Automatic retinal oximetry.

Sveinn Hakon Hardarson; Alon Harris; Robert Arnar Karlsson; Gisli Hreinn Halldorsson; Larry Kagemann; Ehud Rechtman; Gunnar Már Zoega; Thor Eysteinsson; Jon Atli Benediktsson; Adalbjorn Thorsteinsson; Peter Koch Jensen; James Beach; Einar Stefánsson

doi:10.1167/iovs.06-0039

PubMed · 17065521

Automatic retinal oximetry.

Sveinn Hakon Hardarson·Alon Harris·Robert Arnar Karlsson·Gisli Hreinn Halldorsson·Larry Kagemann·Ehud Rechtman·Gunnar Már Zoega·Thor Eysteinsson·Jon Atli Benediktsson·Adalbjorn Thorsteinsson·Peter Koch Jensen·James Beach·Einar Stefánsson

View original source ↗Export metadata ↓

Abstract

PURPOSE: To measure hemoglobin oxygen saturation (SO(2)) in retinal vessels and to test the reproducibility and sensitivity of an automatic spectrophotometric oximeter. METHODS: Specialized software automatically identifies the retinal blood vessels on fundus images, which are obtained with four different wavelengths of light. The software calculates optical density ratios (ODRs) for each vessel. The reproducibility was evaluated by analyzing five repeated measurements of the same vessels. A linear relationship between SO(2) and ODR was assumed and a linear model derived. After calibration, reproducibility and sensitivity were calculated in terms of SO(2). Systemic hyperoxia (n = 16) was induced in healthy volunteers by changing the O(2) concentration in inhaled air from 21% to 100%. RESULTS: The automatic software enhanced reproducibility, and the mean SD for repeated measurements was 3.7% for arterioles and 5.3% venules, in terms of percentage of SO(2) (five repeats, 10 individuals). The model derived for calibration was SO(2) = 125 - 142 . ODR. The arterial SO(2) measured 96% +/- 9% (mean +/- SD) during normoxia and 101% +/- 8% during hyperoxia (n = 16). The difference between normoxia and hyperoxia was significant (P = 0.0027, paired t-test). Corresponding numbers for venules were 55% +/- 14% and 78% +/- 15% (P < 0.0001). SO(2) is displayed as a pseudocolor map drawn on fundus images. CONCLUSIONS: The retinal oximeter is reliable, easy to use, and sensitive to changes in SO(2) when concentration of O(2) in inhaled air is changed.

Explore related subjects

Humans Hyperoxia Oximetry Oxygen Oxygen Consumption Oxyhemoglobins Reproducibility of Results Retinal Artery Retinal Vein Sensitivity and Specificity Comparative Study Journal Article Research Support, Non-U.S. Gov't

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Sveinn Hakon Hardarson, Alon Harris, Robert Arnar Karlsson, Gisli Hreinn Halldorsson, Larry Kagemann, Ehud Rechtman, Gunnar Már Zoega, Thor Eysteinsson, Jon Atli Benediktsson, Adalbjorn Thorsteinsson, Peter Koch Jensen, James Beach, Einar Stefánsson. 2006. Automatic retinal oximetry.. https://doi.org/10.1167/iovs.06-0039

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

KEEP EXPLORING

Related citations

PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

PubMed2027

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

PubMed2027

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗