Evidence map›Paper›PMID 36060422›Full record

ArticleIEEE transactions on radiation and plasma medical sciences2022

Investigation of Electronic Signal Processing Chains for a Prototype TOF-PET System With 100-ps Coincidence Time Resolution.

Shirin Pourashraf, Andrea Gonzalez-Montoro, Min Sun Lee, Joshua W Cates, Jun Yeon Won, Jae Sung Lee, Craig S Levin

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on radiation and plasma medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

2 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Article
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

7 authors at 4 institutions in 2 countries.

Shirin PourashrafDepartment of Radiology at Stanford University, Stanford, CA 94305, USA.
Andrea Gonzalez-MontoroDepartment of Radiology at Stanford University, Stanford, CA 94305, USA.
Min Sun LeeNuclear Emergency & Environmental Protection Division, Korea Atomic Energy Research Institute, Daejeon, Republic of Korea.
Joshua W CatesApplied Nuclear Physics Program at Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Jun Yeon WonDepartment of Nuclear Medicine and Biomedical Sciences, Seoul National University, Seoul, 110-744, South Korea.
Jae Sung LeeDepartment of Nuclear Medicine and Biomedical Sciences, Seoul National University, Seoul, 110-744, South Korea.
Craig S LevinDepartments of Radiology, Bioengineering, Physics and Electrical Engineering at Stanford University, Stanford, CA 94305, USA.
Stanford University · USSeoul National University · KRKorea Atomic Energy Research Institute · KRLawrence Berkeley National Laboratory · US

Funding

Exploring a promising design for the next generation time-of-flight PET detectorR01CA214669 · NCI · STANFORD UNIVERSITY · PI LEVIN, CRAIG S · 2017 to 2021
$2.9M
A new direction to achieve ultra-fast timing for positron emission tomographyR01EB023903 · NIBIB · STANFORD UNIVERSITY · PI LEVIN, CRAIG S · 2017 to 2020
$2.5M
Technologies to drastically boost photon sensitivity for brain-dedicated PETR01EB025125 · NIBIB · STANFORD UNIVERSITY · PI LEVIN, CRAIG S · 2017 to 2018
$984k
NCI NIH HHS R01 CA214669NIBIB NIH HHS R01 EB023903NIBIB NIH HHS R01 EB025125
6 · The paper itself

Abstract

We have evaluated CTR performance of four different mixed-signal front-end electronic readout configurations with the goal to achieve 100 picoseconds (ps) coincidence time resolution (CTR). The proposed TOF-PET detector elements are based on two 3 × 3 × 10 mm

Identifiers

PMID36060422
PMCPMC9432859
OpenAlexW3210025765

What OpenQuestion holds

Textmetadata
LicenceTDM
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.