Evidence map›Paper›PMID 27446663›Full record

ArticleBiomedical optics express2016

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed.

Alex J Walsh, Joe T Sharick, Melissa C Skala, Hope T Beier

Abstract read
In one paragraph

Article in Biomedical optics express, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Impact of noise on optical redox ratio estimation.bioRxiv : the preprint server for biology · 2026
    Article
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  7. Label-Free Optical Metabolic Imaging in Cells and Tissues.Annual review of biomedical engineering · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alex J WalshNational Research Council, JBSA Fort Sam Houston, Texas, 78234, USA; 711th Human Performance Wing, Human Effectiveness Directorate, Bioeffects Division, Optical Radiation Bioeffects Branch, Air Force Research Lab, JBSA Fort Sam Houston, Texas, 78234, USA.
Joe T SharickDepartment of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, 37235, USA.
Melissa C SkalaDepartment of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, 37235, USA.
Hope T Beier711th Human Performance Wing, Human Effectiveness Directorate, Bioeffects Division, Optical Radiation Bioeffects Branch, Air Force Research Lab, JBSA Fort Sam Houston, Texas, 78234, USA.

Funding

Cellular-level Optical Metabolic Imaging to Predict Drug Response in CancerR01CA185747 · NCI · VANDERBILT UNIVERSITY · PI SKALA, MELISSA CAROLINE · 2014 to 2019
$1.6M
NCI NIH HHS R01 CA185747
6 · The paper itself

Abstract

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide-lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis.

Indexed as

(100.1830) Deconvolution(100.2960) Image analysis(110.4280) Noise in imaging systems(170.2520) Fluorescence microscopy(170.6920) Time-resolved imaging

Identifiers

PMID27446663
PMCPMC4929649

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.