PubMed Health⌕ Search

PubMed · 17119557

Modeling the interferometric radius measurement using Gaussian beam propagation.

Abstract

We model the interferometric radius measurement using Gaussian beam propagation to identify biases in the measurement due to using a simple geometric ray-trace model instead of the more complex Gaussian model. The radius measurement is based on using an interferometer to identify the test part's position when it is at two null locations, and the distance between the positions is an estimate of the part's radius. The null condition is observed when there is no difference in curvature between the reflected reference and the test wavefronts, and a Gaussian model will provide a first-order estimate of curvature changes due to wave propagation and therefore changes to the radius measurement. We show that the geometric ray assumption leads to radius biases (errors) that are a strong function of the test part radius and increase as the radius of the part decreases. We tested for a bias for both microscaled (<1 mm) and macroscaled parts. The bias is of the order of parts in 10(5) for micro-optics with radii a small fraction of a millimeter and much smaller for macroscaled optics. The amount of bias depends on the interferometer configuration (numerical aperture, etc.), the nominal radius of the test part, and the distances in the interferometer.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Katherine M Medicus, James J Snyder, Angela Davies. 2006-12-01. Modeling the interferometric radius measurement using Gaussian beam propagation.. https://doi.org/10.1364/ao.45.008621

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Effectiveness of high-dose versus standard-dose influenza vaccines against hospitalisation according to frailty risk: a prespecified analysis of the randomised trial DANFLU-2.

BACKGROUND: Frailty is a major risk factor for influenza-related complications and can influence vaccine effectiveness. We aimed to assess the relative vaccine effectiveness (rVE) of high-dose (HD-IIV) versus standard-dose inactivated influenza vaccine (SD-IIV) in older adults aged 65 years or older according to frailty risk. METHODS: This study was a prespecified analysis of DANFLU-2, an open-label, individually randomised trial, conducted in Denmark during three consecutive influenza seasons (2022-23, 2023-24, and 2024-25). Adults aged 65 years or older were randomised (1:1) to the HD-IIV or SD-IIV group. The primary endpoint was hospitalisation for influenza or pneumonia. Frailty was defined according to the validated Hospital Frailty Risk Score (HFRS) based on ICD-10 codes within 10 years before randomisation. Participants were stratified into three HFRS categories, namely low (<5 points), intermediate (5-15 points), and high (>15 points) frailty risk. The rVE of HD-IIV versus SD-IIV against the primary endpoint was assessed across prespecified HFRS categories and treating HFRS as a continuous variable. Pearson's chi-square test was used to compare safety events across frailty risk groups and randomisation groups. FINDINGS: Among 332&#x2009;438 randomised participants (mean age 73&#xb7;7 years [SD 5&#xb7;8]; 161&#x2009;538 [48&#xb7;6%] were female), 276&#x2009;173 (83&#xb7;1%) had low frailty risk, 52&#x2009;395 (15&#xb7;8%) had intermediate frailty risk, and 3861 (1&#xb7;2%) had high frailty risk. The primary endpoint of hospitalisation for influenza or pneumonia occurred in 1424 (0&#xb7;5%) of 276&#x2009;173 participants with low frailty risk, 761 (1&#xb7;5%) of 52&#x2009;395 with intermediate frailty risk, and 163 (4&#xb7;2%) of 3861 with high frailty risk (relative risk [RR] for intermediate vs low frailty risk 2&#xb7;8 [95% CI 2&#xb7;6-3&#xb7;1]; RR for high vs low frailty risk 8&#xb7;2 [7&#xb7;0-9&#xb7;6]). HFRS as a continuous variable significantly modified the effect of HD-IIV versus SD-IIV against the primary endpoint with higher rVE estimates with increasing HFRS (pinteraction=0&#xb7;020). The rVE was 0&#xb7;2% (95% CI -10&#xb7;8 to 10&#xb7;2) among those with low frailty risk, 13&#xb7;1% (-0&#xb7;4 to 24&#xb7;8) among those with intermediate frailty risk, and 19&#xb7;9% (-10&#xb7;3 to 42&#xb7;1) among those with high frailty risk. No significant interaction was observed when HFRS was assessed according to the prespecified categorical frailty groups (pinteraction=0&#xb7;17). The proportion of participants with at least one serious adverse event increased across frailty risk groups (13&#x2009;366 [4&#xb7;8%] of 275&#x2009;795 for low frailty risk, 5475 [10&#xb7;5%] of 52&#x2009;315 for intermediate frailty risk, and 777 [20&#xb7;2%] of 3850 for high frailty risk; p<0&#xb7;0001), with similar proportions of serious adverse events in the HD-IIV and SD-IIV groups for each frailty risk group. INTERPRETATION: Among adults aged 65 years or older in Denmark, frailty risk might modify the effects of HD-IIV versus SD-IIV against hospitalisation for influenza or pneumonia, with higher rVE estimates with increasing frailty risk. These findings might support considering high-dose influenza vaccines for frail older adults. However, effect modification was not evident when frailty was assessed using prespecified categorical subgroups, and subgroup-specific estimates were imprecise, with 95% CIs crossing the null. These results should be considered exploratory, warranting further investigation. FUNDING: The DANFLU-2 trial was funded by Sanofi.

Journal Article↗