Evidence map›Paper›PMID 34266107›Full record

ArticleOptics express2021

Multispectral fluorescence lifetime imaging device with a silicon avalanche photodetector.

Xiangnan Zhou, Julien Bec, Diego Yankelevich, Laura Marcu

Open access · goldAbstract read
In one paragraph

Article in Optics express, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
8.5field-weighted citation impact, top 3% of its field
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

18 citing papers in PubMed, 37 citations in OpenAlex.

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  12. FLIm-Based in Vivo Classification of Residual Cancer in the Surgical Cavity During Transoral Robotic Surgery.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023
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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 at 1 institution in 1 country.

Xiangnan Zhou
Julien Bec
Diego Yankelevich
Laura Marcu
University of California System · US

Funding

Fluorescence Lifetime Imaging/Spectroscopy System For Robotic Cancer Surgery GuidanceR01CA187427 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI BIRKELAND, ANDREW CHARLES, MARCU, LAURA · 2014 to 2025
$4.6M
Label-free fluorescence lifetime imaging for intraoperative real-time guidance of neurological proceduresR01CA250512 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Orin Bloch, Laura Marcu · 2021 to 2026
$3.0M
NCI NIH HHS R01 CA187427NCI NIH HHS R01 CA250512
6 · The paper itself

Abstract

We report the design, development, and characterization of a novel multi-spectral fluorescence lifetime measurement device incorporating solid-state detectors and automated gain control. For every excitation pulse (∼1 µJ, 600 ps), this device records complete fluorescence decay from multiple spectral channels simultaneously within microseconds, using a dedicated UV enhanced avalanche photodetector and analog to digital convert (2.5 GS/s) in each channel. Fast (<2 ms) channel-wise dynamic range adjustment maximizes the signal-to-noise ratio. Fluorophores with known lifetime ranging from 0.5-6.0 ns were used to demonstrate the device accuracy. Current results show the clear benefits of this device compared to existing devices employing microchannel-plate photomultiplier tubes. This is demonstrated by 5-fold reduction of lifetime measurement variability in identical conditions, independent gain adjustment in each spectral band, and 4-times faster imaging speed. The use of solid-state detectors will also facilitate future improved performance and miniaturization of the instrument.

Identifiers

PMID34266107
PMCPMC8237936
OpenAlexW3166899052

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.