focusing capabilities remain tunable and highly predictable. The fabrication process is simple and can be carried out by using inexpensive telecom equipment. Both the fabrication process and the developed probes can benefit the prototyping of minimally invasive endoscopic tools.

SUBMITTER: Abid A

PROVIDER: S-EPMC7010983 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Etching-enabled extreme miniaturization of graded-index fiber-based optical coherence tomography probes.

Abid Alexandre A Mittal Shiv S Boutopoulos Christos C

Journal of biomedical optics 20191101 3

We introduced and validated a method to miniaturize graded-index (GRIN) fiber-based optical coherence tomography (OCT) probes down to 70 μm in diameter. The probes consist in an assembly of single-mode (SM), coreless (CL), and graded-index (GRIN) fibers. We opted for a probe design enabling controlled size reduction by hydrogen fluoride etching. The fabrication approach prevents nonuniform etching for both the GRIN and SM fiber components, while it requires no probe polishing postetching. We fo ...[more]

PMID: 31707773

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Project description:PRéCIS:: There are errors in automated segmentation of the retinal nerve fiber layer (RNFL) in glaucoma suspects or patients with mild glaucoma that appear to persist over time; however, automated segmentation has greater repeatability than manual segmentation.PurposeTo identify whether optical coherence tomography (OCT) segmentation errors in RNFL thickness measurements persist longitudinally.MethodsThis was a cohort study. We used spectral domain OCT (Spectralis) to measure RNFL thickness in a 6-degree peripapillary circle, and exported the native "automated segmentation only" results. In addition, we exported RNFL thickness results after "manual refinement" to correct errors in the automated segmentation, and used the differences in these measurements as "error" in segmentation. We used Bland-Altman plots and linear regression to determine the magnitude, location, and repeatability of RNFL thickness error in all twelve 30-degree sectors and compared the error at baseline to follow-up time points at 6 months, 2 years, 3 years, and 4 years.ResultsWe included 406 eyes from 213 participants. The 95% confidence interval for errors at baseline was -6.5 to +13.2 μm. The correlation between the baseline error and the errors in the follow-up time periods were high (r>0.5, P<0.001 for all). Automated segmentation had a smaller SD of residuals from the longitudinal trend line when compared to manual refinement (1.56 vs. 1.80 μm, P<0.001), and a higher ability (P=0.009) to monitor progression using an analysis of a longitudinal signal-to-noise ratio.ConclusionsErrors in automated segmentation remain relatively stable, and baseline error is highly likely to persist in the same direction and magnitude in subsequent time periods. However, automated segmentation (without manual refinement) is more repeatable and may be more sensitive to glaucomatous progression. Future segmentation algorithms could exploit these findings to improve automated segmentation in the future.

Dataset Information

Etching-enabled extreme miniaturization of graded-index fiber-based optical coherence tomography probes.

Publications

Etching-enabled extreme miniaturization of graded-index fiber-based optical coherence tomography probes.

Similar Datasets

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